Engineering Chemistry Volume 12

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Volume 12 of
Engineering Chemistry

ISSN print 2813-6527
ISSN web 2813-6535

Full text available online at https://www.scientific.net/book/engineering-chemistry-vol-12/978-3-0364-3024-9

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Table of Contents

Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Shamo Tapdiqov, Dilgam Taghiyev, Elvin Y. Malikov, Samira Mammadova, Jamila Guliyeva, Ayaz Gulamirov, Seadet Humbetova

Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Ayodunmomi Esther Olowofoyeku, Daniel Gbenga Adekanmi

Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

Oludare Johnson Odejobi, Taiwo Hassan Ibrahim, Olajide Olukayode Ajala

Esterification of Coconut Fatty Acid Distillate (COFAD)
Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

Ian Dominic F. Tabanag, Jae Michelle N. Cabo, Carla Bren S. Legarde, Sam Anthonette L. Suico, Jayhiel S. Malila

Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

Ian Dominic F. Tabanag, Jon Lionel O. Babanto, Kent Antonhel B. Catarig, James Anthony S. Solatorio, Jayhiel S. Malila

Keywords Index

Authors Index

The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-12/978-3-0364-3024-9

Engineering Chemistry, ISSN: 2813-6535, Vol. 12, pp 1-24

doi: 10.4028/p-tEwkt3

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2025-03-11

Revised:
2025-08-15

Accepted:
2025-08-27

Online:
2025-12-15

Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

The original version of this paper is available on https://www.scientific.net/EC.12.1.pdf

Shamo Tapdiqov , Dilgam Taghiyev , Elvin Malikov , Samira Mammadova , Jamila Guliyeva , Ayaz Gulamirov and Seadet Humbetova

Department of "Projecting of influence for Formation and Wellbore zone", SOCAR Oilgasresearchproject Institute, AZ1012, H.Zerdabi Ave., 88a, Baku, Azerbaijan

Department of "Nanostructured Metal Polymer Catalysts", Institute of Catalysis and Inorganic Chemistry, Ministry of Science and Education of the Republic of Azerbaijan, AZ1143, H. Javid Ave., 113, Baku, Azerbaijan

Department of Macromolecular Chemistry, Baku State University, Chemistry Faculty, AZ1141, Baku, Azerbaijan

National Nuclear Research Center of the Republic of Azerbaijan, 77 Z. Aliyeva St., AZ1000, Baku, Azerbaijan

shamo.z.tapdiqov@socar.az, dilgamtagiyev@gmail.com, bsuc@hotmail.com, samira_m@mail.ru, guliyevajamila94@gmail.com, ayaz.gulemirov@gmail.com, seadet.humbatova@inbox.ru

Corresponding author: shamo.z.tapdiqov@socar.az

Keywords: cement, nanoparticle, polymer, magnetite, chemical bonding.

Abstract

The changes in the mechanical and physical properties of concrete prepared by incorporating various metal oxide nanoparticles into cement products used in both the oil/gas industry and construction have been analyzed in this review. The study compares the properties exhibited by transition metal oxides and some metal nanoparticles in both isolated and complex forms with polymers in concrete. Analyses were conducted primarily in the direction of changes occurring in properties due to the addition of metal oxide nanoparticles, such as magnetite , , core/shell , in dispersed form as cement powder or water. It has been shown that appropriate changes occur in properties such as compressive and flexural strength, adhesion, initial and final setting, water absorption, porosity, electrical conductivity, and degradation when metal oxide nanoparticles are added to cement. The density and size of nanoparticles affect their response to various influences, alongside the fundamental properties of the material.

Introduction

The original version of this paper is available on https://www.scientific.net/EC.12.1.pdf

Research on nanostructured materials and their applications continues to expand rapidly in sectors such as oil and gas, electronics, biotechnology, pharmacology, and construction industries. The nanosized form of a matter exhibits unique new properties either independently or in composite form due to its high surface energy. In recent years, extensive research and reviews have focused on metal and metal oxide nanoparticles, as well as their complex interactions with polymer macromolecules [1].
There is no field of science and technology where metal nanoparticles are not applied. Particularly highlighted are industrial sectors such as oil and gas fields and the construction sector. In the oil and gas industry, the use of cement products for the cementation of well zones for water and sand isolation has long been recognized as the most promising technology [2]. Furthermore, the irreplaceable nature of cement in construction and the improvement of cement quality through the addition of various additives have been extensively analyzed in review studies by I.P. Segura [3] and others.

It is known that, depending on the application site, the main controlled properties of cement products include: compressive and flexural strength, adhesion, initial and final values of setting, spreadability, water absorption, porosity, and flowability. Specifically, parameters such as electrical conductivity, light reflectance, and resistance to biological effects are sometimes crucial. For many years, additives have been used at the molecular scale to control these properties [4]. However, the rapid advancement of nanoscience has also made a significant impact in this field, with nano-sized modifying agents achieving superior performance [5].
Based on the above, this review analyzes the physical and mechanical properties of concrete obtained by incorporating various transition metals, their polymer composites, as well as binary core/shell nanoparticles into cement solutions. Also, the methods of filling the more commonly used magnetite nanoparticles into concrete, their distribution in their structure, their interaction with the particles, and the changes caused to the main indicators were compared. In addition, the potential for creating smart concrete systems using certain metal nanoparticles' sensitivity to the environment is extensively discussed and aligned with ongoing research conducted by the authors. Also, the current studies include X-ray and infrared spectroscopic analyses of structural changes resulting from the addition of polymer/magnetite nanoparticles to concrete.

Nanoparticles in Cement and Concrete Research

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In cement research, it is known where the need to add nano-sized additives actually arises. It is a fact that the production of 1 ton of Portland cement requires 1.6 tons of raw materials and releases 0.8 tons of into the atmosphere [6]. By replacing a certain part of the cement component with other additives, it is possible to reduce the consumption of raw materials (which in itself reduces carbon dioxide emissions) and to achieve innovations in quality. This trend can be observed in the statistics of publications dedicated to research conducted over the past 22 years, focusing both broadly and specifically on the addition of nanoparticles to cement [Fig. 1].

Fig. 1. Chronology of research on cement in the past 22 years.

Fig. 1. Chronology of research on cement in the past 22 years.

As can be seen, research in both conventional and nanoparticle modifications of cement has seen a sharp increase since 2010. Statistical analyses indicate that the most referenced and highly impactful
scientific journals in this field include Construction and Building Materials, Cement and Concrete Research, and Materials Today: Proceedings. These publications have been prominent in publishing findings and advancements in this area.
By adding nanoparticles in the production of cement, it is possible to control several parameters during the hydration process of concrete. Research indicates that incorporating nanoparticles in amounts of the cement content can increase the strength of concrete by up to , its diffusion by , and its thermal durability by [7].
In the review by F. Sanchez and K. Sobolev [8], research involving the analysis of cementitious materials and concrete incorporating added nanoparticles has been examined through various spectroscopic characterizations such as NMR, XRD, neutron and X-ray scattering, atomic force microscopy, and others. The authors have demonstrated that nanoparticles, by entering the structure of cement, interact with calcium and aluminum silicate components during the hydration process. In all cases, nanoparticles induce changes in both the surface and internal morphology of cement, thereby influencing its properties. It is known that cement is a crystalline material consisting of a mixture of dicalcium silicate, tricalcium silicate, tricalcium aluminate, tetracalcium alumino ferrite, and lime. The hydration process begins when water is mixed with cement powder, and the additional nanoparticles interact with these components at this stage [9]. While nanoparticles affect the properties of concrete by entering its structure, they do not significantly hinder the hydration process of cement. F. Amor and others [10] have confirmed this by adding zinc oxide ( ZnO ) and titanium dioxide ( ) nanoparticles to cement up to , showing that while metal oxide nanoparticles enhance the hydraulic and photocatalytic properties of cement, they do not significantly delay the hydration process of the mixture. X-ray analyses have revealed that nanoparticles interact with matrix components such as calcium silicate and aluminum ferrite silicate structures through ion exchange.
In the review paper by N.B. Singh and others [11], it has been demonstrated that the properties of concrete prepared from cement with added nanoparticles such as , and are improved. According to analyses, the addition of metal oxide nanoparticles enhances (accelerates) the chemical reactions during the initial hydration period. As a result, the durability properties of concrete are enhanced. The authors attribute this to the involvement of metal oxide nanoparticles in reactions with , which leads to the formation of a more compact microstructure.
In another study [12], the authors have shown that the addition of metal oxide nanoparticles to cement increases the amount of calcium silicate hydrates. This leads to an increase in the mechanical properties of concrete (resistance to compression and bending, wear resistance, etc.). Even the addition of nanoparticles to cement induces the formation of a superhydrate layer in concrete. This layer helps to mitigate other photocatalytic reactions, controls energy transfer within the structure, and reduces heat transfer. Moreover, particles sized at 20 nm regulate the hydration period in cement paste and shorten the initial and final value of setting.
In general, the various applications of nanomaterials in concrete, as well as their associated risks to health and the environment, are topics of discussion. Nanomaterials such as nanosilica, nano- , carbon nanotubes, iron oxides, polycarboxylates, and nanocellulose can enhance the mechanical and thermal properties of concrete while also improving its durability. This capability may contribute to reduced energy use and overall costs in the concrete industry. However, due to uncertainties and inconsistencies in size, shape, and chemical composition, some nanoscale materials can pose risks to the environment and human health [13]. Therefore, the potential beneficial effects and inadvertent hazards of nanoscale materials on the environment should be carefully considered in the coming years. Additionally, the disposal of construction material residues should also be a matter of concern. In the review paper by Yonathan R. [7] and Alexander P. [14], it has been concluded that nanoparticles such as , and clays are highly effective additives for modifying cement products even at low concentrations ( ). The addition of these nanoparticles in such quantities has shown to reduce setting time by hours, alter spread by , increase strength by , and enhance heat resistance - residual strength by . The exceptional properties highlighted in the research are attributed to the small size and large surface area of nanoparticles, which contribute to their unique reactivity.

Metal Nanoparticles as Additives to Cement

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In recent years, the use of nanoparticles in construction materials has garnered significant attention, proving that the nanomodification of cement materials leads to considerable improvements in mechanical properties, compactness, and durability. The incorporation of nano- , nanoclay, nano , carbon nanotubes, and nanofibers into cement-based materials has been steadily advancing. The effects of modifying cement materials with nanoparticles, such as their hydration, filling, thixotropic effects, and chemical reactivity, influence the quality of the binder materials. Results have shown that fillers like nano- , nano- , nano-limestone, nanoclay, and nano- , when applied in optimal doses, yield properties that are significantly enhanced [15].
Metal oxides such as , and CaO in cement can interact chemically over an extended period with added nanoparticles. When nano- particles are incorporated into cement paste, the free CaO ions present can easily react with nano- to form particles. is a semiconductor and exhibits photocatalytic activity against ultraviolet radiation [16,17]. Most research studies indicate that the band gap energy of is approximately 3.5 eV [18]. The isoelectric point of is around pH 3 , and based on these energetic values, cement materials with added nano- can be used to create special materials that can partially provide conductivity [19].
In another study [20], the compressive strength of cement paste and concrete mixed with dispersive water containing , and nanoparticles was investigated. The authors prepared concrete samples by mixing cement with sand and oxide nanoparticles with an average size of 12 nm at a water/cement ratio of 0.4 . The method for preparing the mentioned nanoparticles and incorporating them into the concrete structure can be schematically illustrated as follows [Fig. 2].

Fig. 2. Schematic representation of the procedure for preparing concrete specimens with , and nanoparticles according to M. Kamala [20].

Fig. 2. Schematic representation of the procedure for preparing concrete specimens with , and nanoparticles according to M. Kamala [20].

According to the research, nanoferrite particles occupy certain voids in the concrete, leading to an early hydration process. The increase in compressive strength has proven the effectiveness of using this type of nanoparticle-mixed cement in construction and wellbore zone reinforcement. Meral O. and colleagues [21] investigated the mechanical properties of concrete by adding 0.5-1.25 nano and nano particles, as well as their binary forms, to cement powder. They determined that adding more than nanoparticles decreases the compressive strength of the concrete. The compressive strength of the concrete on the day was , which increased to after 180 days. When using binary nano- , the strength increased to 70 MPa . The addition of nano , whether alone or in binary form with nano , only slightly increased the capillary permeability of the concrete.
Roni R. and colleagues [22] studied the crystal structure stability and chemical bonding characteristics of -filled composite cement for X-ray shielding using X-ray diffraction and Fourier-transform infrared spectroscopy. In the concrete sample, the bond at and the -OH bond at were monitored before and after X-ray exposure. It was shown that these bonds are more durable and continuously interact with the particles in the composite. It was
determined that the optimal composition is a composite, which shows the highest linear attenuation coefficient of for 60 keV , approximately for 70 keV , and for 80 keV .
In the study [23], the effects of , and nanoparticles on cement properties were investigated. A polycarboxylate solution was used as a plasticizer, and the nanoparticles with sizes ranging from 10 to 25 nm constituted of the cement. It was determined that with the presence of nano , the compressive strength of the concrete reached 119 MPa after 28 days of curing. In comparison, this value was 92.3 MPa without the nanoparticles. It was also found that the addition of nano reduced the penetration of chloride ions into the concrete by up to compared to the control.
In another study [24], a concrete sample was partially modified with nanoparticles and rice husk ash to act as a pozzolanic material. Various compositions of concrete were prepared using nanoparticles and a fixed amount of rice husk ash as part of Portland cement. The results indicated that the combination with nanoparticles demonstrated high strength and durability characteristics. It was shown that using more than nanoparticles led to a decrease in strength and durability properties.
The authors [25] prepared nanoparticle concrete using by mass of dextrin in cement with a water/cement ratio of 0.5 [Fig. 3]. They found that dextrin increases the compressive strength of the concrete, while nanoparticles enhance its microbial resistance. Additionally, dextrin raises the spread diameter of fresh cement paste from 20.5 cm to 28 cm , which is advantageous for outdoor applications such as wellbore zone reinforcement. The polysaccharide increases the compressive strength of the concrete from 48 MPa to 57 MPa , which can be effective against dynamic impacts. Considering the bacterial degradation of concrete, nanoparticles improve erosional resistance, leading to greater longevity in both construction and oil well applications in contact with formation waters.

Fig. 3. Schematic representation of the preparation of cement stone modified with dextrin with nanoparticle E. Konował, etc. [25].

Fig. 3. Schematic representation of the preparation of cement stone modified with dextrin with nanoparticle E. Konował, etc. [25].

In another study [26], the special role of zinc oxide ( ZnO ) nanoparticles in improving the properties of cement composites has been emphasized. Zinc oxide nanoparticles possess unique optical, antimicrobial, and photocatalytic properties. These ultrafine nanoparticles exhibit a filler effect and have been shown to influence the hydration reaction in the cement matrix. The application of ZnO nanoparticles provides photocatalytic properties to cement structures. The impact of ZnO nanoparticles on the setting time, microstructure, and strength of cement has been extensively investigated. Research has demonstrated that optimized dosages of these nanoparticles can lead to concretes with high mechanical strength and antimicrobial properties.
The rate and coefficient of water absorption, workability, and hardening time of binary concrete obtained by adding nanoparticles to cement in the amounts of , and by mass were investigated [27]. The results indicated that the use of nanoparticles up to a maximum of by mass allows for the production of durable concrete with reduced water permeability.
nanoparticles improve the filler effect and significantly increase the pozzolanic action, enhancing the densification of the gel phase. Additionally, the increased content of nanoparticles in the composition has led to reduced workability and setting time of fresh concrete.
The authors [28] have shown that the addition of of -sized nano particles to the cement composition resulted in a cumulative heat release of over 72 hours. This value was significantly lower compared to the control concrete, which exhibited a higher cumulative heat release. It is concluded that nano particles accelerate the hydration of cement. The creation of nanoparticles in a core/shell structure with has shown a better effect on cement hydration and isothermal heat conduction calorimetry in terms of pozzolanic effect.
In reinforced concrete structures, the steel-concrete matrix is highly susceptible to corrosion and degradation under the influence of environmental ions (e.g., chloride and sulfate ions). Authors [29] have prepared concrete samples where the addition of certain metal oxide nanoparticles has decreased the ion permeability of concrete while increasing its strength and durability. The addition of metal oxide nanoparticles accelerates chemical reactions during initial hydration, resulting in stronger cement composites. These nanoparticles react with to enhance the formation of calcium silicate hydrate (C-S-H), leading to a more compact microstructure. For example, Zhang and Li [30] demonstrated that adding (by weight of binder) of 15 nm -sized to concrete improves its microstructure and increases resistance to chloride penetration by .
When combined with conventional construction materials, nanoparticles can endow new materials with specific properties suitable for the construction of ultra-high, long-span, or intelligent infrastructure systems. There is potential for nanoparticles, which are part of white cement, to possess photocatalytic properties that can preserve the aesthetic characteristics of architectural and decorative concrete over time [31]. White cement containing photocatalytic, self-cleaning nanoparticles has been used in the construction of the modernist "Misericordia Immersion" church in Romada. Coatings of 15 nm -sized particles have been applied to glass windows for the photocatalytic degradation of dirt particles adhered to the glass [32].
Nano- MgO is a newly researched reactive nanocomponent in cement materials. Due to its soft expansion upon contact with water, Nano- MgO offers significant advantages in cement material production by compensating for shrinkage [33]. Reza et al. have studied the effect of nano- MgO on the microstructure and compressive strength of cement composites [34]. The results have shown that the compressive strength durability has increased by and respectively, after 7 and 28 days in samples containing nano- MgO , while the flexural strength has correspondingly increased by and .
Heikal and others [35] have demonstrated that the application of nano- at a mass ratio in cement paste accelerates the hydration of the cement mass, acts as a nano-filler, and provides better thermal resistance up to compared to other pastes.
There are numerous studies in the literature on how the physical and mechanical properties of cement change with the addition of nanoparticles. One study notes that nano- can accelerate the hydration of Portland cement [36], while another shows that it increases the compressive and flexural strength of cement stone [37]. For pavement applications, the abrasion resistance of concrete with added nano- and nano- particles has been experimentally confirmed [38]. The abrasion resistance of concrete with nano- was more effective than that of concrete with the same amount of nano- . Concrete with nano- has been proven to be very effective in self-cleaning and environmental decontamination. This is because nano- influences the photocatalytic degradation of pollutants [39].
It is known that the clean surface of , with the involvement of sunlight, allows for the oxidation of harmful gases into nitrates, thus removing them from the atmosphere. Photocatalytic concrete blocks for road surfaces have been found effective in neutralizing gases [40]. Surface reactions have been extensively studied using X-ray photoelectron and Raman spectroscopy [41], and nano- -based 'self-cleaning' concrete products have been developed for use on building facades and concrete road surfaces in Europe and Japan.

It has been determined that the fatigue properties of concrete with added nano- particles significantly improve during bending, and this increases its sensitivity to stress changes. Concrete with nano- has been experimentally proven to exhibit better flexural fatigue properties than concrete with polypropylene fibers, which are widely used for road surfaces [42].
The photocatalytic properties of nano- can be efficiently used to clean certain environmental pollutants under ultraviolet radiation. Thus, cement-based coatings, including nano- , are more suitable for use on the exterior surfaces of buildings. Due to the high agglomeration of nanoparticles in the cement environment, their photocatalytic activity is significantly reduced [43]. The effective prevention of external agglomerations can be achieved by using nanoparticles in a dispersed form in lime-saturated solution within cement mixtures. The microstructural properties of concrete with nano- additives have been studied by Feng and others [44], and it has been determined that nano- in the cement matrix facilitates the formation of a homogeneous dense calcium silicate hydrate gel. Additionally, nano- particles ensure the continuous distribution of hydration throughout the cement matrix.
In another study [45], the application of nano- improved the pore structure, increased the density of the concrete by acting as filler, and activated the hydration of the cement while reducing the size of calcium hydroxide crystals. When the amount of nanoparticles exceeded , the formation of crystals was limited due to restricted growth space. As a result, the microstructure became more porous, negatively affecting the compressive strength of the cement matrix.
Farzadnia [46] determined that concrete with nano- additives exhibited higher compressive strength, brittleness, and gas permeability up to a temperature of compared to the control sample. Due to the nanoparticles, the mass loss decreased, and although the average mass loss of the control concrete was up to , for concrete with nano- , the mass loss was and , respectively.
Various researchers have studied the properties of concrete with two or more nanoparticles. Zhang [47] investigated the properties of -graphene composites added to cement at mass ratios of , and . Compared to the control concrete, compressive strength increased by , and flexural strength increased by . By using filler at a mass ratio, the capillary sorption coefficient decreased by 1.2 times, and a reduction in chloride penetration was observed.
Guo and others [48] determined that the addition of a -graphene complex to a polymer epoxy matrix reduced the capillary sorption capacity of cement stone by and the chloride diffusion rate by .
, with its self-cleaning and antibacterial properties, and , which forms significant mechanical properties, have been studied for their combined use in producing concrete samples. The negative charges on the surface of the nanocomposite can be evenly distributed in the concrete mixture, significantly improving compressive and flexural strength, as well as dynamic compressive capacity [49]. Another study demonstrated that using by mass of reactive powder increased the compressive strength of concrete by , and using increased the flexural strength by [50].
nanoparticles are very effective in increasing the elastic modulus of cement mortar. For instance, the elastic modulus of cement mortar with nanoparticles increased by over 143 days [51]. A proper mixing procedure was selected to ensure the adhesion of nanoparticles to the sand surfaces. Effective compaction with nanoparticles resulted in a significant increase in the elastic modulus of the paste. However, when the nanoaluminum content exceeded , the agglomeration of nanoparticles led to inefficient compaction, resulting in a decrease in the elastic modulus of the mortars.
The effect of adding synthetic nano particle powder to cement on the strength of Portland cement paste has been studied [52]. The addition of nano- powder to cement resulted in a decrease in porosity and permeability, an increase in compressive strength, and an improvement in the microstructure of the cement paste. Both pore filling and overlapping were identified as possible enhancement mechanisms.

Han and others [53] investigated the change in resistance during the compression of cement mass containing two types of nanoparticles (i.e., anatase and rutile-based) and nanocarbon fiber. It was observed that cement paste with anatase-based nano- (i.e., polymorphic ) exhibited pressure-sensitive characteristics, whereas paste with rutile-based nano- not. The cement paste containing carbon fiber had the best pressure sensitivity at the lowest resistance. The rate of resistance decrease was for nano- (anatase) paste and for carbon fiber paste.
Results of zeta potential and particle size distribution indicated that high agglomeration of nano- occurs in the cement paste with the usual mixture. A proper mixing scheme of dispersing nano- in saturated lime water by ultrasonication and subsequently adding the resulting suspension to cement powder not only leads to the correct distribution of nano- in the cement but also enhances the photocatalytic properties of the nanoparticles in the cement under ultraviolet irradiation due to the formation of [54].
To better understand the effect of nano- on the properties of cement-based materials, the hydration process, the increase in compressive strength, and the drying and pressing of cement-based materials with the addition of 2 nm nano- were investigated. The results showed that nano- accelerates the hydration of cement and the cleaning of pores, increasing the compressive strength of the cement paste: by mass of nano- accelerates the hydration process of cement by 2 hours and reduces the most probable pore size by up to . For comparative study, was also used. The results indicated that [55] reducing the wetting angle and improving the pore structure with the addition of nano- reduced water loss with hardened cement paste, resulting in pressing comparable to that of the 1-month control sample.

Concrete Samples with Magnetite Nanoparticles and İmproved Properties

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As mentioned, the addition of iron oxide nanoparticles to concrete results in improvements in its properties, particularly in durability. In the study [56], the mechanical properties of Portland cement were investigated by adding magnetite colloidal solution at ratios of , and . It was shown that the compressive strength of magnetite nanoparticle cement paste increases at all ages of hydration. For instance, the compressive strength increases from to 850 over 100 days. According to XRD results, magnetite nanoparticles slightly increase the crystallinity of the concrete. This is reflected in the thermal behavior observed by DSC, where the main decomposition starts at , whereas in pure cement concrete, this process is observed at a relatively lower temperature.
Authors [57] determined that when the ferrite content in cement for well cementing is high, the concrete possesses greater hardness. Based on petrographic results, the lithological structure of highferrite oil well cement is evenly distributed, and the particle size is moderate. Additionally, according to XRD and DTG analyses, the hydration products in the cement paste are more tightly bonded, resulting in a more compact structure. Studies were conducted by adding iron slag to cement in amounts ranging from to of the total mass. It was shown that the elastic modulus becomes optimal when the iron slag content is over 3 and 7 days.
In another study [58], thermal treatment of cement powder containing (by mass) of magnetite nanoparticles with sizes ranging from 50 to 100 nm was conducted at temperatures ranging from 200 to . The prepared magnetite nanoparticle concrete exhibited a increase in tensile strength after thermal treatment at . The mechanical properties after heating to were comparable to those of untreated samples. Compressive strength also increased by after treatment at . The authors demonstrated that magnetite nanoparticles can preserve the integrity of the concrete matrix during thermal perforation.

Fig. 4. According to Pawel Sikora [58], indicators of compressive and flexural strength of concrete stone due to nanoparticles.

Fig. 4. According to Pawel Sikora [58], indicators of compressive and flexural strength of concrete stone due to nanoparticles.

In studies [59], it has been observed that without metal nanoparticles, the mechanical properties of polymer-modified cementitious mortar can also be enhanced. Concrete prepared by adding butadienestyrene emulsion ( by mass) has been extensively researched for water absorption, compressive/flexural strength, spreadability, splitting tensile strength, and surface morphology. It has been determined that the use of 1% SBR increases compressive strength from 52.29 MPa to 65.58 MPa over 28 days. Splitting tensile strength also increases from 3.58 MPa to 4.76 MPa when compared to the control. The incorporation of long-chain polymer macromolecules into the visible cement particles connects them. Chemical interaction of calcium silicate structures with copolymer compactifies individual concrete fragments. As a result, the durability and elasticity of the concrete sample are strengthened. As seen, as the emulsion content increases, the material becomes more amorphous, thereby increasing elasticity. When polymer is used, compressive strength reaches its maximum.
The authors [60] have demonstrated that adding 1% nano to the concrete composition exhibits long-term high electrochemical stability. Even after exposing the concrete sample to chlorine and gases for 300 days, the indicators remained unchanged. Additionally, after 28 days, concrete absorption decreased while the elastic modulus and axial compressive strength increased. Magnetite nanoparticles prevent micro-cracks in the cement matrix, contributing to its long-term durability, as evidenced by SEM micrographs by the authors.
In another study [61], the influence of magnetite nanoparticles on the durability of concrete under varying temperatures was investigated. The authors demonstrated that adding 1% nano to cement limits its mass loss to less than at . The maximum flexural strength occurs at , reaching up to 13 MPa , and decreases thereafter, reaching at . Compressive strength peaks at between but decreases to 10 MPa at . These findings indicate that magnetite nanoparticles not only enhance the mechanical properties of cement concrete but also increase its thermal stability. Moreover, they help preserve the integrity of concrete surfaces by preventing cracking at high temperatures, as evidenced in SEM studies conducted by the authors. In another study [62], nano particles were added to cement powder (mixing and preparation temperature ) with a water-cement ratio of 0.35 . The prepared concretes were heated up to , held for 3 hours, and their mechanical properties were studied. The processes involved in the synthesis of magnetite nanoparticles and the preparation of concrete can be schematically represented as shown below [Fig. 5].

Fig. 5. Preparation of magnetite nanoparticle concrete derived from organic iron salts and evaluation of its compressive strength [62].

Fig. 5. Preparation of magnetite nanoparticle concrete derived from organic iron salts and evaluation of its compressive strength [62].

The author investigated the increase in chemically bonded water in the composition due to the presence of nano . This is explained by the nanoparticles acting as nucleation sites during the hydration process, resulting in the formation of more hydrated hydrates. The compressive strength values of the concrete after different thermal treatments with various amounts of added magnetite nanoparticles can be seen in [Fig. 6].

Fig. 6. Dependence of compressive strength values on temperature treatment for concrete filled with and nano .

Fig. 6. Dependence of compressive strength values on temperature treatment for concrete filled with and nano .

As can be seen, the inclusion of nano in the cement structure enhances its durability. Nanoparticles regulate the hydration process by forming a more homogeneous and compact matrix during hydration. Following the other studies by Hui Li [63], the sensitivity to pressure of cement with added nano was investigated. It was found that nano does not reduce the sensitivity of the cement stone. It was shown that when the concrete contains nano , its volume resistance decreases by (stress-sensing sensitivity). Additionally, as the load is applied to the concrete, the electrical resistance of the sample decreases. The authors explain this by the convergence of nano- particles during concrete compression, creating a tunneling effect that intensifies the current flow. Such materials are significant for load detection, evaluation, and the creation of self-diagnostic materials.
Nano- particles not only enhance the durability of the concrete but also improve its fire resistance. In the study [64], was thermally decomposed at , and [Fig. 7], and then added to the cement composition ( ) to investigate the mass loss.

Fig. 7. Preparation of fire-resistant concrete by adding iron-acetate-sourced nanoparticles to cement powder, mass loss, and durability changes [64].

Fig. 7. Preparation of fire-resistant concrete by adding iron-acetate-sourced nanoparticles to cement powder, mass loss, and durability changes [64].

It was determined that cement paste incorporated with nano- shows the lowest weight loss up to . As the amount of nano- increases to , the weight loss also increases. The authors attribute this to the effect of nano- , enhancing the formation of hydration products that precipitate in the open pores with low free water content. Cement paste containing nano- , when treated at , increases in compressive strength from 75 MPa to 110 MPa compared to the control.
The authors [65] studied the physical and chemical properties by adding and particles smaller than , as well as 50 nm NiO nanoparticles, in amounts ranging from to to cement. They showed that the compressive strength of concrete with magnetite nanoparticles can increase by up to after 7 days. After 28 days, this increase is compared to the control. As the amount of nanoparticles increases, durability also increases. Although nanoparticles increase the density of the cement, they have a slight effect on the water absorption capacity of the concrete. For example, nano- only slightly changes the absorption capacity, resulting in wellcrystallized microstructures, with nanoparticles coherently associated with cement particles and wellcompacted.
In this study [66], green magnetite nanoparticles were synthesized using plant-based raw materials. These nanoparticles were applied as electrically conductive fillers in cement mortars formed by replacing sand with fine aggregates from two types of industrial waste: steel slag and mill scale. The study examined the effects of water/cement ratio, the content of green conductive fillers, and industrial waste on the electrical resistivity and compressive strength of the prepared mortars. The results indicated that increasing the content of conductive fillers decreased electrical resistivity and increased compressive strength. According to response surface analysis results, the optimal electrical resistivity of the smart cement-steel slag mortars was found to be . The authors also developed a mathematical correlation between electrical resistivity and compressive strength.
Khoshakhlagh and colleagues [67] investigated the hydration heat of cement pastes modified with nano- over 70 hours. They conducted measurements by adding nano- to the cement at proportions of , and by weight. The results indicated that adding up to by weight of nanoparticles positively influenced the hydration process, accelerating it and yielding favorable results in calorimetry tests.
Research has shown that nano- can enhance the compressive and flexural strength of concrete while also providing self-healing capabilities, making it invaluable for real-time structural health monitoring and the construction of smart structures [68].

Nazari and colleagues [69] investigated the performance of concrete with partial modification of cement using nanoparticles. In their experiment, nanoparticles with an average diameter of 15 nm were used in proportions of , and by weight of the cement. The results indicated that as the content of nanoparticles increased, the performance of the concrete decreased.

Cement Stones Modified with Polymer-Metal Nanoparticles

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Sometimes, polymer-nanoparticle composites are highlighted to regulate both the mechanical and rheological properties of prepared concrete samples. While the polymer regulates the elasticity and hydration processes of the concrete, the metal nanoparticles enhance parameters such as compressive and flexural strength. In the study [70], the surface of the cement stone was investigated by using curana fiber stabilized with polyaniline and magnetite nanoparticles as a binder. They showed that plant fiber increases the adhesive properties of the cement. Polyaniline-modified fiber ensures a stable and durable chemical bond between the cement components and nanoparticles. The inclusion of fiber and polymer in the concrete structure makes it lighter, while magnetite nanoparticles enable electromagnetic properties in the concrete. Additionally, the hydrophobic polymer prevents the sample from getting wet, limiting the formation of cracks.
There are numerous studies that demonstrate the improvement in durability by adding polymernanoparticle emulsions to cement. In the study [71], a polymer nanocomposite latex with butadieneC nanotubes was synthesized. By adding the obtained carbon nanotube latex composite to the cement (specifically up to of the volume of water), they observed that the compressive strength of the concrete increased from 18 MPa to 19.5 MPa , and the flexural strength increased from 16.5 MPa to 17.4 MPa . The authors explained that the adhesive capability of the polymer latex ensures the mutual adhesion of cement particles. The additive effectively controls liquid loss for hydrostatic pressure and hydration, while also increasing surface tension in the cement paste during fresh hydration, preventing early shrinkage and breakages. As a result, the modulus of elasticity increased by , and the flexural strength increased by .
In the present study, the nature of the chemical interactions formed in the composition by the simultaneous inclusion of poly-N-vinylpyrrolidone (PVPr) and magnetite nanoparticles into the cement structure was studied [72]. For this purpose, cement samples were prepared by adding PVPr and 1-2% magnetite nanoparticles to tamponade cement with a water/cement ratio of 0.5 (by dry weight of the cement). The FTIR and XRD spectra of the obtained concrete samples were comparatively analyzed. It is known that concrete made from cement is a material with a hard structure, mainly consisting of calcium and aluminum silicates, constructed with ionic bonds. For comparison, the XRD spectra of hydrated cement, PVPr concrete, and PVPr/ concrete stones were obtained. It is known that the XRD spectrum of concrete made from cement [73] shows specific peaks for di- and tricalcium silicates, as well as calcium-aluminum silicates, at , , and ( ). Concrete made with PVPr shows slightly different XRD patterns compared to its predecessor. PVPr is an amorphous substance and, being in composition, does not form distinct peaks in the X-ray spectrum [74]. However, since the polymer interacts with silicates in the cement, it causes some peaks to decrease in intensity or shift at certain values. Such shifts are particularly noticeable at , and . The formation of a secondary line at proves the immobilization of PVPr in the cement structure. It was found that increasing the amount of magnetite nanoparticles in the concrete composition leads to the clarification of characteristic peaks in the X-ray spectrum and a certain increase in their intensity. Additionally, the harder crystal structure of magnetite nanoparticles further strengthens the X-ray spectrum of the concrete. It is known that iron atoms in magnetite nanoparticles are not in an ionic form (charged) but are composed of particles with sizes ranging from . The observation of characteristic peaks in values, typical for magnetite nanoparticles, indicates that the nanoparticles have not undergone size changes in the concrete.
According to FTIR results, the inclusion of PVPr macromolecules in the concrete composition leads to the observation of some peaks specific to the polymer in certain regions. Additionally, the chemical
interaction of functional groups in PVPr with elements in the cement causes chemical shifts in some regions characteristic of concrete. It is known that in the FTIR spectrum, PVPr exhibits absorption bands at 1646 and corresponding to the and -OH groups, respectively [75]. Additionally, bands are observed at for the asymmetric stretching of in the pyrrolidone ring, at for in the polymer chain, and at for the vibrational stretching of attached to C-N [76]. Although the FTIR spectrum of PVPr concrete does not show distinctly new peaks with different intensities, absorption bands with slight modifications are observed.
According to the FTIR results of PVPr concrete, the polymer is embedded in the pores of the concrete and actively interacts chemically with the metal silicates. The carbonyl groups in PVPr are involved in the main interaction. Specifically, the absorption band at characteristic of the carbonyl group in pure PVPr shifts chemically to the region in the concrete. This, in turn, causes slight chemical shifts in some bands characteristic of silicates in the concrete.
Based on the results of FTIR spectroscopy, XRD, and TGA investigations, the chemical bond formed between the cement particles and the polymer chains can be schematically represented as follows [77]:

Fig. 8. Schematic representation of the preparation of PVPr-modified concrete and the chemical interaction between particles.

Fig. 8. Schematic representation of the preparation of PVPr-modified concrete and the chemical interaction between particles.

All this proves that PVPr macromolecules are immobilized in the pores of concrete with silicates, and similar results are found in other studies [78]. The inclusion of PVPr-coated magnetite nanoparticles in the concrete results in the formation of oxide-related absorption bands in the FTIR spectrum [79]. Specifically, the characteristic absorption band for magnetite nanoparticles is observed at , and the carbonyl group peak of PVPr, which is actively chemically interacting with nanoparticles, shifts to the region. In other regions, the characteristic absorption peaks of silicates in cement show only slight chemical shifts. This indicates that magnetite nanoparticles are more actively chemically bonded with PVPr in the concrete structure, while they are relatively passively bonded with cement components. This can be explained by the faster interaction of Ca and

Al silicates with water molecules and PVPr during the cement hydration phase. Additionally, considering that magnetite nanoparticles are mixed with cement powder in a complex with PVPr macromolecules, it is understandable that iron oxide molecules are more concentrated around the polymer.

Concrete Structures with Core/ShellNanoparticles

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In some studies, the combined addition of silicon oxide and metal nanoparticles to cement has resulted in superior properties. For example, in the study [80], the mechanical properties were investigated by adding nano and nano to the cement composition. The authors showed that as the amount of nano- increases, compressive strength increases by and over 7 and 28 days, respectively. Additionally, flexural strength increases by and . Although the nanoparticles fill the pores in the cement stone, they act as activators in the hydration process. When nano- is added to cement together with nano- ( 9.0 g of nano- of nano per of cement), compressive and flexural strength increase by up to . The authors demonstrated that nanoparticles evenly distributed within the cement paste act as nuclei and form conglomerations by gathering cement particles around them (due to their high surface energy) during the hydration process. The chemical bond between the nuclei and the transmitting substances strengthens the concrete.
In the study [81], both nano- and nano- were added separately and together, and the stability, pore structure, flexural strength, and other properties of -modified cement stone under 60 kPa pressure and humidity were investigated. The authors showed that at low pressure, the cement stone gets damaged, and erosion products like , and form in the presence of free . The nano-modification reduced the number of harmful pores larger than 50 nm and blocked the eroded in the samples.
The authors [82] created -sized core/shell structures by treating magnetite nanoparticles with tetraethyl orthosilicate. They prepared a dispersed solution of nano- particles and cement paste ( ) and investigated Young's modulus. They determined that concrete samples containing 1-5% nano particles had improved elasticity modulus. Although deterioration in mechanical properties was observed at nano , Young's modulus was 0.056 and 0.013 GPa at nano , respectively. Local agglomerates formed due to the uneven distribution of nanoparticles in the cement matrix, increasing the porosity of the cement stone. The chemical explanation was attributed to the increased amount of hydrate due to the pozzolanic reaction of the nanoparticles with .

Cement Mortars Treated with Metal Salts

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In some studies, the addition of not only metal nanoparticles but also nitrates, sulfates, and organic salts of certain metals to cement has been shown to enhance both the initial and post-hardening mechanical properties of the cement mixture. The addition of metal salts to cement affects not only the mechanical properties but also the initial hydration process, allowing control over the hardening process. In the study [83], the effects of certain metal nitrates on the early hydration process and the properties of hardened cement pastes were investigated. Heavy metal ion nitrate salts (lead, cadmium, and nickel) were added to hydrated cement composites at of the cement weight, and their impact on mechanical properties was comprehensively evaluated. It was determined that these salts affect the rate of cement hydration, with Pb compounds significantly slowing down the hydration process. As a result, compressive strength is very low during rapid hardening, and some properties weaken compared to the control.
In another study [84], the effects of chloride salts of alkali, alkaline earth, and transition metals on the hydration and mechanical properties of iron-rich calcium aluminate cement were investigated. The addition of alkali metal salts accelerates the hardening time of cement in the order of , while the long-term strength deteriorates as the ion radius of the metals decreases. The authors explained this by the formation of tetrahedral symmetry by lithium cations. The effect of alkaline earth metal chlorides was related to their concentrations. salt solutions slightly delayed the hardening time of the cement, while higher concentrations caused a sudden acceleration of
hardening. Transition metal chlorides delayed hardening in the order of . The authors attributed the delay effect to the deposition of a protective amorphous gel on the particle surfaces, which inhibits the growth of crystalline hydration products and blocks hydrolysis.
The X-ray, hardening time, and compressive strength of high-Al cement mixtures were investigated using , and Mg salts at various concentrations [85]. The addition of 100-15000 ppm to cement proved the effectiveness of metal salts in converting metastable hydrates to stable hydrates.
In another study [86], the effect of mixtures consisting of alkali slag activated with various concentrations of ion salt solution , and on the mechanical strength of cement was investigated. The results showed that numerous micro-pores form in the sample with high concentrations of replacing -silicate, reducing the cement's binding strength by , on the other hand, helps to form dense internal structures and highstrength fillings. Magnesium ions adsorb , reducing alkalinity, significantly affecting the disintegration of slags, but accelerating the dissolution of desulfated gypsum.
Magnesium-phosphate cement was prepared using magnesium oxide, ammonium dihydrogen phosphate , and potassium dihydrogen phosphate salts [79]. As a result, the cement exhibited high strength and hydration temperature. Additionally, the addition of sodium orthophosphate significantly improved the mechanical properties of the cement and extended its hardening time.
The authors [87] investigated the effects of , and Cd metal salts on Portland cement with a 0.4 water/cement ratio at by mass. They showed that low doses of metal nitrate additives reduce the hydration of the cement by up to and simultaneously decrease its porosity.
Tests and permeability tests were conducted on cement-bentonite mixtures with various hardening times using solutions [88]. The results showed that permeability negatively affects the hydraulic properties of the cement-bentonite mixture, depending on the sulfate concentration and mixture composition. It is also important to select a very low-permeability mixture to limit the negative effects of interaction on hydraulic properties. It was determined that although the sorption of ions by cement-bentonite is significant, hardening remains stable.
Some studies on the application of cement slurries filled with metal nanoparticles in the oil and gas industry have been conducted. It has been shown that using hematite [89] and perlite [90] in nanoparticle form, compared to larger sizes, does not cause problems such as weight increase and settling. This positively affects the thermal conductivity of the cement paste, increasing its stability. Based on the findings of this study[91], to more precisely determine the chemical role of magnetite nanoparticles in the structure, cement paste was also prepared in the presence of iron salts, and the X-ray spectra were compared. It has been determined that the addition of iron ions to the cement paste significantly affects its hydration and hardening process. Metal ions hinder the hydration of Ca and Al silicates in the structure during the hardening process of concrete, leading to the formation of a brittle structure. X-ray analyses suggest that a PVPr addition does not affect the crystal structure of concrete. On the contrary, it ensures long-distance bonding by creating coordination links between the Ca and Al silicates in the cement. Incorporating magnetite nanoparticles with the polymer into the concrete further hardens the structure and fills some voids in the pores. Moreover, PVPr chains function as bridges between cement particles and magnetite nanoparticles in the concrete. The role of magnetite nanoparticles in such link functions has been observed in various studies. Despite the iron ions being present at only of the cement mass, their active interaction with silicates is evidenced by the characteristic lines in the spectrum. The active chemical interaction of iron ions with silicates causes a sharp decrease in the intensity peak at , characteristic of . On the other hand, the passive presence of PVPr results in the disappearance of the broad band characteristic of -OH groups in the region.
Comparative analysis of FTIR spectra indicates that the addition of PVPr-containing magnetite nanoparticles to the solvent used for preparing cement paste does not hinder its hydration process. The homogeneous distribution of polymers and iron oxides in the structure ensures that PVPr-silicate and silicate bonds are distributed throughout the entire volume and surface, rather than
being localized. This ensures that the mechanical properties are maintained uniformly throughout the concrete. Research has shown that the mechanical properties of polymer/cement systems are strengthened due to macromolecular chains [92].
In another study, the authors investigated the mass changes of concrete filled with polyacrylamide/ nanoparticles (by cement mass) in seawater and formation water. Additionally, the IR and X-ray characteristics of the prepared samples were analyzed to determine the chemical state of the polymer and nanoparticles in the structure. It is known that the composition of concrete during operation is adjusted based on environmental conditions and the place of application. In the study, concrete samples were prepared by adding magnetite nanoparticles synthesized in a polyacrylamide medium to Portland cement. After 28 days of complete hardening, the mass changes in the hardened stones were studied in the Caspian Sea and formation water and compared with the control concrete. It has been determined that both the control concrete and the concrete with PAA/Fe3O4 nanoparticles underwent the same degree of adsorption process over 10 days. The concrete with nanoparticles experienced more mass increase, with the sample showing up to adsorptive mass change over 40 days. As seen, the penetration of ions is limited in the nanoparticle concrete, resulting in even smaller mass changes compared to the control concrete. Overall, it is visible that after 40 days, the mass increase stabilizes in all cases. It is assumed that the higher adsorption in the nanoparticle concrete sample is due to the magnetite particles. PAA macromolecules ensure the long-term stability of the magnetite nanoparticles' size. As the PAA-coated magnetite nanoparticles are dispersed at (by weight), they allow for the formation of pores that enable water molecules to penetrate the inner layers. As the concentration of magnetite nanoparticles increases, the concrete surface becomes hydrophobic, making it difficult for salt ions and water molecules to penetrate. Since adsorption occurs only on the surface, the iron oxides protect the penetration of hydrated ions into the concrete.
Observations made in formation water, compared to seawater, resulted in relatively different outcomes. The control concrete sample showed a mass increase over 40 days in formation water. In the concrete modified with magnetite nanoparticles and PAA, the adsorption of formation water increased with the quantity of nanoparticles. However, in this case, the concrete filled with PAA exhibited maximum ion adsorption. As the amount of polymer-coated magnetite nanoparticles increases, the penetration of ions becomes more difficult, reducing water adsorption. Naturally, this is due to the different chemical compositions of the waters when compared to seawater. It is known that the average salinity of the Caspian Sea water is , with carbonates and sulfates being predominant, while chlorides are less prevalent. In the formation waters of the Absheron Peninsula regions, the concentration of is high, with mineralization ranging from 3.1 to 45.5 . Depending on the location, the amounts of and ions in formation waters are 0.8-15.1 and , respectively. The richer chemical composition of formation water also affects the adsorption capacity of concrete. Compared to inorganic ions, the presence of organic molecules and dispersed oil emulsions in the composition hinders the penetration of ions to some extent. However, in both water samples, the adsorption is characterized by maximum values in the concrete containing . The concrete filled with PAA/Fe shows more adsorption in seawater. However, in both water environments, as the amount of filler in the concrete samples increases, adsorption begins to decrease. This is due to the magnetite nanoparticles forming stable chemical bonds with the cement components and PAA, altering the surface structure of the concrete. Magnetite nanoparticles chemically interacting with calcium and aluminum silicates in the cement result in the formation of complexes that cannot be hydrated on the surface and in the volume. Additionally, more pores in the concrete being blocked by complexes limit the penetration of ions in the environment. The adsorption impact of magnetite nanoparticles was also tested in PAA/concrete samples. It was found that adsorption values in PAA-containing concrete in the same waters were higher compared to magnetite nanoparticle concrete. This can be explained by the hydrophilic tendency of PAA macromolecules. Kinetic measurements over 40 days suggest that adsorption stabilizes, and mass change ceases. However, kinetic mass change should be calculated over a longer period. For this purpose, research in this area is currently ongoing, and results
will be re-evaluated for at least one year. Nevertheless, concrete samples filled with magnetite nanoparticles can be used to construct durable pillars resistant to seawater. Also, it is possible to create long-term barrier rings from those cement pastes by cementing the well bottom zone and the back of the pipeline in the oil industry.
Adding and magnetite nanoparticles by weight to the concrete caused some structural changes. The chemical interaction of magnetite nanoparticles with Ca and Al silicates in the cement led to a reduction and shift in the intensity of the characteristic peaks observed in the XRD patterns of the concrete. These changes indicate that the magnetite nanoparticles chemically interacted with the di- and trisilicates of Ca and Al in the cement. The new peaks also suggest that the magnetite nanoparticles were immobilized in the cement pores without significant size change.
The chemical interaction between magnetite nanoparticles and cement components was also analyzed using FTIR. The chemical interactions formed between di- and tri-Ca silicates in the cement, PAA macromolecules, and magnetite nanoparticles were reflected in the absorption bands of the FTIR spectra. Electron density accumulation in functional groups and oxides led to deformation and vibration changes in the chemical bonds due to chemical interactions. Comparative analysis of the FTIR spectra of free PAA, hydrated cement without polymer, and PAA-added cement was performed. It was determined that the primary chemical shift in the modified PAA was the amine group, which shifted from in the polymer to an absorption band at in the concrete, indicative of chemical interaction with calcium and aluminum ions and their silicates in the cement. This is because the amine group with a certain electron density enters into coordination with and ions in cement. Additionally, the absorption band corresponding to the carbonyl group in the polymer shifts from to . All these observations indicate the interaction between PAA and cement particles, which is not observed in the FTIR spectrum of the pure concrete sample.
In the oil and gas sector, the use of cement products for the separation of water and sand in wellbore zones has long been recognized as the most promising technology. It is possible to strengthen the physical and mechanical properties of concrete by adding various transition metals, their composites with polymers, as well as metal nanoparticles to the cement solution. Furthermore, evaluating the environmental sensitivity of metal nanoparticles can lead to interesting findings regarding the behavior of concrete in various mineralized waters. In another study [94], 1.0 and magnetite nanoparticles of size were added to cement paste modified with (mass) PVPr, and the adsorption capacities of the hardened stone in formation water and seawater were tested after 28 days. Concrete samples containing and nanoparticles show the same adsorption capacity. However, concrete with magnetite nanoparticles exhibits more mass increase in both seawater and formation water. The increase in the penetration of cation and anion hydrates with the proportional increase in the amount of magnetite nanoparticles is related to another factor. It is possible that magnetite nanoparticles are not protected during localization in the concrete structure. Due to the high surface energy of the specific surface, nanoparticles easily interact with hydrated ions. This relationship is proportional to the concentration of magnetite nanoparticles, leading to faster and higher penetration of hydrated ions in the PVPr/concrete sample with . Despite chemical differences between wellwater and seawater compositions, the penetration of ions into magnetite nanoparticle concrete occurs to the same extent. It seems that the difference in adsorption occurs not with the concentration of cations and anions, but with their hydrate form. Polarized water dipoles can form electrostatic interactions with magnetite nanoparticles.
Numerous studies have demonstrated that the incorporation of nanoparticles significantly enhances the mechanical properties and durability of cement-based materials. Nanoparticles contribute to a more compact microstructure, mitigate crack formation, and improve compressive and flexural strengths [95]. In addition, they accelerate the hydration process and promote the formation of welldeveloped C-S-H phases, resulting in superior mechanical performance. These advancements underscore the potential of nanoparticles as effective modifiers for the design of next-generation highperformance cementitious composites. The incorporation of magnetite ( ) nanoparticles into cement-based materials has been shown to significantly enhance their mechanical properties [96].

These nanoparticles contribute to a denser and more homogeneous microstructure, thereby improving compressive strength and reducing microcrack formation. Additionally, magnetite nanoparticles can accelerate hydration processes and refine pore structure, resulting in improved durability and longterm performance.

Conclusion

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Research on cement solutions with added polymers and metal nanoparticles shows that this field is one of the promising and relevant directions. Polymer macromolecules and nanoparticles play significant roles from the initial hydration stage of cement to its complete hardening. They do not hinder the hydration process, but can distribute regularly and irregularly between particles in the structure. In both cases, chemical bonding or electrostatic forces occur between base particles and polymer/nanoparticles. This bond formation results in the formation of superior properties in concrete, improves quality, and enhances durability. Studies confirm that when polymer and metal nanoparticles are added to water rather than directly to cement powder, the pozzolanic effect in concrete becomes more pronounced. Achieving equal immobilization of particles on both the surface and within the concrete matrix becomes possible. At this point, nanoparticles and polymer chains interact with di- and tricalcium silicates and aluminates in cement due to their functional groups, leading to enhanced chemical interaction. This, in turn, results in clearer benefits in the final properties of the concrete. Considering that concrete is the primary structural material, the use of nanoparticles as a filler creates a nano-reinforcement effect, which is progressive in increasing the material's strength properties. Therefore, based on a brief review, the use of metal nanoparticles, especially magnetite and polymer materials, in the dispersed phase in cement products is more appropriate and purposeful.

Acknowledgment

The original version of this paper is available on https://www.scientific.net/EC.12.1.pdf

This work was supported by the Azerbaijan Science Foundation - Grant No AEF-MCG-2022-1(42)-12/05/2-M-05.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-12/978-3-0364-3024-9

Engineering Chemistry, ISSN: 2813-6535, Vol. 12, pp 25-36

doi: 10.4028/p-JxUQJ9

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

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2025-12-15

Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

The original version of this paper is available on https://www.scientific.net/EC.12.25.pdf

Ayodunmomi Esther Olowofoyeku , Daniel Gbenga Adekanmi

Pan African University Life and Earth Sciences Institute (Including Health and Agriculture), PAULESI, University of Ibadan, Ibadan, Nigeria

Facultad de Ciencias Químicas, Universidad Autónoma de Coahuila, Saltillo, Coahuila, 25280, México

a*ayoolowo1122@gmail.com, danieladekanmi@uadec.edu.mx

Corresponding author: ayoolowo1122@gmail.com

Keywords: delonix regia, flamboyant tree, activated carbon, adsorption, total petroleum hydrocarbon, remediation.

Abstract

Water pollution causes about 1.4 million deaths annually, and in Nigeria, especially in rural areas and the Niger Delta, millions lack access to clean water due to crude oil contamination. This study investigates the use of carbonized Flamboyant (Delonix regia) pods as a sustainable, low-cost adsorbent for removing petroleum hydrocarbons from contaminated water, promoting agricultural waste valorization and pollution reduction. Water samples collected from Obiakpor in Port Harcourt, Nigeria, contained of total petroleum hydrocarbons (TPH) and were subsequently used to evaluate the efficiency of the prepared adsorbent. Activated carbon was prepared by washing, drying, carbonizing the pods at , chemically activating with KOH , neutralizing, then drying and sieving for uniformity. Carbonization yielded , with proximate analysis indicating low moisture ( ), moderate ash ( ), and high volatile matter ( ), which favors thermal stability and pore formation. Scanning Electron Microscopy (SEM) and Brunauer-Emmett-Teller (BET) analysis revealed a highly porous structure with an average pore diameter of and a large surface area of . X-ray Diffraction (XRD) confirmed a semi-crystalline structure dominated by graphite ( ) and silicate minerals, enhancing mechanical strength and interactions. Thermogravimetric Analysis (TGA) showed that thermal stability was maintained between . Adsorption tests showed TPH removal increased with adsorbent dosage up to 0.2 g , reaching equilibrium afterward. The Freundlich isotherm best described the adsorption ( 0.9104 ), indicating multilayer adsorption on a heterogeneous surface, supported by high constants ( ). Kinetic studies indicated rapid adsorption within 25 min , fitting the pseudo-second-order model . These findings confirm that carbonized Flamboyant tree pods (FTP) are effective, renewable, and thermally stable adsorbents for petroleum-contaminated water treatment.

Introduction

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Water is essential for human survival, but less than of the Earth's total water is available for potable use [1]. Water pollution remains a global crisis, contributing to approximately 1.4 million deaths annually [2,3]. In Nigeria, where the population exceeds 250 million, nearly 71 million lack access to clean water, and this is further complicated by the inadequate access to basic sanitation facilities by over 130 million [4]. The water problem is usually more critical in rural areas, exposing millions to significant health risks [5]. The inhabitants of the Niger Delta region of Nigeria face acute water pollution challenges due to oil spills, industrial discharge, and poor waste management, which threaten health and livelihood [6]. Since the discovery of crude oil in the 1950s, weak environmental regulations have exacerbated ecological degradation, especially in this region [7]. Ensuring access to clean water is a fundamental human right, and this makes water quality control a necessary global priority [8]. Conventional remediation techniques such as chemical precipitation, reverse osmosis, and ion exchange are widely employed but present challenges, including high operational costs and
significant sludge generation. Hence, the search for cost-effective and environmentally sustainable alternatives is imperative [9].
Agricultural waste, such as husks, cobs, and pods of plants, is a viable source of biomass that can be converted into low-cost, sustainable remediation tools, reducing cleanup costs and aligning with circular economy principles through waste valorization [10]. Carbonized biomass sorbents are characterized by high oil sorption capacities of up to through micro/mesoporous structures and large surface areas ( ) [11]. Their properties are further optimized through methods such as KOH activation to enhance hydrophobicity and improve selective oil-water separation. Since they are derived from various biomass sources [12]. Their reusability (via solvent/thermal regeneration) and post-use applications as biochar for soil conditioning or carbon storage further minimize waste and long-term environmental impact [13]. Floating variants (e.g., carbonized sphagnum moss) enable easy recovery, while their biodegradability eliminates microplastic risks, ensuring ecological safety compared to synthetic alternatives. This synergy of performance, scalability, and sustainability positions carbonized biomass as a frontline solution for oil spill remediation [14, 15].
Flamboyant tree (Delonix regia), a member of the Fabaceae family, is often viewed as agricultural waste but has shown significant potential in various applications. Adeniyi et al. utilized Delonix regia stem waste to produce biochar through carbonization at , resulting in a material with a surface area of , mesoporosity, and functional groups ( ), suitable for soil amendment and water purification [16]. Also, Emenike et al. demonstrated the effectiveness of Delonix regia podderived biochar in removing phenol from wastewater, achieving an removal efficiency under optimal conditions ( ) through a non-spontaneous and irreversible process that fits the Freundlich isotherm and pseudo-second-order kinetic models [17]. In another study, Azeez et al. explored the adsorption of Rhodamine B dye onto activated carbon derived from Delonix regia seeds and pods, achieving high removal efficiencies of and , with the process best described by the Freundlich isotherm and pseudo-second-order kinetics [18]. These studies collectively highlight the versatility and potential of Flamboyant tree parts in environmental remediation and renewable energy applications.
Building on previous studies that have demonstrated the effectiveness of Flamboyant tree parts in removing various contaminants, Azeez et al. [18], Emenike et al. [17], Ibrahim et al. [19], and Latinwo et al. [20] his research investigates the biosorption capacity, characterization, and kinetic behavior of activated carbon derived from Flamboyant pods for the removal of total petroleum hydrocarbons (TPH) from crude oil-contaminated water in Obiakpor Local Government Area, Port Harcourt, Rivers State, Nigeria. In this study, a simple and low-cost adsorbent was prepared from Flamboyant pods, thoroughly characterized, and its adsorption properties and kinetics were investigated by varying dosage and contact time. The objective was to evaluate the adsorbent's effectiveness for the environmental remediation of petroleum-contaminated water.

Materials and Methodology

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Water Sampling and Collection of FTP

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Water samples were collected from the three most frequently used drinking water sources in each selected community within Obiakpor Local Government Area, following community consent and guidance. Samples were collected in pre-cleaned, clearly labeled glass bottles to prevent contamination and immediately stored at during transport to the laboratory. Analysis was conducted within 24 h to minimize degradation and maintain sample integrity. All sampling equipment and containers were handled using disposable gloves and standard quality assurance protocols, including the use of field blanks and proper documentation [21]. The average Total Petroleum Hydrocarbon (TPH) concentration in the water sources was determined using standard analytical procedures [22], yielding a baseline value of . This concentration was used for subsequent adsorption studies.

Preparation, Carbonization and Activation of the Adsorbent

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The preparation of activated carbon from Delonix regia pods followed a multi-step process similar to that described by Emenike et al. [17]. Initially, the pods were thoroughly washed with deionized water, soaked, and rinsed before being sun-dried for five days. They were then oven-dried at for 20 h until a constant weight was achieved. The dried material was crushed and sieved using a 250 mesh filter. Subsequently, the powdered material underwent carbonization in a muffle furnace, heated at a rate of to , and maintained for 2 h . Following carbonization, the material was activated using 0.1 M KOH at a 1:2 ratio (carbonized material : KOH ) at for 4 h with periodic stirring. The activated adsorbent was then washed with HCl and deionized water until 7. Finally, the material was dried in an electric oven, sieved for uniformity, and stored in an airtight container for further characterization.

Adsorbent Characterization

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The characterization of the activated FTP adsorbent was conducted using a comprehensive suite of analytical techniques to assess its properties. Proximate analysis, following ASTM D3172-13, was performed to determine the moisture content, ash content, volatile matter, and fixed carbon [23]. Additionally, iodine number analysis (ASTM D4607-14) was used to evaluate microporosity and adsorption capacity [24]. The bulk density of the adsorbent was measured using the tap density method to assess packing efficiency [25]. The surface morphology was determined using Scanning Electron Microscopy (SEM, JEOL JSM-IT300, JEOL Ltd., Japan). Meanwhile, surface area and pore size distribution were determined through Brunauer-Emmett-Teller (BET) analysis (Micromeritics ASAP 2020, Micromeritics Instrument Corp., USA). X-ray Diffraction (XRD) analysis, using an Empyrean X-ray Diffractometer (Malvern Panalytical, Netherlands), was conducted to identify the present phases. Thermogravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) were performed using a PerkinElmer STA 6000 thermal analyzer (PerkinElmer Inc., USA) to evaluate thermal stability, decomposition behavior, and weight loss under increasing temperatures [26, 27].

Adsorption Efficiency and Kinetics Studies

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Adsorption studies were conducted using the modified method of Latinwo et al. [20] after preliminary experiments to evaluate the efficiency of the adsorbent in removing Total Petroleum Hydrocarbons (TPH) from contaminated water. The experimental conditions, that is, adsorbent dosage and contact time, were varied to determine optimal adsorption parameters.

Effect of Adsorbent Dosage

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To study the effect of adsorbent dosage on total petroleum hydrocarbon (TPH) removal, batch adsorption experiments were conducted using carbonized FTP powder treated with potassium hydroxide . The pod powder was sieved to a particle size of less than before use. The adsorbent mass was varied from 0.05 to 0.25 g and added to 50 mL of TPH-contaminated water placed in 100 mL conical flasks. The initial TPH concentration was kept constant at across all samples. The flasks were agitated using a digital orbital shaker at a fixed speed of 130 rpm for a contact time of 21 min at room temperature ( ). After the set mixing period, the mixtures were filtered to remove the solid adsorbent. The clear filtrates were analyzed using UV-Vis spectrophotometry at 272 nm to determine the remaining TPH concentration. Removal efficiency (%) was calculated using:

Where is the initial TPH concentration ( ) and is the final TPH concentration ( ). All experiments were performed in triplicate, and average values with standard deviations were reported.

Adsorption Isotherm Studies

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To study the adsorption isotherms of Total Petroleum Hydrocarbons (TPH) on the carbonized Delonix regia pod (FTP) adsorbent, batch experiments were conducted by varying the initial TPH concentrations while keeping all other parameters constant. A fixed adsorbent dose of 0.1 g was added
to 50 mL of TPH-contaminated water with different initial concentrations (ranging from 25 to 125 . The flasks were agitated at 130 rpm and room temperature ( ) for 25 min , based on the equilibrium time determined from preliminary kinetics studies. After equilibration, the mixtures were filtered, and the remaining TPH concentrations were measured using UV-Vis spectrophotometry at 272 nm .
Two adsorption isotherm models were applied:
Freundlich Isotherm:

Langmuir Isotherm

where amount of TPH adsorbed per gram of adsorbent at equilibrium ( )
equilibrium concentration of TPH in solution (mg/L)
Freundlich constant (adsorption capacity)
adsorption intensity
maximum monolayer adsorption capacity ( )
Langmuir constant related to binding affinity (L/mg)

Adsorption Kinetics Studies

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Kinetics experiments were conducted using a fixed TPH concentration of and 0.1 g of the carbonized FTP adsorbent in 50 mL of solution. Samples were withdrawn at 5, 10, 15, 20, 25, 30, and 35 min , filtered, and analyzed for TPH concentration. Removal efficiency was calculated using Equation (1). Kinetic data were fitted to the following models:
Pseudo-First-Order Model:

Pseudo-Second-Order Model:

Intraparticle Diffusion Model:

where:
adsorption at time
equilibrium adsorption ( )
pseudo-first-order rate constant ( min )
pseudo-second-order rate constant ( )
intraparticle diffusion rate constant ( )
intercept related to boundary layer thickness
The slope and intercepts of the linearized plots were used to calculate the kinetic constants, and model fit was assessed by the values.

Statistical Analysis

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All experiments were performed in triplicate, and average values were reported. Standard deviations were calculated to assess variability. Control experiments without adsorbent were conducted to account for natural degradation effects.

Results and Discussion

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Physicochemical Characterization of FTPs

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The carbonized FTP adsorbent in this study achieved a yield of , surpassing the values reported for the plant's stem by Adeniyi et al. (26.57%) and Vargas et al. (27.8%), while nearing the higher yield of documented by Sugumaran et al. [28]. Tables 1 and 2 present the proximate and physicochemical properties of the material, highlighting its adsorption suitability. The low moisture content (1.86%) enhances thermal stability and minimizes water interference during adsorption, while the moderate ash content (4.94%) and high volatile matter (77.81%) indicate strong reactivity during carbonization, facilitating pore formation and structural development essential for adsorption [29, 30]. The fixed carbon content of aligns with values reported by Alonge et al. [31] (19.11%) and Sugumaran et al. [28] (5.20%), while other parameters are consistent with findings from similar studies. The bulk density of supports practical adsorption applications and matches the reported by Latinwo et al. [32], while the iodine value of reflects a high surface area, indicating strong adsorption capacity consistent with Sugumaran et al.'s results.

Table 1. Proximate Analysis of Carbonized FTP.

Parameter | Value (%)
Moisture Content | 1.86
Ash Content | 4.94
Volatile Matter | 77.81
Fixed Carbon | 15.39

Table 2. Physicochemical Properties of the Carbonized Pod.

Parameter | Value
Yield | 30.2%
Bulk Density | 0.63 g/mL
Iodine Number | 1468.65 mg I₂/g

Characterization of the Carbonized Pods

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Morphology, Surface Roughness and Porosity

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The SEM analysis of carbonized FTP adsorbent revealed irregularly shaped particles up to in size, with pores averaging in size and hive-like hierarchical cells indicative of mesopores and macropores, which enhance hydrocarbon capture and adsorption potential (Fig. 1). Azeez et al. [18], Sugumaran et al. [28], and Ibrahim et al. [19] reported a similar porous structure with a more sheet-like appearance. The surface roughness measurements showed a root mean square (RMS) roughness of and a mean roughness of , confirming a rugged morphology that complements the porosity observed in BET analysis. Negative skewness ( ) and kurtosis (-0.9996) indicate a valley-rich surface, providing entrapment zones for contaminants, while the high surface area of and slope of further supported enhanced molecular interactions during adsorption. BET analysis measured a surface area of , with nitrogen adsorption at 77.350 K showing a strong correlation ( ) in the linear BET region, validating the reliability of the data. A BET C constant of 3.457 suggested moderate adsorbate-adsorbent interactions favoring physisorption, desirable for reversible adsorption processes. Degassing at 250 for 3 h ensured contaminant-free pores, enhancing accessibility for hydrophobic organic pollutants like TPH. Together, these results demonstrate that the carbonized FTP adsorbent possesses a mesoporous structure with high adsorption capacity, making it suitable for environmental remediation applications.

Fig. 1. SEM and surface roughness image of carbonized FTP adsorbent.

Fig. 1. SEM and surface roughness image of carbonized FTP adsorbent.

Table 3. Surface roughness of the carbonized FTP adsorbent.

Parameter | Value | Implication
RMS Roughness (Sq) | 70.74 μm | High surface variation
Mean Roughness (Sa) | 60.24 μm | Reflects surface irregularity
Skewness (Ssk) | −0.358 | Valley-dominated topography
Kurtosis (Sku) | −0.9996 | Flattened surface peaks
Max Peak Height (Sp) | 111.87 μm | Highest elevation from the average line
Max Pit Depth (Sv) | 143.13 μm | Deepest depression from the average line
Surface Area | 27,422.4 μm² | Large interaction area
Surface Slope (Sdq) | 1.17 × 10³ | Indicates steep topographic change

Table 4. BET Parameters of carbonized FTP adsorbent.

Parameter | Value | Unit
BET Surface Area | 226.399 | m²/g
Pore Diameter (mode) | 2.94 | nm
DA Micropore Volume | 0.205 | cm³/g
BET C Constant | 3.457 | —
Correlation Coefficient | 0.997 | —
Degassing Temperature | 250 | °C
Degassing Time | 3.0 | h
Adsorption Temperature | 77.35 | K
DA Best E | 0.701 | kJ/mol

XRD Analysis

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The XRD analysis of carbonized FTP, presented in Fig. 2, shows a semi-crystalline structure, primarily composed of graphite ( ), which enhances interactions and supports the efficient adsorption of hydrophobic TPH molecules. Silicon oxide ( ) and Dinite ( ) are the main silicate phases, contributing to the material's structural rigidity and thermal stability. The presence of Osumilite ( ) and Marialite ( ) suggests mineral retention or ash formation during carbonization, potentially adding polar sites for contaminant anchoring. Specifically, the XRD pattern had a broad peak near , which is associated with amorphous carbon ( ), and smaller peaks at around traceable to disordered carbon [33,34]. The presence of minerals like silicon oxide, along with carbon, is common in biomass-based materials and has been reported in previous studies [34, 35]. Their combination with amorphous carbon creates a mixed structure with tiny crystalline areas, which allows different interaction mechanisms during adsorption. This mineral-rich, semi-crystalline biochar offers good structural strength, porosity, and
surface variety, making it useful for environmental cleanup, especially in removing total petroleum hydrocarbons (TPH).

Fig. 2. XRD pattern of carbonized FTP adsorbent.

Fig. 2. XRD pattern of carbonized FTP adsorbent.

TGA-DTA Analysis

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The TGA-DTG result of the carbonized FTP sample (Fig. 3) was similar to that observed by Adeniyi et al. The result revealed a significant weight loss of about between and , primarily due to the decomposition of volatile matter and organic components. The peak weight loss rate occurs at approximately , marking the main thermal degradation zone, which reflects the high content of pyrolyzable organic compounds. This decomposition pattern aligns with the thermal behavior of biomass components: hemicellulose decomposes between , cellulose between , and lignin over a broader range up to due to its complex aromatic structure [36]. Beyond , minimal weight change indicates the presence of stable carbonaceous residues and inorganic minerals, consistent with the graphite and silicate phases detected by XRD. The initial weight loss below is negligible, confirming the low moisture content, and the biochar exhibits higher thermal stability than raw biomass, with a peak degradation temperature of .

Fig. 3. TGA-DTA curves of carbonized FTP adsorbent.

Fig. 3. TGA-DTA curves of carbonized FTP adsorbent.

Adsorption and Kinetic Properties

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Effect of Adsorbent Dosage on TPH Removal and Adsorption Isotherms of TPH on Carbonized Pod

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As stated earlier, the initial TPH concentration in the contaminated water samples used for adsorption studies was , as determined in earlier studies [37]. The results in Table 5 show that increasing the adsorbent dosage improves the removal efficiency of total petroleum hydrocarbons
(TPH) by providing more active sites for adsorption [26,27]. However, beyond 0.2 g , the efficiency gains become minimal, indicating that the system is nearing saturation or equilibrium, as most TPH molecules have already been adsorbed and additional adsorbent contributes little to further removal. At this stage, adding more adsorbent does not significantly enhance removal because there are not enough TPH molecules left to occupy the extra sites. This trend aligns with findings from previous studies, confirming a limit to the benefits of increasing adsorbent dosage [26].

Table 5. TPH removal efficiency at varying adsorbent dosages.

Dosage
(g)
Initial TPH
(mg/L)
Final TPH
(mg/L)
Removal Efficiency
(%)

0.05
75.22 ± 0.15
32.85 ± 1.2
56.33 ± 1.6

0.10
75.22 ± 0.15
21.40 ± 1.0
71.55 ± 1.3

0.15
75.22 ± 0.15
11.65 ± 0.8
84.52 ± 1.1

0.20
75.22 ± 0.15
4.51 ± 0.5
94.01 ± 0.7

0.25
75.22 ± 0.15
3.85 ± 0.4
94.88 ± 0.5

The adsorption of Total Petroleum Hydrocarbons (TPH) using carbonized FTP was best described by the Freundlich isotherm model as presented in Fig. 4. The Freundlich plot gave a straight line with a high value of 0.9104 , showing a strong fit according to equation (2). From the slope and intercept of the plot, the values of and n were calculated as 166.36 and 2.35, respectively. Since , the adsorption is considered favorable. The high value also indicates a high adsorption capacity. This model suggests that the adsorbent surface is uneven and supports multilayer adsorption (equation 3). The plot gave an value of 0.8385 , which was lower than that of the Freundlich model. The slope and intercept gave a maximum adsorption capacity of and a Langmuir constant of . This result implies some level of monolayer adsorption on the surface, but the lower value shows that the surface is not completely uniform. Overall, the Freundlich model fits the experimental data better, confirming that adsorption occurs on a heterogeneous surface with more than one type of binding site. TPH adsorption using carbonized FTPs follows the Freundlich model better than the Langmuir model, indicating an uneven surface that supports multilayer adsorption. High values of and n confirm a strong attraction between the adsorbent and TPH [38, 39].

Fig. 4. Adsorption isotherms of the carbonized FTPs; Freundlich plot (left) and Langmuir plot (Right).

Fig. 4. Adsorption isotherms of the carbonized FTPs; Freundlich plot (left) and Langmuir plot (Right).

Effect of Contact Time on TPH Removal and Adsorption Kinetics of the Carbonized Pods

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Contact time also affected removal efficiency, as reported by other studies (Table 6), suggesting a time-dependent diffusion of TPH molecules onto the adsorbent surface. The sharp rise in efficiency up to 25 min indicates rapid adsorption due to the high availability of active sites. Beyond this point, the rate of increase slowed, implying that adsorption sites were becoming saturated, and the system was approaching equilibrium.

Table 6. TPH Removal Efficiency at Varying Contact Times.

Contact Time
(min)
Initial TPH
(mg/L)
Final TPH
(mg/L)
Removal Efficiency
(%)

5
75.22 ± 0.15
67.21 ± 0.31
10.65 ± 1.5

10
75.22 ± 0.15
53.56 ± 0.21
28.85 ± 1.0

15
75.22 ± 0.15
39.48 ± 0.26
47.61 ± 1.2

20
75.22 ± 0.15
28.64 ± 0.11
61.89 ± 0.7

25
75.22 ± 0.15
23.12 ± 0.15
69.30 ± 0.9

30
75.22 ± 0.15
18.24 ± 0.11
75.74 ± 0.7

35
75.22 ± 0.15
15.62 ± 0.13
79.32 ± 0.9

TPH adsorption efficiency onto carbonized FTPs increased rapidly within the first 25 min , then slowed significantly to reach at 35 min. This pattern suggests that the system was approaching equilibrium, as also observed by Ji et al. [26] and Esmaeili and Saremnia [40], and that most active sites were occupied early in the process. To further understand this behavior, the kinetics of adsorption were analyzed using three models: pseudo-first-order, pseudo-second-order, and intraparticle diffusion (Fig. 5). The pseudo-first-order model showed a poor fit , indicating that physical adsorption was not the dominant mechanism. Conversely, the pseudo-second-order model yielded a high value of 0.9575 , along with a slope of 0.5740 and an intercept of -1.3413 , pointing to chemisorption involving electron sharing or exchange between TPH and the adsorbent. The intraparticle diffusion model, with an of 0.0000 , confirmed that pore diffusion was not the ratelimiting step. Thus, the pseudo-second-order model provides the most accurate representation of the adsorption mechanism under the studied conditions. The analysis suggests that the adsorption of TPH onto KOH-treated carbonized FTPs is best described by chemisorption, supported by the high fit of the pseudo-second-order model and the poor fit of the pseudo-first-order model. The negligible effect of intraparticle diffusion further supports this conclusion, highlighting that chemical interactions dominate over physical adsorption or pore diffusion. KOH activation introduces oxygen-containing functional groups such as carboxyl and hydroxyl groups, which enhance surface reactivity and promote strong chemical bonding with TPH molecules. This leads to the formation of covalent bonds, ion exchange, and interactions, which increase the adsorption capacity and specificity [41].

Fig. 5. Adsorption kinetics plot of the carbonized FTPs: Pseudo-first-order model (A), Pseudo-second-order model (B), and intraparticle diffusion model (C).

Fig. 5. Adsorption kinetics plot of the carbonized FTPs: Pseudo-first-order model (A), Pseudo-second-order model (B), and intraparticle diffusion model (C).

These findings align with similar studies on KOH -activated biochar, which also report chemisorption as the primary mechanism for TPH adsorption. Previous research on Flamboyant and other carbonbased adsorbents further supports the observation that pseudo-second-order kinetics are indicative of chemisorption [38, 39, 41]. For example, Ji et al. [26] used a corn stalk biochar (SBC) composite modified with nano zero-valent iron was used, achieving up to removal efficiency. The process followed the Freundlich isotherm and pseudo-second-order kinetics. Similarly, Nazal et al. [42] used seagrass biochar to remove of TPH, fitting both Langmuir and Freundlich isotherms, and demonstrating strong adsorption performance.

Conclusion

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The carbonized flamboyant tree pod (FTP) developed in this study shows strong potential as a sustainable, low-cost adsorbent for removing total petroleum hydrocarbons (TPH). The carbon yield of surpasses many similar biomasses. Favorable proximate properties such as low moisture ( ), moderate ash ( ), and high volatile matter ( ) support energy efficiency and effective pore development. The high iodine number ( ) indicates a well-developed surface area. SEM and surface roughness analyses showed a rugged, porous structure with an average pore diameter of and a BET surface area of , enhancing molecular trapping. Mesopores and macropores, along with the moderate BET C constant (3.457), support physisorption and reversible adsorption. XRD confirmed a semi-crystalline structure comprising graphite ( ) and silicate phases, which enables strong interactions and mechanical strength. Thermogravimetric analysis revealed high thermal resistance, with a major weight loss occurring at due to biomass decomposition, confirming the structural integrity under heat. TPH adsorption increased with dosage up to 0.2 g before equilibrium. Freundlich isotherm ( ; ) fit best, indicating multilayer adsorption on a heterogeneous surface, though Langmuir also applied . Kinetic data aligned with the pseudo-second-order model , confirming chemisorption. These findings demonstrate that carbonized FTP is an efficient, thermally stable, and renewable adsorbent with excellent structural features, making it suitable for the large-scale remediation of petroleum-contaminated water and soil.

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Engineering Chemistry, ISSN: 2813-6535, Vol. 12, pp 37-48

doi: 10.4028/p-p9otpD

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2025-07-24

Revised:
2025-10-19

Accepted:
2025-10-20

Online:
2025-12-15

Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

Oludare Johnson Odejobi , Taiwo Hassan Ibrahim and Olajide Olukayode Ajala

Applied Thermodynamics, Renewable Energy, and Process Design Laboratory, Department of Chemical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria

Bioresources Development Centre, National Biotechnology Development Agency, Ogbomoso, Nigeria

dareodejobi@oauife.edu.ng, Phone: +2348060790337, taiwib098@gmail.com, cajalaolajide84@gmail.com

Keywords: co-digestion, biodegradable wastes, quadratic model; optimization, mixture design.

Abstract

Biogas produced via anaerobic digestion where microorganisms break down organic matter in the absence of oxygen, is seen as a promising solution to global energy and environmental challenges. Co-digestion of two or more wastes enhances biogas yield. However, study on optimization of biogas yield using substrate combination is seldom reported. This study was conducted to determine optimum substrate combination to maximize biogas yield. Simple lattice mixture design (SLMD) of Design Expert 13 was employed for experimental design and model development. SLMD was used to systematically vary ratios of different biodegradable wastes. Cassava vinasse (CV), kitchen waste (KW), cow dung (CD) and poultry dropping (PD) were taken as independent variables, and biogas yield as response. Fifteen biodigesters were set-up for the laboratory experiment. Four of the biodigesters were single-waste setups, while the rest digesters were used for co-digestion. A Scheffé quadratic model was developed to predict biogas yield and numerical optimization technique was used for optimization. The model developed gave adequate prediction with coefficient of determination ( ) of 0.7504 and adequate precision of 7.72 . The optimum substrate combination of cassava vinasse (8.6%), kitchen waste (7.1%), cow dung (41.6%) and poultry droppings ( ) were obtained for co-digestion process. The findings from this study made invaluable contributions to the field of waste co-digestion to enhance biogas production, offering a sustainable approach to managing organic waste and producing renewable energy.

Graphical Abstract

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1. Introduction

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

Among the main issues facing the globe today are the rising energy consumption and environmental issues [1]. The growing global demand for sustainable and renewable energy has increased interest in biogas production as a promising alternative to fossil fuels. The uncontrolled waste generation worldwide contributes significantly to greenhouse gas (GHG) emissions including carbon dioxide ( ) and methane. The conversion of these waste generated to energy can drastically reduce GHG emissions, compared to fossil fuels, by utilization of locally available resources [2]. One of the methods for handling mountainous wastes being generated through our daily activities is anaerobic digestion (AD).
Anaerobic digestion (AD) involves microbial processes that break down organic matter in the absence of oxygen to produce biogas, which has methane as the primary energy component, along with carbon dioxide ( ) and trace gases [3]. The percentage composition of biogas includes methane, about carbon dioxide and other gases in a small proportion [4], [5] and [6]. Biogas produced through the anaerobic digestion of biodegradable waste offers the dual advantage of waste management and energy generation [7]. Various biodegradable wastes, such as food waste, agricultural residues, and animal manure, are commonly used for biogas production [8]. Using any of these wastes as a single substrate for mono-digestion may not always provide an optimal environment for biogas production due to factors such as nutrient imbalances or high concentrations of inhibitory compounds [1]. However, co-digestion has been proposed to overcome these challenges by combining different waste types to achieve a more balanced nutrient profile and enhance microbial activity to improve biogas production [9], [10].
The success of anaerobic co-digestion of different wastes depends on nutrient contents of the combined wastes, balancing carbon-nitrogen ( ) ratio, increasing buffering capacity of the pH as well as right combination of other parameters in the co-substrate mixture. Mata-Alvarez et al. [11] reported that substrate combination enhances biogas production. However, selecting optimal substrate combination for maximum biogas yield remains a challenging task that has not fully explored in literature. This study aims to explore the optimization of biogas production from single and co-digestion of biodegradable wastes, focusing on improving biogas yield, operational efficiency, and environmental sustainability. By investigating various combinations of waste substrates and operational conditions, this research seeks to identify the most effective strategies for maximizing biogas production while minimizing environmental impact. This study designs and constructs biodigesters and biogas storage units, conducts physicochemical analysis of the four substrates used, and develops predictive models for the optimization of biogas yield through different substrate combinations.

2. Materials and Methods

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

2.1 Substrate Collection, Processing and Characterization

Four different types of substrates were employed for this study. These substrates include cassava vinasse (CV), kitchen waste (KW), cow dung (CD), and poultry droppings (PD). Cow dung and poultry droppings were collected from the Teaching and Research Farm, Obafemi Awolowo University, Ile Ife, Nigeria. Kitchen wastes were obtained from restaurants on and around campus, while cassava vinasse was collected from a cassava food processing facility in Ile Ife, Osun State, Nigeria. The chemicals and reagents used for this research were of analytical grade, and they were obtained from chemical vendor in Ile-Ife. After collection, the substrates, especially KW, were sorted to remove non-biodegradable materials such as stones, nylon and bones. Furthermore, mechanical pretreatment (grinding) was performed on the KW to achieve homogeneity. The pH of the substrates was tested, and only the CV was observed to need extra pretreatment because it is slightly acidic at a pH 4.5 . It was reported that vinasse from cassava based ethanol production are moderately acidic [12]. This is expected due to the fact that cassava vinasse consists of different organic compounds such as acetic acid, lactic acid, glycerol and various reducing sugars [13]. Therefore, the pH of CV was normalized to near neutral at a pH 6.93 by buffering with 0.1 M sodium hydroxide .

All the substrates were characterized for their total solids (TS %), volatile solid (VS %), moisture content (MC %), total nitrogen (TN) and total organic carbon (TOC) before and after digestion process using EN12280 and APHA 2540 B standard methods. TS analysis was achieved by drying samples to a constant weight at , while VS was obtained by calcination of solid samples at . (TS %), (VS %) and (MC %) were then calculated using Eqs. (1), (2) and (3), respectively. Furthermore, total carbon (TC) and total nitrogen (TN) of each substrate were determined, after which the ratio of each of the substrate were calculated. The determination of TC and TN was done at the Poultry Meat Research Laboratory, Department of Animal Sciences, Obafemi Awolowo University, Ile-Ife.

where is the weight of substrate before drying, is the weight of substrate after drying at and is the weight of dried substrate after calcination in the furnace at .

2.2 Preparation of Substrate Slurry

The slurry was prepared by mixing the substrate with water. The mixing ratios were determined using the method of Tumusiime et al. [14]. The method was used to achieve a total solids (TS) concentration of which falls within optimum TS range for wet anaerobic digestion [15], [16]. This was accomplished by carefully adjusting the water content of the substrates as shown in Eq. (4).

where is mass of water to be added per gram of feedstock is the moisture content of the substrate; is the desire moisture content; is the mass of substrate. The water-substrate mixing ratios for the substrates are presented in Table 1.

2.3 Design of Experiment

Mixture design in Design Expert software 13.0 was used to design experimental runs to achieve optimum substrate combination. Table 2 presents input variables which include CV (A), KW (B), CD (C) and PD (D) and the only output variable is biogas yield. Design Expert software generated randomly twenty (20) combinations including replicates of CV, KW, CD and PD as shown in Table 3.

Table 1. Mixing Ratio for Substrates.

Substrate
Mass [kg]
TS [%]
MC [%]
Water to substrate ratio

CV
4
1.20
98.80
Pure substrate

KW
4
16.00
84.00
1:2

PD
4
31.00
69.00
2:1

CD
4
16.00
84.00
1:2

KW+CD
4
37.10
62.90
3:1

CV+PD
4
21.40
78.60
1:1

KW+CV
4
58.90
40.10
4:1

CV+CD
4
38.05
61.95
3:1

PD+CD
4
42.60
57.40
1:1

KW+PD
4
44.55
55.45
3:1

CV+KW+PD+CD
(3.75:0.75:0.75:0.75)
6
24.63
75.37
3:1

CV+KW+PD+CD
(1.5:1.5:1.5:1.5)
6
37.50
62.50
3:1

CV+KW+PD+CD
(0.75:3.75:0.75:0.75)
6
32.26
67.74
2:1

CV+KW+PD+CD
(0.75:0.75:0.75:3.75)
6
31.83
68.17
2:1

CV+KW+PD+CD
(0.75:0.75:3.75:0.75)
6
35.70
64.30
2:1

Table 2. Input variables.

Notation | Component | Unit | Level
|  |  | -1 | 0 | +1
A | CV | [%] | 0 | 50 | 100
B | KW | [%] | 0 | 50 | 100
C | CD | [%] | 0 | 50 | 100
D | PD | [%] | 0 | 50 | 100

Table 3. Mixture design for substrate combination.

Run | A: CV | B: KW | C: CD | D: PD
1 | 1.000 | 0.000 | 0.000 | 0.000
2 | 0.500 | 0.000 | 0.000 | 0.500
3 | 0.000 | 1.000 | 0.000 | 0.000
4 | 0.000 | 0.500 | 0.500 | 0.000
5 | 0.250 | 0.250 | 0.250 | 0.250
6 | 0.000 | 0.000 | 0.000 | 1.000
7 | 0.000 | 0.000 | 1.000 | 0.000
8 | 0.125 | 0.625 | 0.125 | 0.125
9 | 0.000 | 1.000 | 0.000 | 0.000
10 | 0.625 | 0.125 | 0.125 | 0.125
11 | 0.000 | 0.000 | 0.000 | 1.000
12 | 0.500 | 0.500 | 0.000 | 0.000
13 | 0.500 | 0.500 | 0.000 | 0.000
14 | 0.500 | 0.000 | 0.500 | 0.000
15 | 0.125 | 0.125 | 0.625 | 0.125
16 | 0.000 | 0.000 | 0.500 | 0.500
17 | 0.125 | 0.125 | 0.125 | 0.625
18 | 1.000 | 0.000 | 0.000 | 0.000
19 | 0.000 | 0.000 | 1.000 | 0.000
20 | 0.000 | 0.500 | 0.000 | 0.500

2.4 Experimental Set-Up and Procedure

The anaerobic digestion process was conducted in dark-coloured plastic batch reactors fabricated within the Department of Chemical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria. The dark-coloured batch biodigester contained a gas outlet connected to gas storage tube, with a gas exit for measuring gas volume and flammability. Additionally, each biodigester included a digestate outlet. Fig. 1 illustrates schematic diagram for anaerobic digestion experimental setup. The monodigestion and co-digestion processes were set-up under mesophilic temperature and Hydraulic Retention Time (HRT) of 30 days. Each of the set-ups consisted of a 25 -liter biodigester, a gas storage tube, and a detachable water displacement mechanism for measuring biogas volume.

Fig. 1. Schematic diagram for anaerobic digestion process set up for the biogas generation.

Fig. 1. Schematic diagram for anaerobic digestion process set up for the biogas generation.

2.5 Modelling and Optimization of Biogas Production Process

A quadratic Scheffé model was used to describe the interactive effects of different components and their influence on biogas production. The general form of the quadratic Scheffé model for four components (A, B, C, D) is given in Eq. (5).

are the linear coefficients for the respective components; are the interaction coefficients between pairs of components. and D stand for the proportion of each term, while and CD are interactions that affect the response variable Y , which is biogas yield in this case.
Biogas production was optimized using desirability algorithm in the Design Expert software 13.0. Both the input variable ( and ) and the output variable (biogas yield) were constrained to the range of experimental design. The desirability for each solution was examined for the optimum substrate combination.

3. Results and Discussion

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

The results of this study are discussed in details in this section.

3.1. Biogas Production from Mono-and Co-Digestion Processes

The biogas production during mono-digestion processes over the period of 30 day is shown in Fig. 2. Biogas production started immediately after loading in all substrates (KW, CD and PD) except in CV which started after day. Cassava vinasse is more acidic when compared with other substrates. This observation shows that KW, CD and PD degrade faster than CV. The delay in the biogas production by CV could be due to the impeding influence of acid on microbial activities as the substrate was being degraded. The process exhibited a lag phase during which the microbial communities adapt to the substrate. Also, except for CV, fluctuations were observed in all the mono-digestion cases, similar to the observation reported by Odejobi et al. [17]. For the case of mono-digestion of CV, biogas production was increasing until after day when the biogas production began to decline till day retention time when no appreciable gas production was observed except for the CD. The CV was sourced from cassava processing facility within Ile-Ife town, Osun State, Nigeria. The CV contained high percentage of water with cassava starch sediments. Hence, the steady biogas production from CV before the steady decline could be due to balanced moisture content. The fluctuation in biogas production from other substrates could be due to effects of temperature, pH imbalance and changes in moisture levels on microbial activities during substrate degradation. It could be observed from

Figure 2 that the biogas production for CD was still increasing after day 30 . Cow dung contains fibrous materials which require longer time for the communities of microorganisms to degrade, and in effect, longer time for biogas production to cease. It has been reported that co-digestion improved biogas production, but the results obtained from this study revealed that for co-digestion of substrates to increase biogas production, the composition of participating substrates plays a vital role [17]. During co-digestion of the substrates in this study, biogas production in all cases started within 24 hours. The highest biogas yield of 12,060 mL and the least biogas yield of 3,423 mL were produced from co-digestion of CD+PD and KW+CD, respectively. The positive synergetic effects between CD and PD which provide nutrient balance between the two substrates could be responsible for the observed trend [18]. Kitchen wastes (KW) may have an imbalance of carbon-rich and nitrogen-rich materials due to the presence of oils, fats, or toxic compounds, that can inhibit microbial growth. The low biogas production observed within the specified hydraulic retention time (HRT) in co-digestion of KW+CD may be due to inbalance nutrients and high concentration of ammonia intorduced by KW or poor mixing of the two substrates. Generally, ffluctuations were observed in biogas production in all co-digestion processes as shown in Figure 3. This is in agreement with the study carried out by Odejobi et al. [17]. The reason for the fluctuations in biogas yield in all the co-digestion cases could be due to the same for the mono-digestion cases earlier reported in this study. The observed reduction in biogas yield, after the attainment of maximum biogas yield in each case until the completion of HRT of 30 days, could be due to depletion of degradable part of the participating substrates in the codigestion process.

Fig. 2. Biogas production for mono digestion over 30 days.

Fig. 2. Biogas production for mono digestion over 30 days.

Fig. 3. Biogas production for co-digestion over 30 days.

Fig. 3. Biogas production for co-digestion over 30 days.

3.2 Statistical Analysis of the Developed Model

The actual and predicted biogas yield according to the simple lattice mixture design in Design Expert software is presented in Table 4. The quadratic model developed for the prediction and optimization of biogas yield is given in Equation (6). The model comprises both the negative term, which represents antagonistic effect and positive term which indicates synergistic effect on quadratic model. Model adequacy and degree of fitness were determined using coefficient of determination ( ), predicted and adjusted Coefficient of variance (C.V), and adequate decision. As presented in Table 5 , the value for the developed model is 0.7504 . This value shows that of the variance in biogas yield is explained by the model, which is considered acceptable for experimental data. This implies that the model has good fit and ability to predict the biogas yield accurately. Furthermore, C.V was used to test precision of developed model. The C.V value of 22.24 gives good data reliability and high degree of precision. Adequate precision measures the signal to noise ratio. A ratio more than 4 is desirable. Adequate precision 7.7191 for the developed model shows an adequate signal.
Analysis of variance (ANOVA) for quadratic model is presented Table 6. The model developed represents how the proportion of each biodegradable waste (A: CV, B: KW, C: CD and D: PD), and their interactions affect biogas yield. ANOVA showed that the model has an F-value of 3.34 and a pvalue of 0.0370 , indicating that the model is significant and can accurately predict biogas yield. Significant interactions were observed between cassava vinasse and kitchen wastes ( AB ), cassava vinasse and poultry droppings (AD), kitchen waste and cow dung (BC), and cow dung and poultry droppings (CD), with p -values less than 0.05 . These interactions highlight the importance of combining specific substrates to maximize biogas production. The interaction between cassava vinasse and cow dung (AC), and kitchen waste and poultry droppings (BD), and other terms that have p -values greater than 0.05 , indicating they are not significant in this model. Furthermore, the positive coefficients associated with cassava vinasse (A), kitchen waste (B), cow dung (C), poultry droppings (D), co-digestions of cassava vinasse and kitchen waste (AB), cassava vinasse and cow dung (AC), cassava vinasse and poultry droppings (AD) and cow dung and poultry droppings (CD) as given in Eq. (6) indicate that all contributed positively to biogas yield. The particularly high positive
coefficient for the interaction between cow dung and poultry droppings (CD) suggests a strong synergistic effect, likely resulting from complementary microbial communities or nutrient profiles. Conversely, the negative interactions between kitchen waste and cow dung (BC) and kitchen waste and poultry droppings hint at a potential antagonistic effect, where these components may impede each other's effectiveness, and consequently produce low biogas.

Table 4. Mixture design for biogas prediction.

Run | A: CV | B: KW | C: CD | D: PD | Actual biogas yield | Predicted biogas yield
1 | 1.000 | 0.000 | 0.000 | 0.000 | 4535 | 4524.70
2 | 0.500 | 0.000 | 0.000 | 0.500 | 9450 | 8408.54
3 | 0.000 | 1.000 | 0.000 | 0.000 | 7337 | 7585.70
4 | 0.000 | 0.500 | 0.500 | 0.000 | 3423 | 2530.46
5 | 0.250 | 0.250 | 0.250 | 0.250 | 8644 | 7622.40
6 | 0.000 | 0.000 | 0.000 | 1.000 | 4792 | 4841.11
7 | 0.000 | 0.000 | 1.000 | 0.000 | 7129 | 6993.57
8 | 0.125 | 0.625 | 0.125 | 0.125 | 6680 | 6624.42
9 | 0.000 | 1.000 | 0.000 | 0.000 | 7337 | 7585.70
10 | 0.625 | 0.125 | 0.125 | 0.125 | 5353 | 7369.42
11 | 0.000 | 0.000 | 0.000 | 1.000 | 4792 | 4841.11
12 | 0.500 | 0.500 | 0.000 | 0.000 | 9220 | 8898.86
13 | 0.500 | 0.500 | 0.000 | 0.000 | 9220 | 8898.86
14 | 0.500 | 0.000 | 0.500 | 0.000 | 7420 | 6009.46
15 | 0.125 | 0.125 | 0.625 | 0.125 | 3967 | 6984.47
16 | 0.000 | 0.000 | 0.500 | 0.500 | 12060 | 10768.28
17 | 0.125 | 0.125 | 0.125 | 0.625 | 6334 | 7875.15
18 | 1.000 | 0.000 | 0.000 | 0.000 | 4535 | 4524.70
19 | 0.000 | 0.000 | 1.000 | 0.000 | 7129 | 6993.57
20 | 0.000 | 0.500 | 0.000 | 0.500 | 6370 | 5846.54

Table 5. Fit statistics for biogas yield model.

Std. Dev. | Mean | C.V. % | R² | Adjusted R² | Adeq Precision
1509.24 | 6786.35 | 22.24 | 0.7504 | 0.5257 | 7.7191

Table 6. ANOVA for quadratic model for biogas prediction.

Source | Sum of Squares | Df | Mean Square | F-value | p-value |
Model | 6.846E+07 | 9 | 7.607E+06 | 3.34 | 0.0370 | significant
(P)Linear Mixture | 1.548E+06 | 3 | 5.159E+05 | 0.2265 | 0.8759 |
AB | 1.145E+07 | 1 | 1.145E+07 | 5.02 | 0.0489 |
AC | 57139.11 | 1 | 57139.11 | 0.0251 | 0.8773 |
AD | 1.266E+07 | 1 | 1.266E+07 | 5.56 | 0.0401 |
BC | 2.065E+07 | 1 | 2.065E+07 | 9.07 | 0.0131 |
BD | 1.227E+05 | 1 | 1.227E+05 | 0.0539 | 0.8211 |
CD | 2.139E+07 | 1 | 2.139E+07 | 9.39 | 0.0120 |
Residual | 2.278E+07 | 10 | 2.278E+06 |  |  |
Lack of Fit | 2.278E+07 | 5 | 4.556E+06 |  |  |
Pure Error | 0.0000 | 5 | 0.0000 |  |  |
Cor Total | 9.124E+07 | 19 |  |  |  |

df = Degree of Freedom

3.3 Interaction Effect of Substrate Combination

Fig. 4 shows the 3D plot which offer a more comprehensive view of how the three components interact simultaneously, allowing for a deeper understanding of the combined effects on biogas yield. This plot describes how varying the fraction of one component can affect the biogas yield. In this plot, A, B, C and D represent cassava vinasse (CV), kitchen waste (KW), cow dung (CD), and poultry droppings (PD), respectively. Biogas yield is the dependent variable, represented on the vertical axis, showing the amount of biogas produced as a result of the mixture combinations. The plot shows that binary combination A-C produced the highest biogas, but as it tends towards C, more biogas is being produced. In the binary combination A-B, while A decreases, B increases towards mid-point. The binary B-C was negative where the curve from vertex C decreasing towards mid-point indicating reduction in biogas. Furthermore, the plot shows that when component C increased, and components A and B reduced, the biogas yield is higher, approaching value of biogas. The lowest yield occurs when component B is present in significant amount while A , and C are minimized. This suggests that increasing the proportions of A or B significantly reduces biogas yield. The results as presented in 3D plot and Eq. (5) imply that AB and AC have positive effect on biogas, while BC has negative effect on biogas yield.

Component Coding: Actual

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3D Surface

Biogas Yield (mL)

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3423 □ 12060

Actual Component

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D = 0.426854

Fig. 4. 3D surface plot for combination of substrates.

Fig. 4. 3D surface plot for combination of substrates.

3.4. Optimization of Biogas Production Process

After careful investigation of the combination of biodegradable wastes that would give optimum biogas yield from the experimental run and analyses, the solutions presented in Table 7 were obtained using desirability algorithm in Design Expert software. All solutions provided by the software were feasible due to their desirability values of 1 , but Solution 1 was recommended by the software as the optimum substrate combination. Additionally, as shown in Fig. 5, the optimum substrate combination that gave maximum biogas yield of are of , and
PD. This result is in agreement with the observation reported by Jaro et al. [19] with optimum biogas yield of VS.

Table 7. Optimization solutions for biogas production process.

Solution | CV | KW | CD | PD | Biogas Yield | Desirability |
1 | 0.086 | 0.071 | 0.416 | 0.427 | 9390.450 | 1.000 | Selected
2 | 1.000 | 0.000 | 0.000 | 0.000 | 4524.697 | 1.000 |
3 | 0.500 | 0.000 | 0.000 | 0.500 | 8408.540 | 1.000 |
4 | 0.125 | 0.125 | 0.125 | 0.625 | 7875.149 | 1.000 |
5 | 0.000 | 0.500 | 0.000 | 0.500 | 5846.540 | 1.000 |
6 | 0.250 | 0.250 | 0.250 | 0.250 | 7622.401 | 1.000 |
7 | 0.000 | 1.000 | 0.000 | 0.000 | 7585.697 | 1.000 |
8 | 0.625 | 0.125 | 0.125 | 0.125 | 7369.423 | 1.000 |
9 | 0.000 | 0.000 | 0.000 | 1.000 | 4841.106 | 1.000 |
10 | 0.500 | 0.500 | 0.000 | 0.000 | 8898.861 | 1.000 |

Fig. 5. Ramp plot for optimization.

4. Conclusion

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

The study investigated optimization of biogas production from mono- and co-digestion of biodegradable wastes. Simple lattice mixture design in Design Expert software was used to design the experiment and develop the model, while numerical optimization technique was employed to obtain optimum substrate combination. The model was found to be significant with an F -value of 3.34 and a p-value of 0.0370 . Significant interactions were observed between cassava vinasse and kitchen waste, cassava vinasse and poultry droppings, kitchen wastes and cow dung, and cow dung and poultry droppings, with p -values less than 0.05 . These interactions highlight the importance of combining specific substrates to maximize biogas production. The value suggests that of the variance in biogas yield is explained by the model. This study showed that, optimum substrate combination gave maximum biogas yield of VS are and PD. This investigation could guide future experiments or industrial applications where adjusting the proportions of different biodegradable wastes can maximize production from biogas.

Acknowledgement

The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

The authors acknowledge the financial support received from TETFund Institution based Research (IBR) grant (Ref: TETF/DR&D/CE/UNIV/ILE-IFE/IBR/2023/VOL.1/06). The contributions of the following students who actively participated in this research as their final year's undergraduate project were also acknowledged: Victor Stephen Komolafe Bolaji Odeyemi, Misabudeen Oladele Omisore, Faith Toluwalopemi Afolabi, Solomon Bamidele Ojumu, Idris Adeyemi Salami, Kareemat Oluwatomilola Akiyode, Dasolami Hannah Abidoye, Victor Olanrevaju Ogunjobi, Oyindamola Anthony Adekoleoye, Olamide Oluwaseun Martins.

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The original version of this paper is available on https://www.scientific.net/EC.12.37.pdf

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Engineering Chemistry, ISSN: 2813-6535, Vol. 12, pp 49-71

doi: 10.4028/p-6kVCnm

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2024-10-20

Revised:
2025-05-08

Accepted:
2025-06-30

Online:
2025-12-15

Esterification of Coconut Fatty Acid Distillate (COFAD)
Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

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lan Dominic F. Tabañag , Jae Michelle N. Cabo , Carla Bren S. Legarde , Sam Anthonette L. Suico , Jayhiel S. Malila

Philippine Council for Industry, Energy, and Emerging Technology Research and Development, Department of Science and Technology (DOST-PCIEERD), Bicutan, Taguig City, 1631, Philippines

Engineering and Industrial Research Division, National Research Council of the Philippines, Department of Science and Technology (DOST-NRCP), Bicutan, Taguig City, 1631, Philippines

Department of Chemical Engineering, University of San Carlos, Talamban, Cebu City 6000, Philippines

aian.tabanag@pcieerd.dost.gov.ph, jaenunezcabo@gmail.com, samanthonettesuico@gmail.com, ejayhielmalila@gmail.com

Keywords: acid-catalyzed esterification, biodiesel, coconut oil fatty acid distillate, kinetics, thermodynamics.

Abstract

Refined Coconut oil (RCNO) is the most used feedstock for biodiesel production, which undergoes alkali-catalyzed transesterification to produce fatty acid alkyl esters due to its low freefatty acids (FFA) content. This study utilized coconut oil fatty acid distillate (COFAD) as an alternative feedstock to RCNO. As it contains high amounts of FFA, it is pretreated through acidcatalyzed esterification to derive fatty acid methyl esters. The kinetics of the hydrochloric acid catalyzed esterification was investigated with the conditions of 10:1 methanol-to-COFAD molar ratio, acid catalyst loading ( 0.4729 N with respect to reaction mixture), reaction temperatures at and , and 2 hours reaction time. It was found that temperature had a positive effect on the reaction. The highest FFA conversion was observed when the reaction temperature was set to , where it reached , and the activation energy of the reaction was . The highest conversion predicted by the kinetic model is approximately equal to . A good fit of the experimental and calculated data was observed with . Moreover, the spontaneity of the reaction, as well as the effect of water on the reaction, were identified through the determination of thermodynamic parameters. The esterification reaction was found to be spontaneous only at high temperatures.

Introduction

The original version of this paper is available on https://www.scientific.net/EC.12.49.pdf

Alternative fuels from renewable resources have long been in consideration to slowly replace conventional fuels due to the environmental advantages they bring, such as reduction of net greenhouse gas and alleviation of pollution. Biodiesel is a widely studied renewable alternative to petroleum-derived diesel. Biodiesel is a mono-alkyl ester of long-chain fatty acids derived from biomass such as vegetable oil. Biodiesel is environmentally friendly because it is biodegradable and non-toxic, technically feasible, and compatible with existing internal combustion engines with no required major post-treatment because of the similarities of its properties to the properties of Petrodiesel [1].

In the Philippines, the production and use of biodiesel are governed by the Biofuels Act of 2006 (RA 9367). It mandates the usage of biodiesel as a means to use and develop indigenous clean energy sources that are renewable and sustainable to lessen the dependence of the country on imported oil. Most of the biodiesel produced in the country is derived from refined coconut oil (CNO). As of 2020, 12 registered biodiesel producers in the country use refined CNO as their biodiesel feedstock and have an aggregate annual capacity of 607.9 million liters [2]. In 2015, an increase in biodiesel production was expected in order to meet the requirements for the increase of biodiesel blend from

B2 ( ) to B5 ( ); however, the supply of CNO cannot meet the demands as the use of CNO as a biodiesel feedstock may affect the supply for export, food, and other industries. In fact, the biodiesel requirement should have been increased to by 2020 according to the targets in the Biofuel Roadmap 2018-2040 [2]. To augment biodiesel production, alternative feedstocks that are locally available and less expensive are considered. In the selection of substitute feedstock, the specifications set by the Philippine National Standard (PNS) for biofuels, specifically for coconut methyl esters (B100), should also be considered. According to the requirements prepared by the Department of Energy through its Technical Committee on Petroleum Products and Additives (DOE/TCPPA), fatty acid methyl esters with C8 to C18 alkyl groups should make up the majority of the biodiesel, with a minimum methyl laurate content of by mass [3]. One of the possible alternative feedstocks that could meet the standards for biodiesel is the coconut fatty acid distillate (COFAD). COFAD is a by-product of the refining process of coconut oil. It is produced during the deodorization and steam distillation step, and it is directly collected and sold as a raw material to produce derivatives such as medium chain triglycerides (MCTs), soap, animal feeds, cosmetics, and intermediate chemicals, such as fatty amines, fatty alcohols, and fatty esters. COFAD is considered an attractive alternative feedstock because of its composition, local availability, price, and applicability. COFAD contains a minimum of of free fatty acids (FFA) and has a fatty acid composition of short-chain fatty acids, mainly lauric acid, which is the fatty acid used to derive methyl laurate [4].

Biodiesel production is conventionally done by alkali-catalyzed transesterification of alcohol and triglycerides derived from vegetable oil to produce fatty acid alkyl esters and glycerol. For this reaction, the allowable FFA content of the feedstock must be below with respect to oil to minimize the unwanted saponification of the base catalyst and the FFAs, which would increase the viscosity of the reaction mixture, difficulty in product separation and eventually the termination of the desired reaction which is transesterification [5-7]. If the feedstock contains high amounts of FFA, it must undergo a pre-treatment procedure to lower its FFA content. Acid-catalyzed esterification of FFA and alcohol, shown in Figure 1, can be employed as a pre-treatment step to reduce the FFA content of the feedstock. If the feedstock contains considerable amounts of triglycerides, transesterification may be necessary to produce additional amount of biodiesel. This process is typically called the two-step esterification-transesterification method for high FFA containing feedstocks. This method has been widely used because it only requires moderate operating conditions, yields high reaction rates, and is relatively flexible as it is suitable to process various types of biodiesel feedstock [7,8]. Moreover, in the Philippine context, this approach is suitable for processing cheaper biodiesel feedstock that contains high FFA because the available facilities ( biodiesel production facilities) that utilize the alkali-catalyzed transesterification method would not require modification but would only need additional processing steps prior to the transesterification process [4]. For most fatty acid distillates (FAD), which are composed of a minimum of and contain only a small fraction of triglycerides, esterification can be considered as a main reaction for the production of methyl esters, as what is utilized in this study for using COFAD as feedstock. Step 1: Protonation Step 2: Nucleophilic attack Step 3: Proton transfer

Fig. 1. Homogeneous acid-catalyzed esterification reaction mechanism.

The conversion and rate of reaction for the acid-catalyzed esterification process are affected by different factors such as methanol-to-FFA molar ratio, reaction temperature, and catalyst loading. To obtain a higher equilibrium conversion, the backward reaction must be minimized using excess alcohol since, according to LeChatelier's principle, it shifts the equilibrium of the reversible reaction to the formation of methyl ester [9]. The optimal alcohol-to-FFA molar ratio of high-purity FFAs is 10:1-20:1 [9,10], while for impure FFAs, it reaches up to ratio [11,12]. The reaction usually occurs faster with a lower final conversion when the alcohol to fatty acids ratio is low, entirely different from when a higher molar ratio was utilized. As abovesaid, the reverse reaction should be minimized to achieve a higher equilibrium conversion. By using a higher alcohol to molar ratio (increasing the concentration of one of the reactants), the equilibrium is disturbed and shifts to consuming the increased amount of reactant which results in the increased formation of the desired ester product. In the study of Chai et al. [11], the use of a higher alcohol-to-FFA ratio resulted in a huge decrease in acid value, which is used to quantify the extent of conversion of FFA compared to those with a lower ratio [11]. The final conversion using a high molar ratio is relatively higher, although its initial rate of reaction is slow. For this study, the methanol-to-COFAD ratio was based on the conclusion on the research of Chai et al. [11] that the optimal alcohol-to-FFA molar ratio of high-purity FFAs is 10:1-20:1, and that a similar study of esterification of COFAD by Malila [4] used a ratio of 10:1, and obtained a highest conversion of approximately 98%.

Regarding the effect of temperature, a higher conversion rate is expected for reactions with higher temperatures. In an esterification reaction using COFAD, where the temperature was varied from to , it was found that temperature positively enhanced the reaction rate [13]. The increase in the rate of reaction is caused by the higher mass transfer rate between the oil and methanol phases due to the gain in kinetic energy of the reactants. However, the degree of conversion decreased when the reaction temperature was set at due to the loss of methanol since its boiling point is approximately equal to that temperature. Low temperature is expected to result in lower conversion
in a typical biodiesel reaction process, while too high reaction temperatures will cause methanol loss due to evaporation [14]. Furthermore, the different conversion effects at different temperatures are possibly due to the different inhibition effects of water formed during the esterification reaction [15]. Due to evaporation at high temperatures, a smaller amount of water will be left in the liquid phase, resulting in lesser water inhibition effects in the reaction mixture. For reactions where the temperatures were set in the range of , the conversion reached at least up to [10]. Although temperatures as high as brings the advantage of lower inhibition effects of water, it can also cause evaporation of methanol which significantly lessens the equilibrium conversion, as backward reaction could occur. The highest possible temperature that could be used to avoid, or minimize, the loss of methanol would be at .

The rate of esterification reaction is also enhanced by homogenous catalysts, as they favor more fatty acid conversion or product yield because of the unrestricted movement in the reaction solution in the presence of the catalyst [16]. Several types of homogenous catalysts exhibit distinctive characteristics, which leads to different results. However, most studies only focused on using sulfuric acid as a catalyst, while there are only a few studies conducted for other types of homogenous acid catalysts. In the study of Su, sulfuric acid ( H 2 SO 4 ) and hydrochloric acid ( HCl ) were used as catalysts, resulted in conversions as high as and , respectively. In the same study, HCl was found to be recoverable, while the recoverability of H 2 SO 4 is only [9]. Catalyst recoverability is the fraction of the acid catalyst remaining in the methanol or aqueous layer after the reaction. The difference of the recoverability between acids is caused by the partitioning of a compound in a liquid-liquid equilibrium system. The low recoverability of H 2 SO 4 indicates that the acid was partially dissolved into the biodiesel layer, resulting in its lower concentration in the methanol phase. On the other hand, most of the HCl remained in the methanol layer, allowing a high percentage of recoverability [17]. High recoverability also means that the catalyst can be reused. Thus, aside from a promising high conversion and recoverability of using HCl , there are also less waste generation, ease of biodiesel purification, and significant cut-off in expenses.

In the kinetics of the esterification reaction, high values of activation energies for the reaction are indicators that reaction temperature strongly influences system kinetics, implying that this type of reaction is kinetically controlled [18-20]. More so, the esterification reaction does not proceed without the presence of a catalyst [21]. As catalyst concentration increased, the forward reaction's activation energy decreased [5,22,23]. In addition, the excess alcohol used in the reaction promotes forward reaction, making the backward reaction to the reactants side negligible [11,12]. The kinetic model was based on these obtained details, and was established using the assumptions [5,9,12,24,25]:

The esterification reaction is a reversible heterogeneous process, the rate of which is controlled by the chemical reaction.

The rate of the non-catalyzed reaction is negligible relative to the catalyzed reaction.

The effect of liquid-liquid splitting on the reaction are ignored under intense mixing

The methanol to FFA mole ratio used was high enough for the methanol concentration to remain constant throughout the process.

According to these assumptions, the reaction is assumed to be pseudo-homogenous, and follows first-order in the forward direction and second-order in the backward direction [9]. This model accurately illustrates the kinetics of the esterification reaction of FFA and methanol with the use of an acid catalyst. Following the reaction presented in Figure 1, the reaction rate is expressed as

where is the concentration of FFA in oil, is the concentration of FAME formed, [D] is the concentration of water formed, and are the forward and reverse reaction kinetic constants, respectively. As the concentration of the reactants and products involved in the reaction corresponds to the FFA conversion rate, the esterification reaction rate can be reformulated with respect to the FFA conversion rate as the dependent variable.

where is the initial concentration of FFA in oil, X is the FFA conversion, and are the forward and reverse reaction kinetic constants, respectively. is the equilibrium rate constant, and is the alcohol to FFA molar ratio. At equilibrium, the net rate is equal to zero, , thus, rearranging Equation 2 results to

where is the equilibrium FFA conversion. The equilibrium rate constant is determined experimentally, from the final conversion at equilibrium. Integrating Equation 2 and rearranging gives

Equation 4 can be expanded and rearranged to obtain an explicit expression that can be used in determining the FFA conversion of the reaction.

The influence of temperature on the reaction rate constants can be determined by fitting the equilibrium and forward rate constants to the Arrhenius equation. Preceding the establishment of the model, the activation energy of a reaction decreases as catalyst loading is increased. In a study by Chai et al. [11], activation energies and frequency factors were the lowest at the optimized chemical dosage for the alcohol-to-FFA ratio and catalyst usage [11]. At the same time, higher values for the forward reaction rate constants were obtained at greater catalyst loading and increased reaction temperatures [21]. Furthermore, published research has consistently observed that the equilibrium constant increases with higher reaction temperature; thus, the esterification of FFA with methanol is considered an endothermic reaction [22,26-28]. In thermodynamic analysis, the esterification reaction is examined from the point of view of energy and entropy. To determine the spontaneity of the reaction, and whether the reaction is endothermic or exothermic, the enthalpy and entropy of a reaction are studied. The enthalpy is used to calculate the energy of a substance that passes through the system boundary, while the entropy applied to the materials involved in processes determines the process direction and measures the irreversibility of the process [29].

The change in Gibbs free energy, , is temperature-dependent. It is related to the standard free energy change of the reaction, , which is the difference in the free energies of formation of the products and reactants in their standard states.

where Q is the reaction quotient, is the Gibbs free energy change, is the standard free energy change, R is the universal gas constant, and T is the reaction temperature [30]. At equilibrium, the change in Gibbs free energy is zero and the reaction quotient becomes equal to the equilibrium constant. Thus,

The Gibbs free energy is a state function and is a measure of the amount of usable energy in the system. Thus, the change in free energy is equal to the difference between the change in enthalpy and the product of temperature and entropy change, as shown in the Gibbs Helmholtz equation presented in Equation 8. The change in Gibb's free energy determines the spontaneity of the reaction, and direction of the chemical change, whether the reaction is endergonic or exergonic.

Considering the stagnant production of biodiesel due to the insufficiency of supply and the high cost of coconut oil, this research aimed to study COFAD as an alternative feedstock for biodiesel production. There is only limited data on the operational variables of the esterification of FFA derived from COFAD since it is a relatively new feedstock for biodiesel production. In addition, the effectiveness and performance of homogeneous acid catalysts other than sulfuric acid have not been investigated, along with its reaction kinetics. Consequently, this project intended to investigate the effect of temperature on the conversion and rate of reaction of COFAD esterification using hydrochloric acid as a homogenous catalyst. With an already established kinetic model, the experimental data were used to determine the kinetic parameters of the esterification reaction. In addition, thermodynamic analysis was carried out where the change in Gibbs free energy, change in entropy, and change in enthalpy of the esterification reaction was determined.

Materials and Methods

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Coconut fatty acid distillate was acquired from a local coconut refining plant in Mandaue City, Cebu, Philippines. The following reagents were used in this study: absolute ethyl alcohol, chemsupply, Australia; 95% v/v analytical grade n-hexane, Scharlau, Spain; 36% w/w hydrochloric acid, Scharlau, Spain; methanol, Scharlau, Spain; potassium hydrogen phthalate, Ajax Finechem, Australia; sodium chloride, Ajax Finechem, Australia; sodium hydroxide pellets, Scharlau, Spain; and phenolphthalein indicator, Scharlau, Spain. These reagents were all obtained through a local supplier. The experimental flow diagram is shown in Figure 2.

Fig. 2. Experimental Flow Diagram

Fig. 2. Experimental Flow Diagram

Collection, Storage, and characterization of COFAD. Coconut fatty acid distillate was stored at room temperature of around prior to pre-treatment and further characterization for around 7 days.

Collection, Storage, and characterization of COFAD: Pre-treatment of COFAD. The coconut fatty acid distillate was heated to in a heater for 10 minutes to melt the COFAD that may have solidified while in storage. Afterward, the preheated COFAD was filtered using ordinary filter paper
in a vacuum filtration set-up to remove the suspended solids in the sample that may contaminate the reaction mixture.

Collection, Storage, and characterization of COFAD: Gas chromatography analysis of COFAD. Gas chromatography analysis was outsourced to F.A.S.T. Laboratories to determine the fatty acid composition of COFAD. The methods employed were adapted from the Official Methods of Analysis of the Association of Official Analytical Chemists [31]. Gas chromatography was performed using a Restek 2560 column with a flame ionization detector (FID) at . The carrier gas that was used was nitrogen ( ) at a constant flow rate of . The operating conditions that were used for the chromatographic analysis of the COFAD were as follows: injector temperature of , detector temperature of , column temperature of , and an injection volume of . Using the fatty acid profile results, the average molecular weight of COFAD was calculated by dividing the total mass of the fatty acids by the total moles of the fatty acids, as presented in Equation 9.

Collection, Storage, and characterization of COFAD: Moisture analysis of COFAD. Moisture analysis was outsourced to F.A.S.T. Laboratories to determine COFAD's moisture content. The analysis was performed using the Karl Fischer method, where the amount of water present in the sample was determined by titration [32].

Collection, Storage, and characterization of COFAD: Density determination. A clean, dry 50 mL beaker was put on top of a calibrated densitometer. A thermometer was affixed to the rim of the beaker. Afterward, the disk with the glass plummet was hung from the frame, and the densitometer was tared. The beaker was filled with the reference liquid, distilled water, until the liquid reached approximately 10 mm above the glass plummet. The negative weight displayed on the balance, which corresponds to the buoyancy acting on the glass plummet in the liquid, was recorded. The temperature was also recorded. Afterward, the suspended glass plummet was removed, washed, and dried. Another clean 50 mL beaker was placed on top of the densitometer, and the same procedure was performed. This time, the sample liquid, which is the pre-treated COFAD, was filled onto the beaker. Since the glass plummet has a volume of 10 cm 3 , the density of the reference and sample liquids was obtained by shifting the decimal point of the recorded densities one place to the left.

Collection, Storage, and characterization of COFAD: Viscosity determination. The viscosity of COFAD was determined by capillary viscometry using an Ostwald viscometer. The Ostwald viscometer was clamped onto an iron stand vertically. After which, the viscometer was filled with 15 mL of the reference liquid, distilled water, using a volumetric pipette. The liquid was sucked into the opposite bulb using a pipette pump until it reached the marker above. The liquid sample was allowed to flow independently, and the flow time from the upper mark through the lower mark was recorded. Three readings of the flow time on the same liquid were recorded, and the average of the flow times was calculated and recorded. The room temperature for every trial was also measured. The viscometer was cleaned and dried. Afterward, the same procedure was followed; this time, the COFAD sample was the liquid to be added to the viscometer.

The relative viscosity and exact viscosity of COFAD were then calculated using Equations 10 and 11, respectively.

where is the relative viscosity of COFAD, is the flow time of the COFAD sample, is the flow time of the reference liquid, is the obtained density of COFAD, is the obtained density of water, is the exact viscosity of COFAD, and is the viscosity of water at a specified temperature as obtained from literature [33].

Esterification of COFAD. The esterification reaction was performed at a fixed methanol-toCOFAD molar ratio of 10:1 and a catalyst loading of 0.472 N and a varied reaction temperature of 45,55 , and . On eight screw-capped Erlenmeyer flasks, 15 g of COFAD was added to each flask. These flasks were incubated in an incubator shaker set at the desired temperature. On another set of eight flasks, 29 mL of methanol and 1.8 mL of hydrochloric acid were mixed and preheated in the same incubator shaker for 10 minutes. After achieving the desired temperature, which was measured through a thermometer attached to the side of the incubator shaker, each methanol-hydrochloric acid mixture was added to the flasks containing the COFAD sample simultaneously to start the esterification reaction. The incubator shaker was then kept constant at the desired temperature ( 45,55 , and ) at a speed of 250 rpm . As soon as the incubator-shaker began to operate, the timer was started. One flask was taken out of the incubator every , 60, 75, and 90 minutes and was cooled in an ice bath to stop the reaction. Three replicate experimental runs were performed for each reaction temperature. From this, the FFA conversion was considered the response variable. A statistical test at the three different reaction temperatures was conducted to compare the mean and standard deviation of the FFA conversion for each time point. Consequently, in terms of kinetic analysis, the activation energy and pre-exponential factor were considered the response variables while the change in Gibbs free energy, enthalpy, and entropy were the response variables for the thermodynamic analysis.

Separation of FAME and the aqueous phase. The fatty acid methyl ester (FAME) and the aqueous phase of the reaction mixture were separated by liquid-liquid extraction using n -hexane as the solvent. The procedures were based on the procedures described by Malila [4].

Separation of FAME and the aqueous phase: Preparation of Solution. On a top loading balance, 50 g of technical-grade sodium chloride was weighed and added to a beaker. To this, 950 g of water was added and stirred until the sodium chloride was dissolved entirely. The NaCl solution was transferred to a reagent bottle and stored for the following procedure.

Separation of FAME and the aqueous phase: Extraction of FAME phase using n-hexane. A 250 mL separatory funnel was clamped onto a ring stand, ensuring the stopcock was closed. After which, the post-esterification reaction mixture, which contains FAME, water, excess methanol, and unreacted FFA, was transferred into the separatory funnel. The flask was washed with 10 mL of n hexane to ensure that none of the reaction mixture remained in the flask. The washing was then added to the separatory funnel. The washing process was done twice. After which, 10 mL of n -hexane was added to the funnel, and the stopper was placed on the funnel. The separatory funnel was removed from the ring and iron stand, inverted slowly, and the stopcock was opened to release the pressure. After which, the stopcock was closed, the funnel was given a light shake, and the stopcock was opened again to let the pressure out. This step was done until no more gas escaped.

Afterwards, the separatory funnel was mounted back to the ring stand and was allowed to sit until the layers were visible and could be separated. The upper layer contained n -hexane, unreacted free fatty acids, and methyl esters, while the lower layer contained methanol, water, and hydrochloric acid. Twenty mL of was added into the separatory funnel to remove leached acid from the reaction mixture. The mixture was allowed to sit for 5 minutes. After that, the stopper was removed, and the bottom layer (aqueous phase) was drained into an Erlenmeyer flask. Washing was done thrice to the remaining mixture in the separatory funnel, which is composed mainly of the organic layer until the pH of the discarded layer was equal to or more than the pH of the NaCl solution ( 7). Then, the organic layer was drained into another Erlenmeyer flask.

Three aliquots, each weighing approximately 0.5 grams, were taken from the aqueous phase for acid value determination, as described in the previous sub-sections. Similarly, two aliquots weighing approximately 5.0 grams were taken from the washings for acid value determination. The acid values of the aqueous solution and washings were used in the calculation of the FFA conversion to account for the unreacted FFA present in the solution.

Separation of FAME and the aqueous phase: Evaporation of hexane from the FAME phase. On a dried and pre-weighed evaporating dish, approximately 10 grams of the organic layer was added and weighed in an analytical balance. Afterwards, the evaporating dish was placed on the fume hood
to allow the hexane to evaporate. The mass of the sample's evaporating dish was recorded at 30 minutes, 60 minutes, 90 minutes, and 120 minutes to monitor the amount of hexane that is leaving in the sample. The samples were left inside the fume hood until its mass remains constant, therefore indicating that all the hexane has evaporated. Afterwards, the samples in the evaporating dish were transferred to a test tube for storage. Then, three aliquots weighing approximately 0.5 grams were taken from the FAME phase and subjected to acid value determination as described.

Acid value determination. Acid value determination was carried out via titration method based on the procedures described in the American Oil Chemists Society (AOCS) official method Cd 3d63 [34].

Acid value determination: Preparation of standard potassium hydrogen phthalate (KHP) solution. Potassium hydrogen phthalate (KHP) was dried in an oven at for 20 minutes to remove the traces of moisture before making the solution. After which, approximately 0.2 g of dried KHP was weighed using an analytical balance and transferred into a Erlenmeyer flask. The masses measured were ensured to be within or . Approximately 100 mL of distilled water was poured into the flask, ensuring no traces of KHP were left on the sides. The KHP solution was swirled carefully until all the KHP had been dissolved.

Acid value determination: Preparation of ethanolic sodium hydroxide solution. In a weigh boat, exactly 4 g of sodium hydroxide pellets were weighed using an analytical balance and transferred into a 1-L volumetric flask. After which, absolute ethanol was added to the flask until it reached the one-liter mark. The flask was shaken until all the pellets dissolved in the mixture.

Acid value determination: Standardization of ethanolic NaOH using KHP. Approximately two to three drops of phenolphthalein indicator were added to the prepared standard KHP solution. After which, the KHP solution was titrated by adding drops of ethanol NaOH from the base burette until the endpoint was achieved or when the solution changed from colorless to light pink. The volume of ethanol NaOH consumed was recorded to the nearest . Three trials were performed for the standardization of sodium hydroxide. The concentration of NaOH in the KHP solution was calculated using Equation 12. and the average of three trials was calculated to obtain the final concentration of sodium hydroxide.

where is the concentration (M) of NaOH, is the concentration of the KHP standard solution, is the volume of the KHP aliquot being titrated, and is the volume of the ethanolic NaOH consumed during titration.

Acid value determination: Blank titration. Approximately 10 mL of the solvent, absolute ethanol, was added to an Erlenmeyer flask, to which drops of the phenolphthalein indicator were added. The solvent was titrated by adding drops of ethanolic NaOH from the base burette until the endpoint was achieved. The volume of ethanol NaOH consumed was recorded to the nearest mL .

Acid value determination: Titration of COFAD samples. Approximately 0.5 g of the sample was accurately weighed and placed in a clean, dry flask. After which, 20 mL of absolute ethanol was added to dilute the sample. Two to three drops of phenolphthalein indicator were added, and the mixture was titrated until a permanent pink color persisted for at least 30 seconds. After this, the acid value in terms of of the test sample was calculated. Then, the acid value was divided by 2.81, 2.19, or 1.99 to express the acid value in terms of free fatty acid as percent lauric, palmitic, or oleic, respectively.

where A is the volume ( mL ) of the standard NaOH consumed during titration of the sample, B is the volume of the standard NaOH consumed during titration of the blank, M is the molarity of NaOH , and W is the mass of the sample.

After obtaining the reaction mixture's initial and final acid values, the FFA conversion was calculated using Equation 14.

where is the FFA conversion, is the acid value of the methanol-acid catalyst mixture before esterification, is the acid value of COFAD, is the acid value of the aqueous phase, and is the acid value of the FAME phase.

Kinetic and Thermodynamic Analysis. The kinetic and thermodynamic modeling equations were based on the pseudo-homogeneous model from the study of Su [9].

Kinetic and Thermodynamic Analysis: Kinetic Modeling. The equilibrium reaction rate constant was calculated using Equation 15.

where is the equilibrium conversion or the maximum conversion, is the molar ratio of water to COFAD, and is the molar ratio of methanol to COFAD. After which, the values for and were calculated using Equations 16 and 17.

The forward reaction rate constant, , was then calculated using Equation 18.

where is the initial COFAD concentration ( ), and t is the reaction time. The effect of temperature on the kinetic parameters is determined by fitting the data to the linearized form of the Arrhenius equation, as shown in Equation 19. A plot of the natural logarithm of the forward reaction rate constant against the reciprocal of the reaction temperature was constructed. After which, the bestfit line was created, and the activation energy and pre-exponential factor were calculated using the slope and y-intercept, respectively.

Kinetic and Thermodynamic Analysis: Thermodynamic Analysis. The experimental data were further processed to determine the thermodynamic parameters of the esterification reaction. The standard free energy change, , was calculated using Equations 6 and 7 . After which, the Gibbs free energy change was plotted as a function of temperature . The change in enthalpy and change in entropy ( ) were determined using the Gibbs Energy Equation, as shown in Equation 8.

Results and Discussions

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COFAD Characterization. The characterization of the COFAD was done to determine its fatty acid composition, physicochemical properties, and moisture content. The fatty acid composition will be used to calculate the average molecular weight of the feedstock, Table 1 presents the fatty acid profile of the feedstock after the derivatization of COFAD. The composition was determined through gas chromatography by F.A.S.T. Laboratories. From the results of the test, it can be seen that the majority of fatty acids present in the COFAD is lauric acid, with , followed by myristic acid, with , and palmitic acid, with . This observation is the same with the fatty acid profile in the study of Malila [4], which was expected, as the feedstock was obtained from the same manufacturer. However, there is still a significant difference that can be observed in their composition, especially for the lauric acid, where it comprises about of the feedstock used in Malila [4]. One probable reason for this disparity is the difference of the derivatization process for the gas chromatography. According to Malila [4], the obtained fatty acid profile may not only consist of the fatty acid molecules, but includes the carboxyl groups of the glycerides, as a result of both esterification and transesterification reactions taking place because of the boron trifluoride. The higher percentage of the indefinable content of COFAD in this study might also be a result of the derivatization process, or a contamination during the sourcing and storage of the feedstock. Nevertheless, the fatty acid profile of the three studies presented in the table below have a similar trend, which confirms that the feedstock is mostly composed of short-chain fatty acids.

Table 1. Fatty acid profile of the COFAD feedstock

Components | Weight Percent (%)
| This Study | Malila [4] | Rajesh et al. [13]
Caproic Acid (C6:0) | 0.235 | - | 0.724
Caprylic Acid (C8:0) | 3.940 | 3.93 ± 0.97 | 10.206
Capric Acid (C10:0) | 3.850 | 4.43 ± 0.85 | 6.749
Undecanoic Acid (C11:0) | 0.475 | - | -
Lauric Acid (C12:0) | 38.200 | 48.18 ± 5.22 | 45.533
Myristic Acid (C14:0) | 16.600 | 20.01 ± 1.31 | 16.922
Palmitic Acid (C16:0) | 10.800 | 11.13 ± 2.29 | 8.841
Stearic Acid (C18:0) | 2.600 | 2.69 ± 0.87 | 2.551
Oleic Acid (C18:1n9c) | 8.100 | 7.78 ± 2.41 | 6.776
Linoleic Acid (C18:2n6c) | 2.100 | - | 1.634
Linolenic Acid (C18:3) | - | - | 0.064
Arachidic Acid (C20:0) | - | 0.03 ± 0.02 | -
Eicosenoic Acid (C20:1) | - | 0.03 ± 0.03 | -
Others | 13.100 | 1.78 ± 0.50 | -

The physicochemical properties and moisture content of the COFAD are listed in Table 2. The average molecular weight of the feedstock was calculated using the obtained fatty acid composition, which has almost the same value with the average molecular weight of the feedstock used in the study of Malila [4] and Rajesh et al. [13]. The average acid value of the feedstock was high, with a value of sample, with of free fatty acid content as lauric acid, while the remaining may be composed of glycerides and other unidentifiable matter. The obtained FFA content confirms that the feedstock requires esterification reaction with an acid catalyst to produce methyl esters from FFA. This also meets the standards of the PNS for biodiesel, where the minimum methyl laurate of the product should be . In addition, the density and viscosity were and 8.5988 mPa .s, respectively. There is a significant difference between the calculated viscosity of this experiment and the study of Malila [4]. Aside from the influence of temperature on viscosity, this deviation might also be caused by the difference of their composition, along with their moisture content. Moreover, sample contamination during sourcing and storage cannot be discounted as a potential contributor to this. The calculations for the properties are presented in detail in the appendix section. Lastly, the moisture content of the COFAD was determined through Karl Fischer (KF) titration by F.A.S.T. Laboratories and has a value of only. The amount of moisture present
in the feedstock is necessary to be reported since water has an inhibition effect on the esterification reaction, which will be discussed further in the proceeding sections.

Table 2. Physicochemical properties and moisture content of COFAD feedstock

Properties (Unit) | This Study | Malila [4] | Rajesh et al. [13]
Average Molecular Weight (g/mol) | 214.54 | 212.77 | 210.86
Acid Value (mg KOH/g sample) | 188.17 ± 3.44 | 185.96 ± 1.29 | 49.00
Free Fatty Acid (% Lauric Acid) | 67.18 | 66.39 ± 0.46 | 24.50
Density (g/mL) | 0.8925 ± 0.0001 at 32°C | 0.9068 ± 0.0002 at 27.93°C | 0.892 at 15°C
Viscosity (mPa·s) | 8.5988 ± 0.1243 at 29°C | 23.22 ± 1.05 at 26.56°C | 10.34 at 40°C
Moisture (%) | 0.2746 | — | —

Effect of temperature on the esterification reaction. The acid catalyzed esterification reaction, shown in Figure 3, occurred at three different temperatures, and , with methanol-toCOFAD ratio of 10:1, and catalyst loading of 0.472 N with respect to reaction mixture. The mixtures were shaken at 250 rpm for a reaction time of 2 hours.

Fig. 3. Acid-catalyzed esterification of free fatty acids to produce fatty acid methyl ester and water

Fig. 3. Acid-catalyzed esterification of free fatty acids to produce fatty acid methyl ester and water

The esterification reaction of COFAD and methanol to produce methyl esters, shown in Figure 3, are expected to be affected by multiple factors. For temperature, as what is focused on this study, three varying reaction temperatures were utilized as aforementioned. Figure 4 presents the average experimental and predicted FFA conversion of COFAD to methyl esters of the three trials conducted for each reaction temperature, along with the experimental and predicted data from Malila [4] for the esterification using sulfuric acid as catalyst.

From the plot, the conversion of FFA at the end of the reaction is slightly higher at higher temperatures with a difference of approximately 1 to . In addition, the conversion at the start of the reaction for temperatures and are higher compared to the reaction at . At the first five minutes, the conversion of 0.70 for significantly increased to 0.79 and 0.80 for and , respectively. For this conversion, the percent FFA as lauric acid in the product is only 0.94 to , meeting the standards where the FFA content should be lowered to or less. In the study of Malila [4], which used a sulfuric acid as catalyst, the conversion at the start and end of the reaction at is approximately two times higher than the reaction at , while the conversion at the start and end of the reaction at is and times greater than that of the conversion at , respectively. With this observation, it can be reported that the trend observed in the study of Malila [4], where the conversion escalates when the temperature is increased, is almost identical to the trend discovered in this study. These observations mean that the reaction temperature has a positive effect on esterification, which enhances the reaction rate. A temperature increase raises the kinetic energy of the reactants, increasing the mass transfer rate. Moreover, the use of hydrochloric acid as catalyst in this study resulted in a faster reaction rate but with lower equilibrium conversion compared to the esterification reaction using sulfuric acid. This is an effect of the difference in dissociation constant and water content of the two acid catalysts, which will be examined thoroughly in the next section, along with their catalytic activities.

Fig. 4. Average FFA conversion as a function of reaction time and temperature at a methanol-to-COFAD molar ratio (a) HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper and (b) as catalyst at a loading of 0.00284 N by Malila [4].

Fig. 4. Average FFA conversion as a function of reaction time and temperature at a methanol-to-COFAD molar ratio (a) HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper and (b) as catalyst at a loading of 0.00284 N by Malila [4].

A similar trend of results can be observed in the works of Chai et al. [11] and Rajesh et al. [13], both using sulfuric acid as a catalyst. In the study of Chai et al. [11], for an esterification reaction utilizing used cooking oil as feedstock, the methanol-to-FFA molar ratio is with catalyst loading of 0.0283 N and the reaction time is 2 hours. Its conversion reached and for a reaction temperature varying from to at increments of 10 . On the other hand, Rajesh et al. [13] used COFAD as feedstock, with reaction conditions of 8:1 for methanol-to-oil ratio, 0.0338 N catalyst loading and reaction time of 90 minutes. The biodiesel yield increased from around at , to at , to approximately at . However, at , the yield decreased to due to the loss of methanol as it is near its boiling point.

The results of this part of the study corroborate the findings of the existing research and expected trend as the reaction temperature is increased. An optimum temperature can then be chosen based on the findings of this study.

Kinetic model and Arrhenius equation parameters. The kinetic model used to describe the hydrochloric acid catalysed esterification of COFAD, and methanol was the model established by studying the esterification of pure FFA and methanol [9]. The experimentally obtained reaction conversion as a function of time was fitted into the model and the obtained model parameters are shown in Figure 4a.

Based on the results of the kinetic model fitting, paying attention to the values of the kinetic model parameters for this paper, it is apparent that the esterification reaction is a function of temperature. This confirms the assumption made in the development of the kinetic model. As temperature increases, the values of the equilibrium constant ( ) and the forward reaction rate constant ( ) increase. is the ratio of the product concentration to the reactant concentration at equilibrium. It is notable that the value of at each temperature is small. A small value of implies that the equilibrium concentration of the reactants is relatively large. Based on the reaction conditions, the concentration of methanol, a reactant, is very large since the molar ratio of methanol to COFAD used in the experiment was 10:1. Hence, the obtained equilibrium constant at each temperature has a small value. In addition, the value of at each temperature is greater than 1 . This implies that the formation of products in the reaction is favored. For this study, the reaction conditions except temperature were all kept constant. Hence, the increase in with the increase in temperature implies that at equilibrium, the number of products formed increases as temperature increases.

The reaction rate constant is the proportionality constant that relates the rate of the reaction to the concentrations of reactants. As previously mentioned, the reaction conditions, including reactant concentrations and catalyst loading, except temperature, were kept constant. Hence, the increase in with the increase in temperature implies that the reaction proceeds at a faster rate at higher temperatures.

A similar study by Malila [4] investigated the reaction kinetics of sulfuric acid-catalysed esterification of methanol and COFAD using a 10:1 COFAD to methanol molar ratio and a 0.00284 N catalyst loading. The experimental data of Malila [4] was also fitted into the same kinetic model and the results are shown in Figure 4b. A similar trend in the values of the kinetic model parameters ( and ) can be observed between the two studies. Moreover, looking at the values of the kinetic model parameters, it is notable that the -values of the HCl -catalysed esterification are times the -values of the one catalysed by . This implies that for the same reaction conditions, when HCl is used to catalyse the esterification of COFAD and methanol, the reaction will occur at a faster rate, in a sense that higher conversions are attained after a shorter reaction time, compared to when is used. In addition, it is evident that at relatively higher temperatures ( ), the -values of the -catalysed reaction are times the value of the one catalysed by HCl . This may imply that the -catalysed reaction favors the formation of the product more than the HCl -catalysed reaction. This may be due to the purity of the catalyst used. The purity of the HCl used by this study was the purest grade available in the market which is while the purity of the used by Malila [4] was . The presence of water in the catalyst contributes to the total concentration of water in the reaction mixture. As per Le Chatelier's principle, since water is one of the products of the forward reaction, the increase in its concentration could trigger the backward shift of the reaction.

The obtained coefficient of determination ( ) for each model at each temperature condition for both data sets is greater than or equal to 0.95 . An value that is greater than or equal to 0.95 indicates that the kinetic model adequately fits the experimental data. A plot of the kinetic-model conversion values and experimental conversion values as a function of time and temperature was generated and is shown in Figure 4. It is notable that most of the experimental data at each temperature condition fall agree with the model predicted values. Hence, this confirms that the kinetic model indeed adequately fits the experimental data which further implies that the values obtained at various temperatures through the model fitting are reliable.

Having established that the kinetic model fits the experimental data, the as a function of temperature was used to determine the parameters of the Arrhenius equation which were the preexponential factor or frequency factor and the activation energy . This was done by linear regression of the natural logarithm of versus . The results of the regression are shown in Figure 5b.

The and of the HCl -catalysed reaction are and respectively. The function of the acid catalyst in esterification is to facilitate the nucleophilic attack of the alcohol at the carbonyl carbon of the carboxylic acid [5,6]. Esterification reactions in the absence of an acid catalyst may not occur or may require a huge amount of energy to remove the OH from the carboxylic acid. For example, a study on the non-catalytic esterification of methanol and FFA obtained from Jatropha oil found that the activation energy of the reaction is [37]. This value is roughly five times the activation energy of the HCl -catalysed esterification. Hence, it can be said that hydrochloric acid was able to provide an alternative esterification reaction route that required a significantly lower activation energy. A lower activation energy is desired for a reaction because a lower threshold of energy is needed by the reactant molecules to be able to cross the lower barrier and react to form the products which ultimately results to a faster reaction.

A similar study by Su [9] investigated the reaction kinetics of the hydrochloric acid-catalysed esterification of pure FFA derived from soybean oil using a 5:1 methanol to FFA molar ratio and 0.500 N catalyst loading. Like the results of this study, the activation energy of the HCl-catalyzed esterification was significantly lower than the activation energy of the non-catalysed esterification. At a higher catalyst loading, there are more ions or protons available for the protonation step of the esterification reaction mechanism where the carbonyl oxygen acquires a proton to become a better electrophile [5,6]. The reaction proceeds more easily due to the alternative reaction route provided by the ions and the minimum amount of energy input required by the reactant molecules to activate or energize atoms to form the products, which is referred as the activation energy, is lowered. In the industrial context, a chemical reaction with a lower activation energy is advantageous because the reaction can occur at a considerably faster rate at a relatively lower temperature which may lessen the expenses on the fuel or source of energy. Then, it can be said that for the same reaction conditions, as the catalyst loading increases, the activation energy decreases. Comparing the results found by Su [9] to the results of this study, although the catalyst loading is slightly higher as shown in Figure 5a, the activation energy required is roughly one-third greater and the catalytic activity is times lower. A possible explanation for this discrepancy is that the main FFA-component of soybean oil (linoleic acid, ) has a longer carbon chain than the main FFA-component of COFAD (lauric acid, C12:0). As the carboxylic chain length increases, the FFA or the compound becomes more viscous due to the greater intermolecular forces of attraction for longer chains. Then, there is a higher chance of chains entangling causing steric hindrance and further resulting to a higher activation energy and slower reaction rate [38]. The esterification reaction starts with the protonation of the carbonyl oxygen of the FFA as the lone pair of electrons o the carbonyl oxygen picks up a proton from HCl to make the carbonyl carbon more electrophilic. Then, this will be followed by the nucleophilic attack of the alcohol to the carbonyl carbon as shown earlier in Figure 3. As the carbon chain length of FFA increases, the size of the molecule increases which could possibly hinder the protonation step and the subsequent nucleophilic attack. And this could ultimately result to a higher activation energy for the molecules to have enough vibrations to overcome the steric hindrance caused by the long carbon chain.

Fig. 5. (a) Catalyst loading in N [mol equivalents of rxn mix] and the corresponding catalytic activity [ mol FFA converted ] (b) and the result of the linear regression to determine Arrhenius equation parameters and coefficient of determination

Fig. 5. (a) Catalyst loading in N [mol equivalents of rxn mix] and the corresponding catalytic activity [ mol FFA converted ] (b) and the result of the linear regression to determine Arrhenius equation parameters and coefficient of determination

A study by Malila [4] investigated the reaction kinetics of sulfuric acid-catalysed esterification of methanol and COFAD using a COFAD to methanol molar ratio and a 0.00284 N catalyst loading. Comparing the findings of Malila [4] to the findings of this study, the catalyst loading is significantly lower and is only of the catalyst loading used in this paper and the activation energy is about one-third greater. This may imply that HCl was a better catalyst as it was able to provide an alternative reaction route that required a lower activation energy. However, despite a lower catalyst loading, the catalytic activity of is times the catalytic activity of HCl . There are two possible reasons that
could explain why the HCl -catalyzed esterification had a lower activation energy than the one catalyzed by . These are (1) HCl is a stronger acid than (2) and/or this study used a high HCl catalyst loading. Hydrochloric acid is a strong acid with an acid dissociation constant ( ) value of [39]. Further, hydrochloric acid ( HCl ) exhibits a higher degree of dissociation compared to sulfuric acid , which has dissociation constants of and , indicating that HCl provides a greater concentration of ions essential for the protonation step in the esterification reaction mechanism [5,6]. During this step, the carbonyl oxygen is protonated, enhancing its electrophilicity and thereby facilitating the reaction pathway with a reduced activation energy. An increased catalyst loading further elevates the concentration of ions, which can promote an alternative reaction pathway characterized by lower activation energy, ultimately accelerating the reaction rate, even at lower temperatures.

However, despite the higher loading of HCl , its catalytic efficiency was significantly lower than that of . This discrepancy can be attributed to the difference in reagent purity- contains substantially more water than . The additional water in HCl likely reduced its specific catalytic activity by driving the esterification reaction in the reverse direction, consistent with the observed lower equilibrium constant ( ) values for the HCl -catalyzed reaction compared to those catalyzed by .

Thermodynamic parameters. Thermodynamic analysis was used to study the esterification of COFAD using hydrochloric acid as a catalyst from the position of energy and entropy. The Gibbs free energy change was plotted against temperature as shown in Figure 6. The change in enthalpy and entropy was determined using the Gibbs Energy Equation. Figure 7 shows the change in enthalpy and entropy in the esterification reaction using hydrochloric acid and sulfuric acid as catalysts.

Fig. 6. Change in Gibbs free energy ( ) as a function of temperature ( ) in the esterification with methanol using HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper; as catalyst at a loading of 0.00284 N by Malila [4]; and HCl at a catalyst loading of 0.500 N by Su [9] Model used is shown in Equation 14

Fig. 6. Change in Gibbs free energy ( ) as a function of temperature ( ) in the esterification with methanol using HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper; as catalyst at a loading of 0.00284 N by Malila [4]; and HCl at a catalyst loading of 0.500 N by Su [9] Model used is shown in Equation 14

Fig. 7. Change in enthalpy and entropy in the esterification with methanol using HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper; as catalyst at a loading of 0.00284 N by Malila [4]; and HCl at a catalyst loading of 0.500 N by Su [9]

Fig. 7. Change in enthalpy and entropy in the esterification with methanol using HCl as catalyst at a loading of 0.472 N [mol equivalents rxn mix] by this paper; as catalyst at a loading of 0.00284 N by Malila [4]; and HCl at a catalyst loading of 0.500 N by Su [9]

From the thermodynamic parameters obtained in the esterification of methanol and COFAD using hydrochloric acid as a catalyst, it can be implied that the esterification reaction is exergonic ( 0 ), endothermic ( ), and irreversible ( ). As presented in Figure 6, the Gibbs free energy is negative ( ), which means that the reaction is exergonic at , and . This signifies that the reactants have more energy than the products. Thus, as time passes, free energy is released to the surroundings, allowing the esterification reaction to occur under the specified conditions even without external energy input.

Looking into the relationship of the Gibbs free energy change as a function of temperature in Figure 6, it is noticeable that the line for the esterification of COFAD with sulfuric acid is the steepest among the three studies which implies that with an increase in temperature, the Gibbs free energy change decreases the greatest, thus, the esterification reaction occurs more spontaneously than the other two reactions. This observation could be caused by the amount of water present in the catalysts. As mentioned in the previous sub-sections, contains relatively less water than 36 . The purity of the HCl used in this study was while the purity of the used by Malila [4] was . The presence of water in the hydrochloric acid could diminish its catalytic activity and accelerate the inverse reaction towards the reactant direction.

On the other hand, comparing this study to the study of Su [9], while both studies used a hydrochloric acid catalyst, esterification of soybean oil using HCl showed a steeper line, thus is more spontaneous than the esterification of COFAD using HCl. This could be because of the difference in the feedstock, which varies in FFA composition. In the study of Su [9], the soybean oil was hydrolyzed to prepare from it with an acid value of oil [9]. As compared to this study, the feedstock, COFAD, only contained FFA with an acid value of 188.17 mg oil. With this, it is evident that there is more free fatty acid available for esterification in the hydrolyzed soybean oil, thus, it has an increased rate of reaction. Because of the higher initial concentration of FFA found in the hydrolyzed soybean oil, it has a relatively higher reaction quotient, thus, the Gibbs free energy change becomes more negative, thus, the esterification reaction of soybean oil with HCl is more spontaneous.

The two thermodynamic driving forces of a chemical reaction are entropy and enthalpy. Figure 7 shows that the change in enthalpy is positive. The esterification process is characterized by the absorption of heat from the environment, resulting in products with higher energy content than the reactants. This thermal behavior indicates that an external heat source is necessary to drive the reaction, classifying it as an endothermic process. This aligns with existing literature, which has consistently demonstrated that the esterification of free fatty acids (FFA) with methanol is an
endothermic reaction [22,26-28]. Additionally, the calculated entropy values for the reaction are positive, signifying an increase in system disorder as the reaction proceeds. According to the second law of thermodynamics, a positive entropy change indicates that the reaction is spontaneous. This spontaneity is further supported by the fact that the Gibbs free energy of the products is lower than that of the reactants, resulting in an overall decrease in free energy during the reaction.

In a similar study by Malila [4], which investigated the esterification of methanol and COFAD using sulfuric acid as a catalyst, at a reaction temperature of and , the Gibbs free energy change is negative; thus, the reaction is exergonic ( ). However, at a reaction temperature of , the reaction is endergonic ( ). Since the equilibrium constant is relatively low at and equilibrium favors the reactants ( ), the Gibbs free energy change becomes positive. Meanwhile, the change in enthalpy is positive ( ); hence, the reaction is also endothermic. Conversely, the change in entropy is also positive ( ); thus, there is an increase in disorder as the reaction occurs. In another study by Su [9] which investigated the esterification of soybean oil with a hydrochloric acid catalyst, it was found that the reaction is exergonic ( ), endothermic , and irreversible ( ).

Looking closely at Figure 7, the enthalpy change in the esterification of COFAD using hydrochloric acid is much lesser, with a value of , than when sulfuric acid was used as a catalyst where the enthalpy change is , and when HCl was used in the esterification of soybean oil, where the change in enthalpy was . A much higher heat input is needed for the esterification reaction to occur using a sulfuric acid catalyst as compared to when hydrochloric acid is used. In this aspect, it can be said that hydrochloric acid is a better catalyst to use for the esterification of COFAD with methanol. However, in terms of entropy, using hydrochloric acid as a catalyst resulted in a relatively smaller entropy change with a value of as compared to when sulfuric acid was used where the entropy change was , and when soybean oil was the feedstock where entropy change was . The entropy change data shows that in the esterification using sulfuric acid, there is a greater increase in disorder in the system, thus, the reaction can occur more spontaneously than esterification using hydrochloric acid, thus, it would favor the formation of FAME more.

The relatively high values of the change in entropy using sulfuric acid in comparison to when hydrochloric acid was used could again be owed to the fact that hydrochloric acid has more water content which would shift the reaction in the reverse direction. Published research has observed noticeable inhibition effects of water on homogeneous acid-catalyzed esterification [27,40,41]. However, there is limited data on how water affects the spontaneity of an esterification reaction, particularly using hydrochloric acid as the catalyst.

In HCl and -catalyzed esterification of free fatty acids of this study, the reaction is thermodynamically spontaneous due to a positive entropy change ( ) and favorable enthalpy conditions. However, thermodynamic spontaneity does not ensure a rapid reaction, as reaction rate is determined by kinetic factors, particularly activation energy . HCl , with its higher dissociation, supplies more ions, potentially reducing and enhancing reaction rate. Yet, its catalytic efficiency is hindered by its water content, which promotes the reverse reaction. In contrast, , despite its lower dissociation, outperforms HCl due to its higher purity and strong dehydration capability, which suppresses the reverse reaction. This distinction highlights that a reaction can be thermodynamically favorable but kinetically slow if it faces significant energy barriers.

Thermodynamic analysis reveals that while entropy favors the esterification reaction, enthalpy does not, making the reaction's spontaneity temperature-dependent. According to the GibbsHelmholtz equation, the positive term ( ) dominates at higher temperatures, making the Gibbs free energy change ( ) negative and driving spontaneity. This aligns with findings by Malila [4] and Su [17], confirming that the esterification reaction is spontaneous only at elevated temperatures where is significant.

Conclusions and Recommendations

The original version of this paper is available on https://www.scientific.net/EC.12.49.pdf

In this study, the kinetics, and thermodynamics of the hydrochloric acid-catalyzed esterification of COFAD and methanol were analyzed. It was found that the reaction temperature had a positive effect on the rate of esterification. Equilibrium conversion was reached faster and had a higher value at increasing temperature. It was found that the equilibrium constant and forward reaction rate constant increased with the increase in temperature. The forward reaction rate constants at , , and were , and respectively. The frequency factor and the activation energy of the reaction were and , respectively. The change in Gibbs free energy at each of the three temperature conditions was negative, hence, the reaction was exergonic. This signifies that the reactants have more energy than the products. As time passes, free energy is released to the surroundings, allowing the esterification reaction to occur under the specified conditions even without external energy input. The change in enthalpy was positive, therefore the reaction was endothermic. This implies that external heat input is required to allow the reaction to occur. The calculated value of entropy was positive which implied that the esterification reaction was spontaneous only at high temperatures or when was high.

The water from the acid catalysts HCl and contributes to the increase of the concentration of water which could trigger the backward shift of the reaction which in turn lowers the specific activity of the catalyst. Hence, it is recommended to compare the specific activities by between HCl and catalyzed esterification of COFAD where the effect of the water content in each acid source is highlighted and incorporated in a higher-order pseudo-homogenous kinetic modeling approach as this was not clearly captured in the pseudo-homogenous first-order approach investigated in this study. In addition, optimizing esterification reactions with different acid catalysts in industrial applications is crucial for achieving high reaction efficiency, cost-effectiveness, and product quality. Different catalysts, such as HCl and , offer distinct advantages based on their acid strength, dissociation behavior, and dehydration capacity, which directly influence reaction rate, conversion efficiency, and product yield.

Acknowledgements

The original version of this paper is available on https://www.scientific.net/EC.12.49.pdf

The authors would like to acknowledge the efforts of Mr. Joseph Cabilara to help us whenever we needed assistance from the Unit Operations Laboratory for additional glassware and equipment, and the financial support provided by the University of San Carlos - Biomass and Biofuels (B&B) Research Group for the completion of the third-party analysis conducted by F.A.S.T. Laboratories..

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Liu Y, Lotero E, Goodwin JG. Effect of water on sulfuric acid catalyzed esterification. J Mol Catal A Chem 2006;245:132-40. .

Park JY, Wang ZM, Kim DK, Lee JS. Effects of water on the esterification of free fatty acids by acid catalysts. Renew Energy 2010;35:614-8. .

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The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-12/978-3-0364-3024-9

Engineering Chemistry, ISSN: 2813-6535, Vol. 12, pp 73-99

doi: 10.4028/p-27Ar1w

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2024-10-20

Revised:
2025-05-09

Accepted:
2025-07-25

Online:
2025-12-15

Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

The original version of this paper is available on https://www.scientific.net/EC.12.73.pdf

lan Dominic F. Tabañag , Jon Lionel O. Babanto , Kent Antonhel B. Catarig , James Anthony S. Solatorio , Jayhiel S. Malila

Philippine Council for Industry, Energy, and Emerging Technology Research and Development, Department of Science and Technology (DOST-PCIEERD), Bicutan, Taguig City, 1631, Philippines

Engineering and Industrial Research Division, National Research Council of the Philippines, Department of Science and Technology (DOST-NRCP), Bicutan, Taguig City, 1631, Philippines

Department of Chemical Engineering, University of San Carlos, Talamban, Cebu City 6000, Philippines

aian.tabanag@pcieerd.dost.gov.ph, bjonlionelbabanto@gmail.com, ckacatarigche@gmail.com, djamessolatorio16@gmail.com, ejayhielmalila@gmail.com

Keywords: reusability, response surface methodology - central composite design (RSM-CCD), directly sulfonated cacao shell solid acid catalyst, coconut oil fatty acid distillate (COFAD/CFAD), fatty acid methyl esters.

Abstract

The valorization of agricultural byproducts presents a viable strategy to mitigate feedstock challenges in Philippine biodiesel production. One promising feedstock for the industry is coconut oil fatty acid distillate (COFAD), which can be optimized for conventional alkali transesterification through pre-treatment by acid-catalyzed esterification. This process involves converting free fatty acids (FFAs) into fatty acid methyl esters (FAMEs) using an innovative solid acid catalyst derived from directly sulfonated cacao shell (CS-SAC). A response surface methodology (RSM) approach was employed to systematically assess the influence of two key parameters-methanol-to-COFAD molar ratio ( 6.4 to ) and catalyst loading ( 0.07 to COFAD)-on FFA conversion, while maintaining a constant temperature of and a reaction time of two (2) hours. Catalyst reusability was evaluated over four cycles under conditions that achieved the highest FFA conversion. Results indicated that an increase in the methanol-to-COFAD ratio initially enhanced FFA conversion. However, beyond a certain point, further increases in methanol concentration led to reduced conversion due to the dilution of the reaction medium. Regarding catalyst loading, a direct positive correlation with FFA conversion was observed across the tested range. The highest FFA conversion of 0.604 was achieved at the upper limits of the evaluated parameters, suggesting that further optimization beyond these ranges may further enhance conversion efficiency. CS-SAC demonstrated excellent stability, maintaining of its initial conversion efficiency even after three reuse cycles. These findings underscore the potential of directly sulfonated CS-SAC as a robust catalyst for industrial-scale esterification of COFAD.

Introduction

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The global reliance on petroleum-derived diesel remains significant, even amidst the increasing adoption of renewable energy sources [7]. Diesel fuel is essential in various sectors, including transportation, agriculture, and power generation, making it a critical component of modern economies. However, this heavy dependence on petroleum diesel poses several challenges, including price volatility, environmental degradation, and the depletion of finite fossil fuel reserves. In the Philippines, the situation is further complicated by a growing demand for diesel, which has been steadily increasing over the past decade [5,8]. With domestic production accounting for only of the diesel consumed, the country is overwhelmingly dependent on imported fossil fuels [10]. This dependence on foreign energy sources exposes the Philippines to supply chain disruptions and fluctuating global oil prices.

In response to these challenges, biodiesel has emerged as a promising alternative to petroleum diesel due to its renewable and environmentally friendly characteristics [1-3]. As an oxygenated fuel derived from renewable biological sources, biodiesel is typically produced through the transesterification of triglycerides from plant oils or the esterification of free fatty acids (FFAs) with alcohols [6]. Notably, the Biofuels Act of 2006 (Republic Act No. 9367) and the Renewable Energy Act of 2008 (Republic Act No. 9513) have been enacted in the Philippines to promote the use and commercialization of biofuels, including biodiesel. Under the Biofuels Act, all diesel fuels sold in the country must contain at least biodiesel by volume (B2), with provisions for future increases. As a result, approximately 173 million liters of biodiesel are produced annually in the Philippines, primarily using coconut oil (CNO) as feedstock, through the transesterification process [11-13].

Despite the favorable regulatory framework, the biodiesel industry in the Philippines has experienced stagnation, with blend rates remaining at B2 until last year; as recent developments increase the mandated blend to B3 in 2025. Factors contributing to this stagnation include limited investment in biodiesel production infrastructure, tax policies, low petroleum prices, and a lack of interest in biodiesel utilization [5]. Moreover, the local biodiesel industry is highly dependent on CNO as the primary feedstock, despite the Philippines being one of the world's largest coconut producers [14]. A significant portion of domestically produced is exported, with only allocated for biodiesel production [15]. This imbalance has created a feedstock limitation that prevents the country from achieving higher biodiesel blend targets, such as B5, making it economically unfeasible [5,16]. Consequently, the Philippines lags behind other nations in adopting higher biodiesel blend mandates [17].

To overcome these limitations, there is a critical need for alternative biodiesel feedstocks that are locally available, cost-effective, and do not compete with existing supply chains. Coconut oil fatty acid distillate (COFAD), a byproduct of CNO refining, represents a promising solution. COFAD is a waste product that can be effectively converted into coconut methyl esters (CME) for biodiesel production, leveraging existing CNO production infrastructure. Approximately 16,000 tons of COFAD are generated annually in the Philippines, which can yield around 16 million liters of CME [18]. Although this volume alone may not fully address the country's biodiesel feedstock demand at higher blend rates, the combined use of COFAD with other coconut industry byproducts-such as copra cake (CC)-offers the potential to enhance domestic biodiesel production capacity. By integrating these alternative feedstocks, the Philippines can increase its biodiesel blend rates beyond B2, reduce its dependence on imported petroleum diesel, and optimize the utilization of coconut industry byproducts for sustainable energy production [19].

COFAD is a non-edible waste byproduct from the deacidification step of the physical refining process of crude CNO mainly composed of lauric and myristic acids [18,20]. As the Philippines produces large amounts of CNO, this represents an untapped feedstock for biodiesel production. Since COFAD is the separated acidic part of crude coconut oil, it contains free fatty acids higher than the maximum FFA limit needed for alkali-catalyzed transesterification [21], ranging from 24.5 in lauric acid equivalents. Thus, if COFAD is to be used as a biodiesel feedstock for alkali-catalyzed transesterification it first needs to undergo a pretreatment process in order to decrease the to less than or equal to the requirement.

Because FFAs react with alkali, many pretreatment processes for lowering the FFA of the oil such as steam distillation [22], extraction by alcohol [23], and esterification using acid catalysts [24] have been proposed. Utilization of steam distillation, however, requires high temperatures and has a low efficiency while alcohol extraction requires large amounts of solvent due to limited solubility of FFA with alcohol. In comparison, esterification using acid catalysts is performed at mild temperature and pressure conditions and presents a better way for utilizing the FFA present in the feedstock by converting it to biodiesel [23,25].

Carboxylic acids such as fatty acids are esterified by alcohols in the presence of a suitable acid catalyst as shown in Equation 1.

Theoretically, one mole of fatty acid requires one mole of alcohol to produce one mole of fatty acid alcohol ester (FAAE) such as FAME. However, since the esterification reaction is a reversible reaction, then according to Le Chatelier's principle excess amounts of alcohol are required in the reaction to drive the reaction towards ester formation [26]. Common alcohols used in the esterification reaction are short-chain alcohols such as methanol, ethanol, propanol and butanol. Of the four, methanol is primarily used due to its relatively cheap price and high relative reactivity. Since methanol has the shortest chain length, it has the highest polarity and reacts with fatty acids faster compared to alcohols with bulkier structures [27,28].

Aside from the reactants, choosing the right kind of acid catalyst is very important in biodiesel production since the esterification reaction will not occur with its absence. One type of acid catalyst are the homogenous acid catalysts such as sulfuric, nitric, and hydrochloric acids [29,30]. However, utilization of these acids results in equipment corrosion and increased costs in the purification process due to generation of by-products during neutralization. Heterogenous or solid acid catalysts, on the other hand, are more favorable as they are easily recovered and reused for the next reaction cycle [31,32].

Heterogenous acid catalysts have various classifications and are classified as sulfated or mixed metal oxides, heteropolyacids, acid ionic liquids, and organically functionalized acid catalysts such as ion-exchange resins and sulfonated carbon materials [26,33]. In recent years, carbon-based solid acid catalysts have gained more importance as they are reported to have much better performance for biodiesel production and can be derived from inexpensive and renewable waste materials compared to other commercially available solid acid catalysts which includes zeolites, niobic acid and Amberlyst-15 [34-38]. The performance of a carbon-based catalyst however, is significantly affected by the choice of the starting materials thus it is crucial to look for new materials and investigate their structural and catalytic performance [39].

Various novel raw materials for synthesizing carbon-based solid acid catalysts were investigated such as sugarcane bagasse [39,40], jatropha seed cake waste [41], cacao shells [42], oil palm trunks [43], spent coffee grounds [44], red liquor solids [45], X. sorbifolium Bunge hulls [46], and peanut shells [47]. Most of these studies investigating the esterification conditions primarily use oleic acid as the oil feedstock - however palmitic acid [43] and soybean soap stock [46] have also been used. Regardless, the previous studies investigated the optimum synthesis conditions of their respective catalysts in terms of the carbonization and sulfonation temperatures and durations.

The synthesis of carbon-based SACs involves carbonization of a source material for the formation of the carbon support followed by sulfonation for the addition of active sulfonic sites. This can be done in either the two-step carbonization-sulfonation or simultaneous carbonization-sulfonation (direct sulfonation) processes. In the two-step process, the carbonization step is done through slow pyrolysis at for hours, leading to the formation of highly cross-linked, multi-ringed, aromatic structures that allows for functionalization with acid groups [48]. Afterwards, the sulfonation step is done by heating the carbonized material in concentrated sulfuric acid at ranges of for hours [39,41-44]. In the simultaneous carbonization-sulfonation or direct sulfonation process, the untreated carbonaceous material and sulfuric acid mixture are instead heated at ranges of for hours in order for simultaneous carbonization and sulfonation processes to occur [32,40,45-47]. In both processes, polycyclic aromatic carbon sheets with phenolic groups are created as a result of partial carbonization of the biomass. The addition of sulfuric acid then introduces sulfonic acids which can then covalently bond with the created polycyclic aromatic carbon sheets to form acid sites [49].

Compared to other traditional solid acid catalysts which only has a single functional group, sulfonation of carbon source materials brings about three acid sites, namely, the weak carboxylic acid , the medium phenolic acid , and the strong sulfonic acid ; all of which contributes to the total acid density of the catalyst [48]. In the previous study by Mendaros et al (2020) [32], the synthesized directly sulfonated CS-SAC catalyst has a total acid density of catalyst with phenolic acid being the main contributor of around of the total acid density, followed by carboxylic acid at and sulfonic acid at of the total acid density. Despite being
the least, the sulfonic acid functional group is considered to be the main functional group and that the other weaker acid groups (i.e., -OH and -COOH ) had no significant impact in the conversion of FFA .

The previous studies using carbon-based solid acid catalysts for the esterification of pure FFA investigated the effects of carbonization and sulfonation synthesis temperatures and times on the conversion of FFA at constant esterification parameters (reaction time, catalyst loading, and reaction temperature). For the two-step carbonization-sulfonation process, previous studies [39,41-44] used catalyst loadings of , temperatures and times of for hours, yielding an FFA conversion of . For the direct sulfonation process, past studies [ ] used catalyst loading at for hours, yielding an FFA conversion of . All the reviewed studies used methanol as the alcohol reactant. Some studies from both processes used higher esterification temperatures greater than the boiling point of methanol however these studies used methanol-to-oil molar ratios of less than 10 which would elevate the boiling points of the alcohol solutions thus preventing alcohol loss.

For both biomass-based (or carbon-based) heterogeneous solid acid catalyst synthesis processes, reusability analysis were done for catalysts explored by literature with results expressed in terms of %retention which is the part of the conversion that is retained from the 1st cycle to the nth cycle. In the catalyst reusability analyses, generally at least four esterification cycles were done, with one study using two cycles [44] and another using eight cycles [39]. In most studies, methanol was mainly used for washing post-esterified catalysts, although one reported study [39] also used n-hexane instead, showing the applicability of using other solvents. Literature reports that a large %retention range of is present. Some studies show that certain catalysts (sugarcane bagasse, oil palm trunk, and peanut shell catalysts) give out large %retentions of above 95% while having esterification cycles of greater than five [39,43,47], while some catalysts (spent coffee grounds, and red liquor solid catalysts) give out small %retentions of below 30% despite only having fewer esterification cycles of two-four cycles [44,45]. Factors affecting the %retention are the addition of a water washing step right after sulfonation to remove unbound acids and the choice of washing solvent used during catalyst recovery [32,39]. Additionally, in the reusability analyses of catalysts from literature, a decrease in conversion after each cycle/washing was reported to be caused by three main aspects. The first is the reduction of catalyst mass caused by insufficient mechanical strength of the solid catalyst which results to catalysts breaking down into relatively small particles [50]. The second is the leaching of active sites caused by the addition of excess alcohol and exposure of the catalyst with a hot liquid [51-53]. The third is the decrease in the number of active sites which may be caused by the fatty acid methyl esters blocking the pores of the catalyst surface [54]. Additionally, alcohol may react with the acid groups in the surface of the catalyst forming esters and lowering the number of acid sites considerably [55].

One of the catalysts that has a great potential in the production of biodiesel but is still relatively unexplored is the cacao shell-derived solid acid catalyst (CS-SAC). The Philippines produces approximately 7000 metric tons of cacao shells as an agro-industrial waste in cocoa bean processing for chocolate production [56]. Cacao shells also have a relatively high fixed carbon content of around [32] which is comparable to the fixed carbon content of the other materials used in the studies . Fixed carbon content is the measure of the amount of carbon remaining after carbonization and is an important characteristic for determining the potential of carbonaceous materials to be used as supports. Both the direct sulfonation and two-step carbonization-sulfonation method synthesis conditions were already optimized by Mendaros et al. (2020) [32] and Bureros et al. (2019) [42] with acceptable biodiesel production conversions of and respectively. The two previous studies also show that directly sulfonated cacao shells have a higher stability in terms of %retention and higher total acid density than the two-step carbonizationsulfonation process. Considering that direct sulfonation method has less synthesis time and energy requirements, it is more practical for industrial use [32].

Limited research has been done on the application of carbon-based solid acid catalysts for biodiesel production using COFAD as feedstock specifically in the Philippines. As of the writing of this paper, only Malila (2020) [18] has published an optimization study of esterification of FFA in COFAD using
heterogenous acid catalysts which was Amberlyst 15. In his parametric optimization study, Amberlyst 15 achieved a FFA conversion of using the optimized esterification conditions ( methanol-to-oil molar ratio, oil catalyst loading, hours). Prior to the optimization of the parameters, he also studied the effects of methanol-to-COFAD molar ratio, catalyst loading, and reaction time on FFA conversion using a one-variable-at-a-time (OVAT) approach, in which all other variables are held constant except for the variable of interest.

The results of Malila's (2020) [18] OVAT analysis shows that increasing the methanol-to-COFAD molar ratio leads to an increase in FFA conversion and FAME yield until it reaches a peak. Further increase causes the FFA conversion and FAME yield to drop instead due to the dilution of the oil [57]. Furthermore, increasing the catalyst yield and reaction time also increases the FFA conversion and FAME yield until it reaches a point wherein further increase in parameter value offers insignificant increase in FFA conversion and decreases the FAME yield. The stagnation of FFA conversion and decrease in FAME yield may have been caused by the reaction reaching an equilibrium with respect to the other reaction conditions that were held constant [58].

As for the reaction temperature, literature shows that using esterification temperatures slightly over the boiling point of methanol is possible [32,39,41,43-47,58,59], typically at ranges of , with the reasoning being that increasing temperatures increases FFA conversion due to the reaction rate constant and activation energy being dependent directly on temperature changes [60]. However, a previous study by Yin et al. (2016) [61] which used methanol as the reactant shows that FAME yield peaks at around with further increases causing a decrease in the FAME yield. This is due to the boiling point of methanol at standard atmospheric pressure . Exceeding the boiling point without changing the pressure causes the methanol in the bulk phase to evaporate, depleting the available methanol for the esterification reaction [18,59]. Because of this, studying esterification parameters at a sufficiently high constant temperature below the atmospheric boiling point, such as at , is preferred.

Similarly, reaction times are shown to have an effect on FFA conversion. Past kinetic studies [18,40,58] have shown that FFA esterification with heterogeneous solid-acid catalysts regardless of catalyst type require long reaction times in the span of hours if higher FFA conversions are desired, which is due to the mass transfer limitations between solid catalysts and fatty acids [62,63]. Additionally, a study by Su et al. (2008) [64] using heterogenous catalysts require long reaction times ( 30 hours) to achieve equilibrium conversion. However, it is not necessary to obtain high values of conversion in order to investigate the effects of the other variables. Thus, investigating the initial FFA conversions with short reaction time is practical.

Most studies on biomass-based solid acid catalysts so far focus only on the valorization aspect and synthesis of such carbon-based catalysts [32,42]. Thus, there is a need to bridge the gap between novel catalysts and biodiesel feedstocks to help address the issue of insufficient biodiesel feedstock and also highlight the potential of carbon-based catalysts for biodiesel production. In particular, literature has not focused on the esterification of COFAD and methanol using directly sulfonated cacao shell catalyst in comparison with commercially available catalysts such as Amberlyst-15. So far, little literature has been found that investigates the esterification of COFAD and methanol using directly sulfonated cacao shell catalyst and on the reusability of directly sulfonated cacao shell catalyst for such application. Since this study uses novel feedstock and catalyst, factor screening using 2 k factorial design of experiment is a viable option for evaluation of esterification parameters. With limited information on esterification of COFAD using biomass-based catalyst, the range of values used for factor screening were based on the existing parameters used by various studies involving esterification of oleic acid using directly sulfonated and two-step carbonization-sulfonation biomass catalyst [32,39-42,44,45,47].

Thus, this study aims to (1) investigate the effect of methanol-to-COFAD molar ratio and catalyst loading to the heterogeneous esterification of COFAD (i.e., FFA conversion) at 2 hours, , and 1 atm, using a 22 factorial screening Response Surface Methodology - Central Composite Design (RSM-CCD) approach, and (2) determine the catalyst reusability of directly sulfonated cacao shells at the esterification conditions with the highest observed conversion.

Materials and Methods

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COFAD was purchased from AD Gothong Manufacturing in Mandaue City, and cacao shells were sourced from a small-scale cacao bean processor in Mahinog, Camiguin. Amberlyst® 15 dry hydrogen form (styrene-divinylbenzene macroreticular matrix, 39389-20-3) was acquired from Sigma-Aldrich. Chemical reagents used were barium chloride dihydrate ( , Ajax Finechem Pty Ltd), methanol ( , Scharlab S.L.), ethanol ( , Scharlab S.L.), phenolphthalein indicator ( , Scharlab S.L.), potassium hydrogen phthalate ( , Ajax Finechem Pty Ltd), n-hexane ( , Tedia Company, Inc.), and sodium chloride ( , Ajax Finechem Pty Ltd), sodium hydroxide ( , Scharlab S.L.), hydrochloric acid ( , Ajax Finechem Pty Ltd), sulfuric acid ( , Ajax Finechem Pty Ltd) and distilled water. Pretreated COFAD sample was sent to an external laboratory for moisture content and gas chromatography analyses. The standard used for gas chromatography analyses was Supelco 37 Component FAME Mix (CRM47885, Lot LRAC9768, Sigma-Aldrich Pte Ltd). The research design flow diagram for this study are shown in Appendix A.

Preparation of Raw Materials. Approximately 2 L of COFAD and 500 g of cacao shells were pretreated prior to usage. Details of the pretreatment are discussed below.

Preparation of Raw Materials: Preparation of COFAD prior to characterization and esterification. About 1 L COFAD was poured into a 1.5 L beaker. Thereafter, it was heated at 100 for 20 minutes on a hot plate magnetic stirrer (Thermolyne Cimarec 2) to allow traces of water to evaporate. The COFAD was then filtered in a vacuum filtration set-up using Whatman No. 2 filter paper to remove suspended solids. The filtrate was stored at ambient conditions ( ) in a screw-cap borosilicate glass reagent bottle throughout the whole duration of the experiment which was around 5 months.

Preparation of Raw Materials: Preparation of cacao shell prior to characterization and esterification. The collected cacao shells were dried in a drying oven (Memmert, UN 55, Yana Chemodities, Inc.) set to for three hours. The dried cacao shells were then milled using a Wiley mill (Model 4, Thomas Scientific, USA) fitted with a 2 mm aperture screen to prepare for catalyst synthesis, particle size distribution analysis, and proximate analysis. After which, the dried, milled cacao shells were stored in a sealed plastic container and two representative samples were taken for moisture analysis (see proximate analysis). A moisture content of less than is desired as to prevent spoiling during storage. The moisture analysis resulted to a value of less than moisture, so no re-drying of the cacao shells was done.

Cacao shell characterization. The milled cacao shells were characterized to determine its particle size, moisture content, volatile matter content, ash content, and fixed carbon content. These properties, particularly the particle size and fixed carbon content, determine if the cacao shell is suitable as a carbon support for the acid sites during sulfonation.

Cacao shell characterization: Particle size distribution analysis. Particle size distribution analysis of cacao shell (CS) was based on the ASTM C136 Standard. Test sieves were stacked in an order of decreasing screen opening ( , and ) and 300 g minimum of the milled CS were placed on top of the sieve. The top sieve was then covered and the whole stack was transferred on a mechanical sieve shaker (Matest Srl Brembate Sopra, Italy) where it was shaken for 15 minutes. After which, the solids retained on each sieve were weighed. Using the mass of the solids retained on each sieve, the mean particle size of the milled cacao shells was calculated using Equation 2.

where is the mass of the retained cacao shell particles on the sieve, is the total mass of the cacao shell subjected to sieving, and is the average screen opening of adjacently stacked sieve.

Cacao shell characterization: Proximate analysis. The proximate analysis of cacao shell was carried out based on the ASTM D1762-84 Standard and done in duplicates. First, empty and clean
crucibles were prepared and wiped dry with lint-free tissues. The empty crucibles with their lids were then heated for 10 min at in a muffle furnace (Vecstar Furnaces) then cooled in a desiccator for 1 h . Once cooled, the crucibles without the lids were weighed using an analytical balance. Afterwards, about 1 g each of the milled cacao shell was added and weighed into the cooled and dry crucibles. The weighed crucibles were then placed in a drying oven (Memmert UM 500, Yana Chemodities, Inc.) heated at a temperature of for 2 h followed by cooling in a desiccator for 1 h prior to weighing. This process of weighing and drying was repeated until the mass of the samples was constant (less than 0.0005 g mass loss). The moisture content (%moisture) of the CS was then calculated using Equation 3.

where wet and are the mass of the wet and dried cacao shells, respectively.

After which, the crucibles containing the dried samples were covered with the lids and placed in a muffle furnace then set at for heating to remove volatile matter. The crucibles were heated in the furnace at for a total of 11 minutes. After heating and allowing the furnace to cool near room temperature, the samples were then taken and cooled in a desiccator for 1 h prior to weighing. The volatile matter content ( ) of the CS was calculated using Equation 4.

where is the mass of the cacao shell sample after heating at .
The sample-containing crucibles, without the lids, were heated in a muffle furnace maintained at a temperature of for 6 h . Afterwards, the crucibles were covered and transported into a desiccator for 1 h for cooling before weighing. Then, the sample-containing crucibles were repeatedly burned at for 1 h without the lids, cooled for 1 h with the lids, and reweighed until constant mass was achieved (less than 0.0005 g mass loss). The ash content ( ) of the CS was calculated using Equation 5.

where is the mass of the cacao shell residue after the last repetition of burning at . The fixed carbon content ( ) in dry basis was then calculated using Equation 6.

Synthesis of cacao shell-solid acid catalyst.

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The cacao shell-solid acid catalyst (CS-SAC) was synthesized via simultaneous carbonizationsulfonation process based on the study of Mendaros et al. (2020) [32] under optimized conditions of synthesis temperature and 6 h synthesis time. Five samples of about 3.5 g of powdered cacao shells were weighed and transferred into heating digester tubes. Each 3.5 g sample was immersed in 70 mL of to promote homogeneity following a ratio of milled cacao shell to concentrated sulfuric acid. After which, the cacao shell-acid mixtures were heated in a heating digester (DK 8S, VELP Scientifica) at a rate of until they reach a temperature of . This temperature was maintained for six hours for the simultaneous carbonization-sulfation process.

The resulting mixture was then transferred into a 3 L Erlenmeyer flask immersed in an ice bath for cooling to room temperature. After cooling, about 1 L of distilled water was added to dilute the reaction mixture. The diluted reaction mixture was filtered using ordinary filter paper in a vacuum filtration set-up to recover the solid catalyst and was then continuously washed with hot distilled water to further remove unbound acids. After each washing, the pH of the washing solution was determined with the use of pH paper then about four drops of was added into the
washing solution to qualitatively check for the presence of sulfate ions ( ) in the solution by the formation of white barium sulfate precipitate. The washing with hot distilled water was done until the pH of the washing solution is the same as distilled water and there is no observed formation of barium sulfate precipitate. When this was achieved, the solid acid catalyst together with its filter paper was weighed and dried in the oven set to for about . Additional batches of cacao shells were synthesized until the desired amount of CS-SAC produced was acquired. The CS-SAC produced was utilized for total acid density determination and esterification.

Total acid density analysis of solid acid catalysts. The procedure for the total acid density analysis was derived from the work of Malila (2020) [18]. About 1 g of solid acid catalyst was weighed and mixed with 50 mL of 0.05 M volumetric standard NaOH solution. The mixture was then agitated for 3.5 h at 200 RPM using a tabletop shaker (New Brunswick Scientific, USA). After agitation, the resulting mixture was filtered using Whatman No. 2 filter paper to separate the solid catalyst from the solution. Three 5 mL aliquots of the filtrate were taken, and each aliquot was mixed with 15 mL of 0.05 M HCl in a 100 mL flask to completely neutralize the base present. Three drops of phenolphthalein indicator were then added into the neutralized mixtures prior to back titration with 0.05 M NaOH until the endpoint was reached. The total acid density ( TAD) of the samples were calculated using Equation 7.

where and are the concentration and volume of NaOH added before agitation, and are the concentration and volume of HCl to complete neutralize the base, and are the concentration and amount of NaOH used for back titration, soln ( ) and V_aliquot ( ) are the volumes of the filtrate obtained after solid catalyst separation and aliquot used for titration, and cat is the mass of the solid acid catalyst (CS-SAC or Amberlyst-15).

Characterization of COFAD. The pretreated COFAD was characterized for its moisture content, acid value, fatty acid profile, molar mass, and %FFA as lauric acid. The acid value of the COFAD was utilized for the calculation of the catalytic activity while the molar mass of COFAD was used to determine the mass of methanol needed for a specified methanol to COFAD molar ratio in the later sections.

Characterization of COFAD: Acid value analysis. The acid value of the samples was determined based on the ASTM D1980-87 Standard. About 0.5 g of COFAD sample was weighed in a Erlenmeyer flask and diluted with 20 mL absolute ethanol. Approximately three drops of phenolphthalein indicator were added into the COFAD-ethanol mixture, then the resulting mixture was titrated against standardized 0.1 M ethanolic NaOH solution until the end point was reached. The acid value of the pretreated COFAD ( ) was calculated using Equation 8.

where and are the volume and concentration of solution used in the titration, 《MM/_NaOH (g/mol) is the molar mass of NaOH, and COFAD is the mass of the COFAD sample.

Characterization of COFAD: Fatty acid profile analysis and moisture content analysis. Approximately 400 mL of pretreated COFAD that was stored for around 5 months was sent to F.A.S.T. Laboratories in Mandaue City, Cebu for the determination of the fatty acid profile and moisture content. The fatty acid profile analysis was done using gas chromatography while Karl Fischer titration was performed for the moisture analysis [65]. The gas chromatography was performed using Restek 2560 column with an injection volume of and flame ionization detector (FID). The conditions for the quantification of fatty acid present in COFAD were as follows: injector temperature of , detector temperature of , and column temperature of . The carrier gas used was nitrogen and a constant flow rate of was employed.

Characterization of COFAD: COFAD molar mass. The molar mass of the COFAD (MM_COFAD) was determined using Equation 9.

where or is the percent by weight of a specific fatty acid, and is the molar mass of a specific fatty acid.

Characterization of COFAD: %FFA as lauric acid. The total amount of free fatty acid in COFAD ( ) was estimated in terms of lauric acid since it is the most abundant FFA in coconut oil. It was calculated using Equation 10

where /MM/_(lauric acid) ( ) is the molar mass of lauric acid.
Screening factorial response surface methodology: central composite design. Factor screening is often used for studies involving new systems. The factorial design of experiment is a commonly used technique in factor screening to study the effects of factors on a response variable, and it is particularly useful when the number of factors is relatively small. By systematically varying each factor at two levels, this design allows for the estimation of the main effects from each factor as well as the interactions between them while minimizing the number of experimental runs. However, this design assumes a linear relationship between the factors and the response, and it does not account for higher-order effects or curvature in the response surface. To address this limitation, additional runs can be added to the design, such as axial runs and replicates of center points. Axial runs involve selecting intermediate levels of the factors in addition to the high and low levels used in the factorial design. This can help identify any curvature in the response surface and allow for the estimation of quadratic effects. Replicates of center points involve repeating the experiments at the central point of the design, which can help to estimate the experimental error and provide a measure of the precision of the experimental results. By incorporating these additional runs into the design, the design of experiment becomes a response surface methodology- central composite design (RSM-CCD) which can obtain a more complete understanding of the relationship between the factors and the response variable, and develop higher-order models that better capture the behavior of the system [66].

The OVAT study by Malila (2020) [18] on the effect of COFAD esterification parameters shows that an increase in methanol-to-COFAD ratio leads to an increase in FFA conversion until it reaches a peak. The same study also exhibits that increasing the catalyst loading also increases the FFA conversion until it reaches a point that further increase in catalyst loading provides no significant changes to FFA conversion. Thus, these behaviors are to be taken into account in the results of the factor screening using the factorial design of experiment.

Design-Expert 13 software was utilized for the determination of the effect of methanol to COFAD ratio and catalyst loading (in COFAD) to the FFA conversion of COFAD using CS-SAC ( objective). A two-factor two-level RSM using a rotatable type ( ) of CCD was used. In this design of experiment, the two parameters were varied simultaneously and the model equation that describes the effect of the two parameters to FFA conversion was determined while keeping other parameters such as temperature ( ), pressure ( 1 atm ), and reaction time ( 2 h ) constant. The optimized parameters were calculated by the software.

Using CCD, thirteen randomized runs were set, each having different combinations of the values of the parameters to be investigated. The range of values investigated was based on the mean and standard deviations (i.e., mean ± std) of the investigated parameters in literature [32,39-42,44,45,47]. This was used as the lower and upper boundaries since no studies have been conducted involving the esterification of COFAD using CS-SAC. Methanol to COFAD molar ratios within the range of 6.4:1 to and catalyst loadings within the range of 0.07 to COFAD were explored for CS-SAC. The summary of the combinations of process parameters for each experiment run are shown in Table 1.

Table 1. Summary of the randomized combination of process parameters for each experimental run in the CCD-RSM approach at a constant temperature ( ), pressure ( 1 atm ), and reaction time ( 2 h) using CS-SAC as catalyst

Uncoded Levels | Coded Levels
Run | Methanol to COFAD molar ratio (mol/mol) | Catalyst loading (mmol H⁺/g COFAD) | Methanol to COFAD molar ratio (mol/mol) | Catalyst loading (mmol H⁺/g COFAD)
1 | 16.9 | 0.42 | +1 | +1
2 | 11.7 | 0.0028 | 0 | -√2
3 | 19.2 | 0.25 | +√2 | 0
4 | 11.7 | 0.25 | 0 | 0
5 | 11.7 | 0.25 | 0 | 0
6 | 11.7 | 0.25 | 0 | 0
7 | 11.7 | 0.49 | 0 | +√2
8 | 11.7 | 0.25 | 0 | 0
9 | 11.7 | 0.25 | 0 | 0
10 | 6.4 | 0.42 | -1 | +1
11 | 6.4 | 0.07 | -1 | -1
12 | 16.9 | 0.07 | +1 | -1
13 | 4.1 | 0.25 | -√2 | 0

Using the combinations in Table 1, the response (FFA conversion) using CS-SAC as catalyst was determined experimentally following the procedures on in the next sub-sections. Design-Expert 13 was used to conduct multiple regression analysis which would then generate a quadratic equation, or the diminished form as shown in Equation 11 [67].

where , and are the regression coefficients of the intercept, linear, quadratic and interaction coefficients respectively, and are coded independent variables, and is the response variable. Analysis of variance (ANOVA) was then utilized to test the validity of the model equation obtained. Model reduction can be performed to improve the fit statistics, i.e., maximize the values of , adjusted , and predicted while keeping the three values close together.

Esterification of COFAD. The FFA conversion of COFAD and catalytic activities of Amberlyst15 and the synthesized CS-SAC were determined through esterification. Specifications on the number of runs and the conditions discussed were used. The following steps were done for every esterification run. Ten grams of the pretreated COFAD and the corresponding catalyst mass to achieve the set catalyst loading were added in a 250 mL screw capped flask - this set catalyst loading is calculated by multiplying the total acid density of the catalyst with its dry mass. The flask was then placed in an incubator shaker and pre-heated to . When the incubator shaker reached , the flask was taken out of the incubator shaker and the corresponding methanol amount to achieve the set methanol to COFAD molar ratio was quickly added into the flask. Afterwards, the flask with the complete reaction mixture was put back into the incubator and let set to heat until the temperature reached again. When the target temperature was reached, the incubator shaker set at 200 RPM was activated. A timer set at an esterification reaction time of 2 hours was also activated at the same time when the agitating mechanism was activated. To stop the reaction, the reaction mixture was allowed to cool to room temperature using an ice bath.

SAC recovery. The spent solid acid catalyst (SSAC) was separated from the liquid phase using vacuum filtration with a Whatman No. 2 filter paper to speed up the process. The SSAC was then washed with 25 mL n-hexane twice to remove the adhering product mixture. After washing, the SSAC was transferred to an evaporating dish and was left in the fume hood for hours to evaporate the n -hexane prior to drying in an oven for approximately at [42]. The recovered SSAC was then characterized for its total acid density.

FAME purification. For product purification, the crude FAME was transferred to a 250 mL separatory funnel along with 25 mL n-hexane to dissolve the FAME and unreacted FFA. Ten milliliters of was added to remove leached acid from the reaction product mixture and afterwards, the mixture was swirled thoroughly and allowed to settle to form two distinct layers. The acid value of the bottom layer, /_bottom, was determined to ensure that any leached FFA are accounted for in the AV analysis. The washing step using was repeated until the pH of the bottom layer is the same as that of the . About 10 g aliquot was collected from the oil phase and was placed in the fume hood to dry for approximately 12 hours to remove the n -hexane solvent. After drying, the remaining mixture was weighed to identify the amount of hexane lost. The drying and weighing steps were repeated until a constant weight is obtained (less than difference).

FFA conversion determination. Using the acid value (AV) of the oil sample determined using acid value analysis, the FFA conversion ( ) can then be calculated using Equation 12.

where and is the acid value of the oil sample before and after the esterification reaction.

Reusability analysis of CS-SAC. The reusability analysis ( objective) was done based on the study of Flores et al. (2019) [40]. Two sets (with 20 g COFAD as basis) following the methanol to COFAD molar ratio and catalyst loading which yielded the highest observed conversion during the factor screening ( objective) were esterified. The catalyst was then recovered. Only the initial and final CS-SAC cycles were analyzed for their total acid density. A total of four cycles were done since studies [32,40,42] that used carbon-based solid acid catalyst show a stabilization of FFA conversion after four to five cycles, omitting the need for further recycle. Knowing the point at which the %retention stabilizes will aid in deciding whether the catalyst is economically practical for reusing especially when considering its conversion after every cycle. Reusability study starts with cycle 1 using the unused catalyst and followed by succeeding cycles (cycles ) which are the recycles. In order to maintain constant catalyst loading and methanol to COFAD molar ratio, the amount of COFAD and methanol utilized was adjusted based on the actual amount of SAC recovered after each reaction cycle. The percent retention (%retention) with respect to the first cycle's conversion is determined using Equation 13.

where is conversion of the cycle, and is the conversion of the cycle.

Results and Discussions

The original version of this paper is available on https://www.scientific.net/EC.12.73.pdf

Characterization of feedstock and catalyst. The feedstock and catalyst are characterized to serve as basis of comparison with literature. The COFAD was characterized based on its molecular weight, acid value, %FFA as lauric acid, moisture content, and fatty acid profile. On the other hand, the cacao shell was characterized by its volatile matter, ash, and fixed carbon content, and the synthesized CSSAC was characterized by its total acid density.

Characterization of feedstock and catalyst: Coconut oil fatty acid distillate. Coconut oil fatty acid distillate (COFAD) purchased from AD Gothong Manufacturing in Mandaue City was pretreated by heating for 20 minutes at and filtration to remove excess moisture and insoluble solids. The pretreated COFAD was found to have an average acid value of oil, average FFA as lauric acid of , and moisture content of , with literature values close to the obtained values as shown in Table 2. The remaining 35.2% of the COFAD is likely composed of tri, di-, mono-glycerides and unsaponifiable components.

An average molecular weight was found to be , showing a similar molecular weight with literature [18,68]. Determination of the average molecular weight of COFAD is important since COFAD is mainly a mixture of various fatty acids from coconut oil itself each with different molecular weights in varying amounts as shown in the fatty acid profile later. Additionally, the average molecular weight of COFAD will slightly differ due to the varying process conditions in the deacidification or deodorization step in coconut oil refining which uses steam at . Furthermore, the average molecular weight is used for calculating the amount of COFAD with respect to the MeOH :COFAD molar ratio and helps determine that the COFAD sample was actually made as a byproduct from coconut oil refining [18,20].

Because a high average acid value and %FFA as lauric acid was found which will cause unwanted saponification in traditional transesterification, esterification pretreatment is needed to decrease the acid value and %FFA to equal or below oil and respectively [20] if COFAD is to be used as feedstock for transesterification in FAME production.

Table 2. Coconut oil fatty acid distillate characteristics

Component | This study | Malila [18] | 168 Exports Trading Co. [68]
Average Molecular Weight (g/mol) | 214.54 | 212.77 | -
Acid Value (mg NaOH/g oil) | 129.33 ± 0.88 | 132.57 | 114
%FFA as Lauric Acid | 64.77 ± 0.01 | 66.39 ± 0.46 | 55.0 min.
Moisture Content (%w/w) | 0.2746 | - | 1.0 max.

In the esterification reaction (as shown in Equation 14), water is one of the byproducts which will interfere in converting FFAs into less-acidic FAMEs since water can cause a reverse reaction to occur. Thus, moisture content was determined to ascertain the suitability of the pretreated COFAD feedstock. Since a moisture content of less than was observed, it indicates that the feedstock is suitable for esterification without foreign water interfering in the equilibrium reaction [69].

The fatty acid profile of COFAD, as shown in Table 3, reveals that it is primarily composed of lauric acid ( ), followed by myristic ( ) and palmitic ( ) acids, with a total of ten fatty acids identified, ranging from C6 to C18. Saturated fatty acids constitute 89.9% of the total fatty acids, and the average molecular weight is . It is important to note that these values represent not only free fatty acids (FFAs) but also fatty acid molecules released from glycerides during derivatization in gas chromatography analysis. The fatty acid composition is consistent with other studies, indicating the reliability of COFAD's profile.

In the Philippines, national standards for pure coconut biodiesel (B100) require a minimum methyl laurate content of [70,71]. As lauric acid is directly converted to methyl laurate during esterification, profiling the fatty acids in COFAD is crucial to ensure that the final biodiesel product meets the specified standards. Additionally, the presence of other fatty acids in COFAD confirms its coconut oil origin, which is expected to contain lauric acid [72,73]. However, the lauric acid content in this study was lower than expected (below ), which may impact the final methyl laurate content of the biodiesel. This deviation could be attributed to the prolonged storage period (5 months) of the COFAD sample prior to analysis, potentially leading to a reduction in lauric acid content.

It can also be seen that unspecified components (others) comprise 13.10% of COFAD. Literature shows that these unspecified components are glycerol and unsaponifiable matter, which in vegetable oil fatty acid distillates (FADs) like COFAD, are mainly composed of tocopherols, sterols, and squalenes [74,75]. The unspecified components of this study is also higher compared to Malila (2020) [18]. This may have been caused by the lower concentration of %FFA as seen in Table 2 which then possibly denotes higher glycerides content which upon derivatization becomes glycerol.

Table 3. Fatty acid profile of coconut oil fatty acid distillate stock

Component | %w/w
| This study | Malila [18] | Fabian [76] | 168 Exports Trading Co. [68]
Caproic acid (C6:0) | 0.235 | - | - | -
Caprylic acid (C8:0) | 3.94 | 3.93 ± 0.97 | 4.34 | 4.3 – 9.4
Capric acid (C10:0) | 3.85 | 4.43 ± 0.85 | 4.14 | 5.2 – 7.5
Undecanoic acid (C11:0) | 0.48 | - | - | -
Lauric acid (C12:0) | 38.20 | 48.18 ± 5.22 | 46.45 | 42.4 – 47.3
Myristic acid (C14:0) | 16.60 | 20.01 ± 1.31 | 17.49 | 15.8 – 19.7
Palmitic acid (C16:0) | 10.80 | 11.13 ± 2.29 | 3.85 | 7.0 – 9.6
Stearic acid (C18:0) | 2.60 | 2.69 ± 0.87 | 3.45 | 1.9 – 3.8
Oleic acid (C18:1) | 8.10 | 7.78 ± 2.41 | 3.87 | 4.7 – 9.4
Linoleic acid (C18:2) | 2.10 | - | - | 1.0 – 2.4
Othersa | 13.100 | 1.78 ± 0.50 | 15.44 | -

not included in molecular weight calculation
Characterization of feedstock and catalyst: Cacao shell and solid acid catalysts. Cacao shells (CS) obtained from Camiguin Island were analyzed for mean particle size, volatile matter, ash, and fixed carbon content. CS as received were pre-dried and underwent particle size analysis which were found to have a mean particle size of . A volatile matter content of , ash content of , and fixed carbon content of were obtained from proximate analysis. As shown in Table 4 a summary of the CS sample's characteristics compared to literature.

Table 4. Characteristics of CS samples

Composition (%w/w)a | This study | Mendaros [32] | Bureros [42]
Mean particle size (μm) | 1424.72 ± 3.15b | 93.15 ± 2.27 | 840.84 ± 7.74
Volatile matter | 71.8 ± 0.12 | 66.78 ± 0.68 | 69.28 ± 1.97
Ash | 8.07 ± 0.01 | 9.50 ± 0.31 | 6.27 ± 0.10
Fixed carbon | 20.14 ± 0.13 | 23.73 ± 0.56 | 24.46 ± 1.75

calculated based on dry CS sample
estimated uncertainty based on ASTM C136 fine aggregate multilaboratory precision data
Literature indicates that cacao shell (CS) properties, including mean particle size, volatile matter , ash content ( ), and fixed carbon ( ), can vary depending on processing conditions Table 4 [32,42]. Variations in mean particle size are primarily attributed to the milling frequency of the CS. However, the volatile matter, ash, and fixed carbon content obtained in this study were consistent with reported values, suggesting that cacao shells maintain these inherent properties regardless of their geographic origin. This consistency implies that cacao shells can be reliably sourced from any location in the Philippines for producing cacao shell solid acid catalyst (CS-SAC), provided that the shells are milled to a uniform particle size to ensure catalyst consistency, which is particularly important given the variability in shell characteristics from different small-to-medium-sized cacao processors in the country [77].

Fixed carbon content is a critical parameter for biomass-based solid acid catalysts, as it determines the carbon framework available for attaching catalytic acidic functional groups. During simultaneous carbonization-sulfonation, volatile components are removed, and some ash is dissolved in sulfuric acid, leaving behind the fixed carbon, which serves as the catalyst support. The fixed carbon content of the CS used in this study was slightly lower than those reported by Mendaros (2020) [32] and Bureros et al. (2018) [42], indicating that a relatively lower amount of catalyst may be produced. However, it remained within the range reported for other biomass sources ( ) [32].

To evaluate catalytic performance, unused CS-SAC samples were synthesized in batches, homogenized, and analyzed for total acid density (TAD). For comparison, the TAD of Amberlyst-15, a commercial solid acid catalyst, was also measured. TAD analysis at two agitation times ( 3.5 h and for Amberlyst-15 showed minimal differences ( catalyst), indicating that 3.5 hours was sufficient for accurate TAD measurement while saving time.

Unused CS-SAC was found to have a TAD of cat while unused Amberlyst-15 was found to have a TAD of cat. As shown in Table 5 and relating to literature the obtained TADs of CS-SAC and Amberlyst-15 are not similar as they are different catalyst types. Interestingly, it can be seen that the TAD of CS-SAC in this study compared to Mendaros et al. (2018) [32] are far apart in values. This could be attributed to differences in CS mean particle size. The mean particle size in the study by Mendaros et al. (2018) [32] was smaller than in this study ( 93.15 vs. ) - this implies a higher surface area available for more mass transfer of acidic functional groups, allowing for even more functionalization with carboxylic, phenolic, and sulfonic acid groups during catalyst synthesis. Since a lower TAD was measured for the catalyst synthesized in this study, this would imply a lower amount of active acid groups present in the catalyst structure and also lower FFA conversions compared to previous studies. However, an opposite trend was observed due to our study using COFAD as feedstock which is mainly composed of lauric acid which is a shorter fatty acid chain than oleic acid by Mendaros et al (2018) [32].

Table 5. TAD of catalyst samples

Study | TAD (mmol H+/g cat)
| CS-SAC | Amberlyst-15
This studya | 2.701 ± 0.053 | 2.434 ± 0.057
Mendaros et al. (2018)b [32] | 7.12 | -

agitation time of 24 hrs for CS-SAC used
RSM-CCD for factor screening. As discussed, the ranges of methanol-to-COFAD ratio and catalyst loading utilized in previous studies [32,39-42,44,45,47] involving biomass-based catalysts were used as bases for the design of experiment. RSM-CCD was chosen as the design of experiment, and with the aid of Design-Expert 13 software, thirteen experimental runs were generated. Esterification of COFAD was then performed following the experimental runs to obtain the %FFA conversion response variable. Regression analysis was then conducted using the gathered data to obtain a mathematical model that sufficiently describes the relationship between independent variables (methanol-to-COFAD molar ratio and catalyst loading) and the dependent or response variable (FFA conversion).

RSM-CCD for factor screening: Response surface modeling. The methanol-to-COFAD ratio, catalyst loading, and FFA conversion were used to make the 3D response surface as presented (Figure 1). As seen in Figure 1, the highest conversion within the investigated parameter range was obtained with Run 1 conditions ( COFAD). This is likely due to Run 1 having the highest parameter values (coded values of ) excluding the axial value (coded value of ). It was also found that for Run COFAD) which utilized a catalyst loading of , no conversion was observed implying that the amount of catalyst was too little to be able to convert FFA to FAME. An FFA conversion of around 0.60 can already be deemed high compared to the study of Mendaros et al. (2020) [32] that also utilized directly sulfonated cacao shells in the conversion of oleic acid with the esterification conditions of oleic acid, , and 4 hours which resulted in an FFA conversion of around 0.39 . Considering that the highest FFA conversion of 0.60 was obtained in the initial stages of the esterification reaction (reaction time of 2 hours) and at the maximum parameter ranges investigated, increasing the factors above the studied ranges can still potentially increase the FFA conversion.

Fig. 1. 3D Response Surface Plot of (A) MeOH:COFAD Molar Ratio and (B) Catalyst Loading versus Conversion with the predicted highest conversion (0.6012) and its parameters (16.9, 0.42).

Fig. 1. 3D Response Surface Plot of (A) MeOH:COFAD Molar Ratio and (B) Catalyst Loading versus Conversion with the predicted highest conversion (0.6012) and its parameters (16.9, 0.42).

Upon performing response surface modeling and regression analysis, the model terms were evaluated on their influence on the response variable. In the case of this study, both the AB and terms were considered not significant and was excluded since both have high P -values ( ). Runs 2 and 12 were also not included in the dataset to improve the fit statistics of the model. The summary of the ANOVA results is shown in Table 6.

Table 6. Analysis of Variance (ANOVA) for the response surface regression using a reduced quadratic model

Source | Sum of Squares | df | Mean Square | F-value | P-value | Remarks
Model | 0.1577 | 3 | 0.0526 | 200.37 | <0.0001 | significant
A – Methanol-to-COFAD Ratio | 0.0609 | 1 | 0.0609 | 232.21 | <0.0001 |
B – Catalyst Loading | 0.0427 | 1 | 0.0427 | 162.83 | <0.0001 |
A² | 0.0147 | 1 | 0.0147 | 55.86 | 0.0001 |
Residual | 0.0018 | 7 | 0.0003 |  |  |
Lack of Fit | 0.0013 | 3 | 0.0004 | 2.90 | 0.1648 | not significant
Pure Error | 0.0006 | 4 | 0.0001 |  |  |
Cor. Total | 0.1595 | 10 |  |  |  |

As shown in Table 6, the chosen model (reduced quadratic model) has an F-value of 200.37 and a P -value less than 0.0001 which signifies that the chosen parameters have a significant impact on the response variable. It was also found that both the methanol-to-COFAD ratio (A) and catalyst loading (B) have both influenced the FFA conversion, as seen in their F-values of 232.21 ( P -value ) and -value , respectively. Additionally, the model's Lack of Fit has a low F -value of 2.90 and a P -value greater than 0.05 which indicates that the Lack of Fit was not significant relative to the pure error. Having a not significant Lack of Fit is desirable because it implies that the data gathered fits the model well. It can then be concluded that a reduced quadratic model can be used to accurately predict the conversion response variable. The final polynomial equation (Equation 14) representing the relationship between the methanol-to-COFAD ratio (A), catalyst loading (B), and FFA conversion (Y) is shown below.

The fit statistics (Table 7) gives insight on the validity of the model obtained. The resulting model equation has an value of 0.9885 which implies that there is a very good correlation between the independent (methanol-to-COFAD molar ratio and catalyst loading) and the dependent (FFA conversion) variables. Moreover, the adjusted value of 0.9836 is a very good indication that the terms in the model equation are adequate in defining the effect of methanol-to-COFAD molar ratio and catalyst loading to FFA conversion in the researched parameter range. Furthermore, the predicted of 0.9560 is in reasonable agreement with the adjusted where the difference between the two is less than 0.2 . This means that the statistical model is not overfitting the data gathered, and that the regression model is satisfactory in predicting the response for new observations. Finally, the adequate precision value measures the signal to noise ratio. The adequate precision value of 40.6082 indicates an adequate signal ( is desirable) and that the regressed model is suitable for navigating the design space [66].

Table 7. Fit statistics of the model

Statistic | Value
R² | 0.9885
Adjusted R² | 0.9836
Predicted R² | 0.9560
Adequate Precision | 40.6082

Using RSM for optimization provides benefits such as offering a significant amount of information based on a small amount of experimental data and being able to observe any interactions between the independent variables. However, working on a narrow range can cause difficulty in determining the stationary points of the model [67]. Fortunately, the range of the catalyst loading studied ( 0.07 to 0.42 COFAD or 2.59 to of COFAD) has a similar size to the range of methanol-to-COFAD ratio ( 6.4 to ) which leads to both parameters exerting influence on the magnitude of the FFA conversion.

RSM-CCD for factor screening: Main and interaction effects. As shown in Equation 14, the linear model terms A and B , and the quadratic term are the ones responsible for predicting the extent of conversion. On the other hand, the interactions between the methanol-to-COFAD ratio and catalyst loading (A-B) along with the interactions of catalyst loading and itself ( ) have no substantial effect on the conversion.

Since the rate of reaction is directly proportional to the reactant concentration, then the FFA conversion is expected to increase with increasing methanol-to-COFAD molar ratio. Thus, the reaction is accelerated by adding more methanol, resulting in the production of FAMEs and the considerable reduction of FFAs [78]. This can be supported by the positive coefficient in the linear term . However, since the squared term has a negative coefficient ( -0.001717 ), this means that further increasing the methanol-to-COFAD ratio causes the conversion to drop. In Figure

2A, it can be observed that the plot of the methanol-to-COFAD molar ratio versus FFA conversion starts to plateau with increasing molar ratio and it can be deduced that further increasing the parameter beyond the studied range will lead to the FFA conversion to peak and then decrease. The decrease in FFA conversion may be caused by the effects brought upon by dilution of oil [57]. As the methanol-to-COFAD ratio increases, the concentration of COFAD in the reaction mixture decreases, thereby affecting the rate of reaction and conversion.

The FFA conversion is also expected to increase with increasing catalyst loading. More catalyst in the reaction mixture would suggest that there are more ion active sites available for the esterification reaction to proceed more quickly, turning more FFAs into FAME. This can be explained by the positive coefficient in the linear term B ( 0.583458 ). The result in this study shows that there is a linear relationship between catalyst loading and conversion as seen in Figure 2B. However, the OVAT study of Malila (2020) [18] on the relationship between catalyst loading and FFA conversion at a range of 0.5 to exhibited that there is a point where further increasing the catalyst loading has insignificant changes to FFA conversion. The stagnation of FFA conversion may have been caused by the reaction reaching an equilibrium [58]. This implies that the linear relationship of catalyst loading and FFA conversion is only applicable within the range used in this study which is 0.07 to COFAD.

Fig. 2. Plot of (A) MeOH:COFAD Molar Ratio ( ) and (B) Catalyst Loading (mmol COFAD) versus FFA Conversion

Fig. 2. Plot of (A) MeOH:COFAD Molar Ratio ( ) and (B) Catalyst Loading (mmol COFAD) versus FFA Conversion

Reusability study. One advantage of using solid acid catalysts such as CS-SAC is the ease of recovery and reusability. Thus, the ability of the synthesized CS-SAC to convert FFA into FAME for four cycles was investigated. In each cycle, the reaction was made to proceed for 24 hours instead of only two hours. This was done to ensure that the highest possible conversion was achieved in each cycle. A study performed by Flores et al (2019) [40] shows that FFA conversion increases over time. However, beyond 24 hours of reaction is not practical for industrial applications as the reaction will have achieved equilibrium conversion beyond this point. Thus, a reaction time of 24 hours was used in the reusability study.

In every cycle, the FFA conversion and %retention were determined. The catalyst was recovered, washed with hexane, dried in the fume hood for 3-4 hours, then dried in the oven set to for 1216 hours. Although most of the washing used for recovery is methanol , hexane was used instead in this study since it is non-polar. A study conducted by Mo et al., (2008) [51] shows that methanol has a tendency of attracting the polar acid groups ( , and -OH ) attached in the CS-SAC due to its polarity thereby causing leaching. Since hexane is non-polar, it causes a lower degree of leaching during washing [39]. The FFA conversion and %retention in the four cycles are presented in Figure 3.

Fig. 3. Reusability study of CS-SAC sulfonated at for 6 hours (Esterification conditions: , catalyst loading COFAD, methanol-to-COFAD molar ratio = 16.9). Error bars represent standard deviations of duplicate runs. %Retention cycle cylce . TAD is the unused catalyst total acid density while TAD is the catalyst total acid density after the last cycle.

Fig. 3. Reusability study of CS-SAC sulfonated at for 6 hours (Esterification conditions: , catalyst loading COFAD, methanol-to-COFAD molar ratio = 16.9). Error bars represent standard deviations of duplicate runs. %Retention cycle cylce . TAD is the unused catalyst total acid density while TAD is the catalyst total acid density after the last cycle.

The FFA conversion obtained using the unused catalyst (recycle 0 ) is 0.98 . After every cycle, the conversion tends to decrease, resulting in a diminishing trend of %retention. The final FFA conversion after four cycles ( 3 recycles) is 0.89 which coincides to a %retention of . This trend can be attributed to the decrease in active sites in the catalyst imparted during the carbonizationsulfonation of the cacao shells. These active sites are represented by the total acid density of the CSSAC. As such, the change of total acid density of the catalyst before and after the four cycles was monitored. Results show a decrease in total acid density from cat to 2.501 cat. The decrease in total acid density may be caused by several factors, one of which is the leaching of the active sites which occurs prior to recovery since the reaction mixture contains polar methanol and water molecules. There is a tendency that the polar acid groups will dissolve into the reaction mixture since polar compounds dissolve in polar solvents. Another cause is the formation of sulfonate esters caused by the reaction of the group with excess methanol [45]. This leads to catalyst poisoning which renders the sulfonic active sites inactive. Clogging of pores by the reactants or products in the reaction mixture may also hinder the active sites and lower the activity of CS-SAC. Although washing with hexane was done prior to reuse, there were no means of determining its efficiency. Finally, changes in the structure of the catalyst as it is being reused may have reduced the number of its active sites.

Another observation is that the FFA conversion did not stabilize to a certain value and only decreased continuously in the four cycles. Results obtained from [32,40,42] which also uses carbonbased solid acid catalysts show negligible changes in conversion after four to five cycles. This is attributed to the fact that the total acid density of the catalyst has also stabilized at this point. What this implies in the current study is that additional cycles must have been done to determine the point of stabilization of the synthesized CS-SAC.

Comparison of heterogeneous catalyst performance in fatty acid esterification. The catalyst synthesized in this study was compared with literature in terms of its characteristics and esterification performance. Comparison provides information on the effectivity of the produced catalyst with respect to other CS-SAC and the more popular Amberlyst-15 catalyst. Details of the comparison is discussed in the succeeding subsections.

Comparison of heterogeneous catalyst performance in fatty acid esterification: Comparison of CS-SAC. Presented in Table 8 are several studies using CS-SAC for FFA conversion. Among the CS-SACs used in the reusability studies, this study has the highest %retention. This implies that the catalyst in this study is still able to convert high fractions of FFA despite being reused many times, showing its practicality of being used as a catalyst. The high %retention in this study can be attributed to using n -hexane as the washing solvent as compared to the other studies which used methanol; using hexane for washing reduces the tendency for leaching of the active sites. Moreover, the synthesized CS-SAC in this study has the lowest total acid density among the three studies presented in Table 8. Mendaros et al. (2020) [32] synthesized a CS-SAC with a TAD of catalyst. On the other hand, this study created a CS-SAC with a TAD of only catalyst despite having the same synthesis conditions as that of Mendaros et al. (2020). As discussed previously, this is due to the inverse relationship between the TAD and mean particle size.

However, higher TAD does not always result to higher FFA conversion rates. Instead, the sulfonic acid density which corresponds to the sulfonic acid sites per gram of catalyst has a bigger impact on FFA conversion. Literature [79,80] shows that the sulfonic group ( ) greatly increases the hydrophilicity of the catalyst as compared to the weak acid sites such as the carboxylic (- COOH ) and phenolic groups, allowing more of the hydrophilic methanol to enter the carbon catalyst bulk and react with the free fatty acids during esterification. The attachment of these acid sites can be affected by the carbon precursor morphology specifically on the size and number of pores [81]; a higher number of pores provides more avenues for acid sites to attach into the carbon source. This may also explain the high TAD values of Bureros et al. (2019) [42] and Mendaros et al. (2020) [32]. However, only larger pore sizes allows for better accessibility of sulfuric acid into the carbon bulk, leading to the formation of more . The catalyst synthesized in this study may have a larger pore size despite having a smaller surface area and TAD value, thus having a higher sulfonic acid density and FFA conversion rates. Moreover, the catalyst pore size and substrate size also contributes to the mass transfer of the substrate into the inner surface of the catalyst during esterification [81]. Since this study uses COFAD as a feedstock which is mainly composed of lauric acid, a fatty acid with a shorter chain compared to the oleic acid feedstock used by Bureros et al. (2019) and Mendaros et al. (2020), it is easier for the FFA molecules of COFAD to enter into the catalyst surface thereby increasing the esterification rate. The higher FFA conversion in this study may also be attributed to higher methanol-to-oil ratio and catalyst loading since increasing these two factors will likely increase the rate of conversion as discussed in the previous sub-section.

Table 8. Comparison of CS-SAC and Amberlyst-15

Catalyst | Feedstock | Optimum Synthesis Conditions | Esterification Reaction Conditions | Total Acid Density(mmol H+/g) | Conversion | Cycles | Washing | % Retention | References
|  | Carbonization | Sulfonation | Type of Alcohol Alcohol:Feed (mol/ mol) | Catalyst Loading (mmol H⁺/g oil) | T (°C) | t (h) |  |  |  |  |  |
|  | T (°C) | t (h) | T (°C) | t (h) |  |  |  |  |  |  |  |  |  |
Cacao Shell | Oleic acid | 400 | 1 | 120 | 4 | Methanol 7:1 | 0.22 | 42 | 24 | 4.41a (2.60)b | 0.93c (0.48)d | 5 | methanol | 51.61 | [42]
Cacao Shell | Oleic acid | N/A | N/A | 120 | 6 | Methanol 7:1 | 0.50 | 65 | 24 | 7.12 (6.50) | 0.77 (0.60) | 5 | methanol | 77.92 | [32]
Cacao Shell | COFAD | N/A | N/A | 120 | 6 | Methanol 16.9:1 | 0.42 | 60 | 24 | 2.701 (2.501) | 0.98 (0.89) | 4 | hexane | 90.25 | This study
Cacao Shell | COFAD | N/A | N/A | 120 | 6 | Methanol 16.9:1 | 0.42 | 60 | 2 | 2.701 | 0.60 | 1 | none | N/A | This study
Amberlyst 15 | COFAD | N/A | N/A | N/A | N/A | Methanol 16.9:1 | 0.42 | 60 | 2 | 2.408 | 0.78 | 1 | none | N/A | This study

Comparison of heterogeneous catalyst performance in fatty acid esterification: Comparison of COFAD esterification performance between CS-SAC and Amberlyst-15. Upon comparing with a commercially available solid acid catalyst used for esterification such as Amberlyst 15, the FFA conversion using CS-SAC as catalyst is lower compared to using Amberlyst-15 even though the CS-SAC used has a higher TAD than Amberlyst-15 as seen in Figure 4. This may be attributed to Amberlyst-15 having functionalized by only the strong functional group [82] as compared to carbon-based catalysts which can be functionalized by weak - COOH and - OH groups during the carbonization-sulfonation process. For instance, in the studies of Mendaros, et al. (2020) [32] and Bureros, et al. (2019) [42], the main contributors for the total acid density of their synthesized CSSAC are the weak - COOH and - OH groups with respect to the structural analysis of the synsthesized CS-SACs.

Fig. 4. Comparison of CS-SAC and Amberlyst 15 in the esterification of COFAD (Esterification conditions: , catalyst loading oil, methanol-to-oil molar ratio 16.9)

Fig. 4. Comparison of CS-SAC and Amberlyst 15 in the esterification of COFAD (Esterification conditions: , catalyst loading oil, methanol-to-oil molar ratio 16.9)

Conclusions and Recommendations

The original version of this paper is available on https://www.scientific.net/EC.12.73.pdf

This study examined the combined effects of the methanol-to-COFAD ratio and catalyst loading on the heterogeneous esterification of COFAD using directly sulfonated cacao shell as a solid acid catalyst, under constant reaction time, temperature, and pressure. Within the tested parameter range (methanol-to-COFAD ratio of and catalyst loading of 0.07 to COFAD or 2.59 to of COFAD), an increase in the methanol-to-COFAD ratio initially enhanced FFA conversion. However, beyond a certain point, further increases in methanol concentration led to reduced conversion due to reaction mixture dilution. For catalyst loading, a direct positive correlation with FFA conversion was observed across the tested range. This linear relationship suggests that the catalyst loading level used in this study is still below the point where conversion plateaus. Prior studies indicate that this plateau is typically reached when excess catalyst leads to more water formation and the reaction approaches equilibrium. As such, catalyst loadings beyond the of COFAD adopted in this should be explored to determine the FFA conversion inflection point.

The highest FFA conversion ( 0.604 ) was achieved at the upper limits of the studied parameters, suggesting that further extending these ranges could further increase conversion. Reusability tests conducted under these conditions showed that the catalyst retained of its initial activity after four cycles (three recycles), demonstrating excellent stability. Given this high retention, future studies are encouraged to investigate the reusability of CS-SAC for more than four cycles when processing COFAD.

Given its excellent stability and significant FFA conversion ( retention after four cycles), directly sulfonated cacao shell (CS-SAC) shows strong potential for use in industrial heterogeneous esterification of COFAD. Future research is recommended to explore the effects of reaction parameters-specifically the methanol-to-COFAD ratio and catalyst loading-beyond the tested range to identify optimal conditions. Additionally, conducting a catalyst morphological study on CSSAC is advised to better understand the relationship between catalyst active sites and FFA conversion.

Acknowledgements

The original version of this paper is available on https://www.scientific.net/EC.12.73.pdf

The authors would like to acknowledge and thank for the financial support provided by the Department of Science and Technology - Science Education Institute (DOST-SEI) for the 2018 DOST-SEI undergraduate scholarship thesis subsidy grant as well as the support from the paper publication incentive used for the undertaking of this research.

Appendix A. Research Flow Diagrams

The original version of this paper is available on https://www.scientific.net/EC.12.73.pdf

Fig. 5. Research Design Flow Diagram Part A

Fig. 5. Research Design Flow Diagram Part A

Fig. 6. Research Design Flow Diagram Part B

Fig. 6. Research Design Flow Diagram Part B

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Fresh total acid density
Total acid density after last recycle
Conversion using fresh catalyst
Conversion in the last cycle
e%Retention in the last cycle

Keywords Index

A

Acid-catalyzed Esterification Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

Activated Carbon Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Adsorption Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

B

Biodegradable Wastes Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

Biodiesel Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

C

Cement Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Chemical Bonding Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Co-digestion Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

Coconut Oil Fatty Acid Distillate Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

Coconut Oil Fatty Acid Distillate (cofad/cfad) Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

D

Delonix Regia Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Directly Sulfonated Cacao Shell Solid Acid Catalyst Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

F

Fatty Acid Methyl Esters Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

Flamboyant Tree Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

K

Kinetics Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

M

Magnetite Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Mixture Design Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

N

Nanoparticle Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

P

Polymer Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Q

Quadratic Model; Optimization Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

R

Remediation Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Response Surface Methodology - Central Composite Design (rsm-ccd) Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

Reusability Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

T

Thermodynamics Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

Total Petroleum Hydrocarbon Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Authors Index

A

Adekanmi, D. Characterization and Kinetic Analysis of Activated Flamboyant Tree Pod (Delonix regia) Biochar for Crude Oil-Contaminated Water Treatment

Ajala, O. Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

B

Babanto, J. Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

C

Cabo, J. Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

Catarig, K. Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

G

Gulamirov, A. Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Guliyeva, J. Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

H

Humbetova, S. Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

I

Ibrahim, T. Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

L

Legarde, C. Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis

M

Malikov, E. Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

Malila, J. Esterification of Coconut Fatty Acid Distillate (COFAD) Using Hydrochloric Acid as Homogeneous Acid Catalyst: A Kinetic and Thermodynamic Analysis; Heterogeneous Esterification of Coconut Oil Fatty Acid Distillates (COFAD) Using Directly Sulfonated Cacao Shells

Mammadova, S. Metal Nanoparticles and Polymer Incorporated Cement Rock. The Role of Magnetite Nanoparticles in the Mechanical and Bonding Behavior of Portland Cement in Structuring: A Short Review

O

Odejobi, O. Modelling and Optimization of Biogas Production from Co-Digestion of Cassava Vinasse with other Biodegradation Wastes

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