Engineering Chemistry Volume 11

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Volume 11 of
Engineering Chemistry

ISSN print 2813-6527
ISSN web 2813-6535

Full text available online at https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

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Table of Contents

Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

Ismawati Putri, Isnaeni Isnaeni, Mochamad Zainuri, Widyastuti Widyastuti

Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Ayodunmomi Esther Olowofoyeku, Ademola Kabiru Aremu, Abel Olajide Olorunnisola

Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

I. Gusti Ayu Agung Istri Dwi Jovanca Devi, Andhika Fathurrohman, Alfa Rizky, Firyal Lutfi Fauziah, Muhammad Ezra Bena, Hikmatun Ni'mah, Fahimah Martak

Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

Innocentia G. Mkhize, Ephraim Igberase

Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

Dina Rika Silviana, Dylia Rahmadyanti, Retno Asih, Haniffudin Nurdiansah, Mochamad Zainuri, Darminto Darminto

Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Faried Latief, Putri Istichomah, Bagas Haqi Arrosyid, Ratih Amalia, Muhammad Fahroji, Trivadila Trivadila, Akmal Zulfi, Andika Fajar, Andika Widya Pramono, Alfian Noviyanto

Keywords Index

Authors Index

The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 1-6

doi: 10.4028/p-esjRg1

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

Submitted:
2024-12-15

Revised:
2025-03-18

Accepted:
2025-05-05

Online:
2025-09-10

Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

Ismawati Putri , Isnaeni , Mochamad Zainuri and Widyastuti

Department of Materials and Metallurgical Engineering, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia

Research Center for Photonics, National Research and Innovation Agency, Tangerang Selatan, Indonesia

Department of Physics, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia

puputisma98@gmail.com, isnaeni@brin.go.id (corresponding author), zainuri@physics.its.ac.id, wiwid@mat-eng.its.ac.id

Keywords: Carbon Dots, Environmental Remediation, Oil absorption, and Oil-spill

Abstract

Marine oil spills negatively impact human health and aquatic ecosystems, causing biodiversity loss and reduce water quality. A range of mechanical, chemical, and biological methods have been employed to address oil spills in marine environments. As science and technology advance, there is a high demand for affordable and effective oil-absorbing materials. Oil absorbers using sponges with solar heat can be a solution to overcome the problem of oil spills at low cost and can be recycled. In this study, we combined the sponge with carbon dots from graphite pencils to improve the sponge's ability to absorb oil. The electrochemical method successfully synthesized carbon dots with particle sizes ranging from 1 to 5 nm . UV-Vis absorption, photoluminescence intensity, and FTIR spectra have revealed transition energies, peak intensities, and functional groups characteristic of carbon dots, respectively. We used sponges with and without carbon dots to compare their performance in absorbing oils. In addition, we also compared sponge performance when exposed to temperatures of 60 to . Sponges with carbon dots have high absorbency. The absorbency of the sponge increases by when combined with a carbon dot. A higher temperature can also increase the absorbency of the sponge.

Introduction

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

Oil spills are one of the main causes of marine water pollution. Oil spills in the ocean negatively impact human health and aquatic ecosystems, as well as loss of biodiversity and reduced water quality [1]. Efforts to effectively clean up oil spills are necessary to prevent harm to the public and preserve the environment's health. Several methods have been used to overcome the problem of marine oil spills, including skimmers [2], oil dispersants [3], biodegradation and in situ burning [4]. However, these methods are expensive, time consuming and cause secondary pollution. With the development of science and technology, there is great demand for low-cost and efficient oil-absorbent materials. Oil absorbers using sponges that utilize solar heat can be a solution to overcome the problem of oil spills at a low cost and can be recycled.

Sponge are porous materials that can be used as oil absorbers. To increase the absorbency, we combined the sponges with carbon dots. Carbon dots are zero-dimensional nanomaterials with a particle size of less than 10 nm [5]. Carbon dots were initially discovered in 2004 while purifying single-walled carbon nanotubes [6-8]. Carbon dots have good optical properties [9], non-toxicity [5], biocompatibility [10], good chemical stability and low cost [7]. Carbon dots can be synthesized from materials containing carbon elements. Their unique properties make them widely used as photocatalysts [11], solar cells [12], drug delivery [13], sensor and oil-absorbing material [1, 14].

Sunlight oil absorption is a promising method for increasing the absorbency of sponges. Sunlight lowers the oil's viscosity, allowing the sponge to absorb the oil easily [1]. Previous studies have shown the outstanding performance of carbon dots conjugated with several types of sponges to absorb water and oil [15]. Polyvinyl alcohol sponges have better absorbency than other sponges. Therefore,
we combined the polyvinyl alcohol sponges with carbon dots derived from pencil graphite. This research aims to increase the absorbency of sponges combined with carbon dots to absorb oil. Besides, we used a halogen lamp as an irradiation source.

Methods

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Carbon dots were made from 2B pencil graphite using a simple electrochemical process. Two graphite pencils were used as anode and cathode electrodes for the electrochemical process. The electrolyte solvent was 0.5 sodium hydroxide mixed with 100 ml of ethanol. The electrodes were connected to a 45 mA DC power supply for 2 hours. The solution was kept at room temperature for 24 hours until a brown solution appeared. The appearance of a brown color indicates that the carbon dots were successfully synthesized.

We made a sponge with a thickness of 0.5 cm . The sponge used is polyvinyl alcohol from local distributor and engine oil from shell HX6. The sponge was manually dipped in the carbon dots solution and dried for 24 hours at room temperature. We tested each sponge's oil absorption (with and without carbon dots). We put 3 ml of oil in a glass with 30 ml of seawater. Then, manually dip a sponge into the glass until all sponge parts are submerged. We measured the mass of the sponge after and before dipping to determine the absorbency of the sponge based on the following equation.

is the mass of the sponge before dipping, and is the mass of the sponge after dipping. We tested the absorbency of the sponge with carbon dots when irradiated with a halogen lamp. The halogen lamp was placed 30 cm from the sample. Then the absorbency results with and without irradiation were compared. In addition, we characterize the synthesized carbon dots using UV-Vis absorbance, photoluminescence, fourier transform infrared spectroscopy (FTIR) and transmission electron microscope (TEM).

Results and Discussion

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

Carbon dots have been successfully synthesized from 2B pencil graphite using a simple electrochemical method. The brown color indicates that the carbon dots have been successfully synthesized. In addition, we perform various characterizations such as UV-Vis, photoluminescence, FTIR and TEM. The UV-Vis absorption spectrum (Fig. 1a) shows that carbon dots exhibit two peaks at 263 and 364 nm . The first peak is thought to represent the energy transition at the core of the carbon dots. Meanwhile, the second peak is assumed to be the carbon dots peak’ energy transition. These two transition peaks are characteristic of carbon dots [16]. Photoluminescence characterization was performed, and the characterization result (Fig. 1b) shows that carbon dots have the highest luminescence intensity at a wavelength of 527 nm when excited using a laser diode with a wavelength of 420 nm .

Fig. 1. Absorption spectrum of carbon dots (a) and photolinescence spectrum (b) of carbon dots

Fig. 1. Absorption spectrum of carbon dots (a) and photolinescence spectrum (b) of carbon dots

We performed FTIR characterization to determine the functional groups of carbon dots. FTIR characterization results show that carbon dots have the same peaks as ethanol, except for three peaks (Fig. 2a). and stretching vibrations that were detected at wave numbers 3317, 1740 and respectively [17]. These three functional groups originated from the surface of carbon dots. Additionally, we conducted TEM characterization to determine the size and morphology of carbon dots. Carbon dots were quasi-spherical in shape with uniform particle size and distributed from 1 nm to 5 nm . The dominant particle size of carbon dots is 3 nm (Fig. 2b). This size is consistent with previous research indicating that carbon dots have a particle size of less than 10 nm [18]. Since the carbon dots are small (less than 5 nm ), the synthesized carbon dots can be called carbon quantum dots [15].

Fig. 2. FTIR spectra of carbon dots and ethanol (a) and TEM image of carbon dots (b)

Fig. 2. FTIR spectra of carbon dots and ethanol (a) and TEM image of carbon dots (b)

The next phase of this research involved testing the absorbency of sponges with and without carbon dots. The sponges combined with carbon dots turned brown (Fig. 3). Next, the sponge is used to test the oil absorbency. We dipped the sponge in a glass filled with sea water and oil, and let it soak for 10 minutes at room temperature. The absorbency of sponge is calculated using Equation 1 to determine the performance of the sponge in absorbing oil.

Fig. 3. Sponges image with and without carbon dots

Fig. 3. Sponges image with and without carbon dots

This research results show that sponges with carbon dots have a greater absorbency than sponges without carbon dots (Fig. 4a). The research was conducted at room temperature with normal light from a ceiling lamp. The first and second experiments showed increased absorbency of sponges with carbon dots. Meanwhile, the third experiment showed that the sponge without carbon dots had higher absorbency. The sponge without carbon dots had a higher absorbency than the sponge with carbon dots, it is thought to be due to the difference in the initial mass of the sponge and the low amount of carbon dots conjugated in the sponge. In addition, we tested the absorbency using halogen lamp irradiation (temperature at ). Sponge with carbon dots compared their absorbency when irradiation and non-irradiation. Sponge increased absorbency when given irradiation (Fig. 3b). The absorbency of sponges increased by 5.4 to under the influence of the irradiation process. The irradiation process can increase the surface polarity of sponge, so that it easily absorbs oil. Furthermore, the irradiation process can help decrease the oil's viscosity so that it is easily absorbed into the sponge.

In this study, we evaluated the effectiveness of sponges infused with carbon dots for absorbing oil (Fig.4c). The results indicate a progressive decline in absorbency with repeated use, suggesting that several factors contribute to this degradation. One primary factor is structural damage to the sponges' porous. Over time, repeated exposure to oil, mechanical stress during use, and irradiation may cause compression, collapse, or fragmentation of the pores, reducing the available surface area for absorption. Additionally, the loss of carbon dots embedded within the sponge matrix could significantly impact its performance. Carbon dots are known for their ability to enhance surface wettability and interaction with hydrophobic substances, so their depletion may lead to reduced oil affinity. Furthermore, degradation of the sponge material itself is another critical consideration. Prolonged exposure to oil, grease, and irradiation could alter the chemical and physical properties of the polymeric structure, leading to embrittlement, swelling, or oxidative degradation. These changes may not only weaken the sponge but also alter its oil-absorbing capability. Lastly, surface modifications induced by irradiation may also play a role. Irradiation can lead to crosslinking, oxidation, or surface roughness changes, which might influence the sponge's interaction with oil molecules. Depending on the irradiation type and intensity, it may cause beneficial modifications initially but contribute to long-term deterioration of the material's effectiveness. Future work could explore strategies to improve the durability of such sponges, such as optimizing carbon dot adhesion, enhancing the stability of the sponge matrix, or developing protective coatings to minimize structural degradation. Investigating alternative irradiation methods or lower-energy treatments may also help in maintaining sponge performance over extended use cycles.

Fig. 4. Absorbency of sponges with and without carbon dots (a), absorbency of sponge when given irradiation and non-irraditation process (b), and the effectiveness of sponge in absorbing oil

Fig. 4. Absorbency of sponges with and without carbon dots (a), absorbency of sponge when given irradiation and non-irraditation process (b), and the effectiveness of sponge in absorbing oil

Summary

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

Carbon dots have been successfully synthesized from 2B pencil graphite using a simple electrochemical method. The results of UV-Vis, photoluminescence, FTIR and TEM show that carbon dots have been synthesized. The particle size of carbon dots ranged from 1 to 5 nm . Carbon dots conjugated into the sponge can increase the absorbency up to . The irradiation process can help the sponge to increase its absorbency. Sponge with carbon dots showed a decrease in absorbency with repeated use. Separating oil using a sponge with carbon dots is simple, low-cost and time consuming. However, for broader practical applications, future research should explore several key areas such as testing the sponge's performance with different types of oils and assessing the sponge's durability and absorbency under real-world spill conditions. Further studies could also investigate strategies to enhance sponge longevity, such as optimizing carbon dot adhesion, using more resilient sponge materials, or incorporating protective coatings.

Acknowledgment

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

All experiments were conducted in the Research Center for Photonics BRIN with characterization tools fully facilitated by BRIN's e-Science Service (ELSA).

References

The original version of this paper is available on https://www.scientific.net/EC.11.1.pdf

S. Singh and R. Jelinek, "Solar-mediated oil-spill cleanup by a carbon dot-polyurethane sponge," Carbon N. Y., vol. 160, pp. 196-203, 2020.

M. \DJor\djević, \DJani Šabalja, \DJani Mohović, and D. Brčić, "Optimisation methodology for skimmer device selection for removal of the marine oil pollution," J. Mar. Sci. Eng., vol. 10, no. 7, p. 925, 2022.

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Y. Guan, D. Qiao, L. Dong, X. Chen, Z. Wang, and Y. Li, "Efficient recovery of highly viscous crude oil spill by superhydrophobic ocean biomass-based aerogel assisted with solar energy," Chem. Eng. J., vol. 467, p. 143532, 2023.

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D. Sawitri, N. Nurfathiya, A. Fauzan'Adziimaa, and others, "Synthesis of carbon dots from organic waste as heavy metal ions detector sensor," in Third International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2018), 2019, vol. 11044, pp. 155-161.

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This ePub file was created using machine-generated methods and automated software to convert the source text into an ePub format and may contain formatting inconsistencies from the original version. Formatting may vary depending on the device used.

The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 7-23

doi: 10.4028/p-xbw7Qg

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

Submitted:
2025-03-24

Revised:
2025-04-24

Accepted:
2025-05-08

Online:
2025-09-10

Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

The original version of this paper is available on https://www.scientific.net/EC.11.7.pdf

Ayodunmomi Esther Olowofoyeku , Ademola Kabiru Aremu , Abel Olajide Olorunnisola

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

Department of Agriculture and Environmental Engineering, University of Ibadan, Ibadan, Nigeria.

Department of Wood Products Engineering, University of Ibadan, Ibadan, Nigeria.

ayoolowo1122@gmail.com, ademolaomooroye@gmail.com, abelolorunnisola@yahoo.com Corresponding author: ayoolowo1122@gmail.com

Keywords: Photoluminescent polymers, porous composites, calcium carbonate, oleic acid, citric acid, oil contaminant.

Abstract

Oil contamination from petroleum hydrocarbons and other sources poses significant environmental and health risks due to its persistence and toxicity. This study developed polyethylenecalcium carbonate (PE-CC) composites with tailored structural and surface properties to enhance oil adsorption. The composites were fabricated through melt blending ( ), with the calcium carbonate (CC) filler first modified using oleic acid (OA) (0, 0.5, and ) to improve hydrophobicity and dispersion, followed by citric acid ( 1 M ) treatment of the composites to induce porosity and optimize oil adsorption. X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) confirmed successful surface modification of CC, as evidenced by reduced diffraction peak intensities and the emergence of new functional groups at and . Citric acid treatment led to partial CC dissolution, resulting in up to weight loss, as confirmed by XRD and energy-dispersive spectroscopy (EDS). Scanning electron microscopy (SEM) revealed increased porosity (up to ) and enhanced surface roughness, particularly in TE 3. Wettability analysis demonstrated a maximum contact angle of following OA modification of CC, while oil adsorption tests of the PE-CC composites showed substantial improvements in oil uptake, with vegetable oil adsorption increasing from (NE) to (TE 3), and hexane and diesel reaching and respectively, in TE 3. Photoluminescence analysis revealed wavelength-dependent blue-violet emissions with broad peaks at 405 and 570 nm when excited at 255 and 405 nm , respectively, indicating potential optical applications. These findings show the potential of OA and citric acid modifications in enhancing the surface properties, photoluminescence, and adsorption efficiency of PE-CC composites, positioning them as promising candidates for oil remediation and multifunctional industrial applications.

Introduction

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Oil contamination from petroleum hydrocarbons, industrial lubricants, and vegetable oils poses significant environmental and health risks due to its persistence and widespread occurrence [1,2]. These pollutants infiltrate water, soil, and air through spills, runoff, and improper disposal, leading to oxygen depletion in aquatic ecosystems, groundwater contamination, and inhibition of plant growth and development. Their hydrophobic nature limits natural biodegradation, causing bioaccumulation and toxicity, with petroleum-based compounds exhibiting potential carcinogenic effects [3]. Addressing this challenge requires materials that adsorb oil efficiently and also retain their structural integrity.

Polymer-based composites have emerged as promising materials for oil remediation due to their tunable surface properties, chemical resistance, and ability to incorporate hydrophobic reinforcements that enhance oil uptake [4]. By leveraging the complementary properties of their constituents, polymer composites offer enhanced mechanical strength, thermal stability, and controlled wettability, making them suitable for oil spill recovery and environmental applications [5-7]. Beyond their core structural properties, advanced composites can also incorporate multifunctional characteristics such as photoluminescence, electrical conductivity, and self-healing capabilities, broadening their utility in areas like sensor technology, renewable energy, and biomedicine [7-10].

Among polymer composites, polyethylene (PE)-based systems reinforced with calcium carbonate (CC) have gained attention for their improved mechanical, thermal, and barrier properties. CC, a widely used mineral filler, enhances the dimensional stability and density of PE composites while influencing water adsorption, dispersion, and swelling behavior [11-14]. A comparative study indicated that CC improves crystallinity and processability in high-density polyethylene (HDPE) composites more effectively than alternative fillers like eggshells [11]. However, its hydrophilic nature hinders dispersion in hydrophobic polymer matrices, leading to agglomeration and weak fillermatrix bonding, which can compromise mechanical integrity and reduce efficiency in oil adsorption applications [15, 16].

To address this limitation, surface modification of CC with hydrophobic agents such as oleic acid (OA) has been explored to improve its compatibility with polymer matrices. OA-treated CC enhances interfacial adhesion, increases composite durability, and improves oil uptake by reducing surface energy mismatch [17-19]. Additionally, acid treatments, such as nitric or sulfuric acid, modify polymer surfaces by introducing functional groups, increasing roughness, and enhancing adsorption properties. For instance, nitric acid treatment has been shown to introduce nitro groups onto styrofoam, creating an anionic surface capable of adsorbing ions effectively [20]. However, strong acids can also degrade polymer mechanical properties, necessitating careful selection of modification strategies [20]. Citric acid is a mild, biodegradable organic acid that can selectively reacts with calcium carbonate fillers to produce without damaging the polymer matrix, unlike stronger acids such as nitric acid. Also, it is safer and eco-friendly making it ideal for sustainable material processing and green chemistry applications [21].

Beyond structural modifications, functional enhancements such as photoluminescence can add value to oil-remediating materials, particularly for real-time monitoring and detection of contaminants. While neither PE nor CC exhibits significant intrinsic photoluminescence, composite formulations incorporating luminescent fillers or surface-modified CC may develop unique optical properties. Fu et al. demonstrated that CC enhanced photoluminescence in alginate by releasing ions, which altered structural morphology and facilitated electron transfer, offering a sustainable alternative to rare-earth-based materials [22]. These findings suggest that incorporating modified CC into PE composites could yield new functionalities beyond oil adsorption, making them applicable in environmental sensing technologies.

While studies have explored OA-treated CC for improved polymer compatibility, the role of acid-induced porosity from CC dissolution in enhancing oil adsorption and photoluminescence remains unexamined. This study investigates the influence of OA-modified CC and citric acidinduced porosity on polyethylene-calcium carbonate composites (PE-CC), focusing on structural and surface properties, wettability, oil adsorption, hardness, and photoluminescent behavior. By addressing these aspects, this research aims to develop advanced polymer composites with optimized oil-remediating capabilities and potential multifunctionality.

Materials and Methods

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Materials

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The primary materials used in this study were Low-Density Polyethylene pellets (PE) and calcium carbonate (CC). The PE pellets used were commercially available industrial-grade material with a melt flow rate of (ASTM D1238, purity, Shijiazhuang Jintaichang New Materials Co., Ltd., China). The calcium carbonate used was also commercially available industrial grade ( purity, local supplier, Nigeria). Oleic acid ( purity, Sigma-Aldrich, Germany) and citric acid ( purity, Sigma-Aldrich, Germany) were used as chemical modifiers. Ethanol ( , Sigma-Aldrich, Germany) was employed as the solvent for OA treatment, and laboratory-produced distilled water was used for preparing solutions and for rinsing after citric acid modification.

Preparation of OA-treated CC

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OA was dispersed in 100 mL of ethanol at the desired concentrations of , and . To this solution, 100 g of CC was added with continuous stirring for 3 h to ensure uniform dispersion of OA on the surface of the CC particles. The mixture was then heated to dryness while stirring at for a period of 3 h to ensure complete removal of the solvent. The resulting powder was pulverized and labeled as follows based on the OA content: CC1 ( ), CC2 ( ), CC3 ( ). These powders were then stored for subsequent use in the fabrication of polymer nanocomposites [23]. The wettability of the CCs was assessed by measuring the contact angle of a water droplet on their surface using a Drop Shape Analyzer (DSA30, Krüss). Higher contact angles signify greater hydrophobicity and a reduced attraction to water [24].

PE-Composite fabrication

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PE-CC composites were fabricated using the melt blend method. The CC samples (CC1, CC2, and CC3) were incorporated into PE at a CC weight fraction of to produce the polymer composites, labeled as follows: NE 1 (CC1 with 0 wt.% OA), NE 2 (CC2 with 0.50 wt.% OA), NE 3 (CC3 with ). The blend was processed using a twin-screw extruder maintained at with a screw speed of 100 rpm for 10 min to ensure uniform CC dispersion within the polymer matrix. The extrudate was then pressed into films of appropriate thickness using a Rositek heat press with a pressure of 500 MPa for 5 min (RMP2, USA) and cut based on the test standard. Pure PE was processed using the same method and labeled as NE to serve as a reference material for comparison against the composite samples [25]. Their wettability was assessed using the same procedure applied to the OA-treated CCs.

Synthesis of porous polymer-composites

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The PE-CC composites were made porous by immersion in excess citric acid. Specifically, 20 pieces of of each composite (NE 1, NE 2, and NE 3) were immersed in 50 mL of 1 M citric acid solution for 48 h . After immersion, the composites were removed, rinsed three times with distilled water, and dried at for 12 h . The citric acid-treated composites were labeled as: TE 1 (from NE 1), TE 2 (from NE 2), and TE 3 (from NE 3). Pure PE treated with citric acid was labeled as TE [20]. Weight loss was calculated using Eq. 1.

where wo represents the initial weight of the composite before citric acid treatment (in grams) and , the final weight of the composite after citric acid treatment (in grams).

Crystallographic analysis

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The crystalline structure of the CC samples, PE, and the polymer composites was analyzed using a Malvern Panalytical Empyrean X-ray diffractometer equipped with radiation ( ). Data were collected in the range of , with a scan rate of . Diffraction patterns of the CCs were matched against the ICDD reference database to determine its crystalline phases.

Morphological analysis

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Surface morphology, particle dispersion, and associated changes were analyzed using a Philips XL30 ESEM at a magnification of 600 x . Elemental composition was determined using Energy Dispersive X-ray Spectroscopy (EDS) integrated with the Philips XL30 ESEM. Surface profiles and roughness parameters of the composites were analyzed using Gwyddion 2.45 software.

Functional groups

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Functional group analysis on the CCs and polymer composites was performed using an FTIR spectrometer PerkinElmer Spectrum Two in the wavenumber range of . Samples were analyzed using the attenuated total reflectance (ATR) method for the CC and their composites.

Photoluminescence spectroscopy

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The photoluminescent properties of the PE composites were evaluated using an RF-6000 Shimadzu Spectro fluorophotometer. Emission spectra were recorded at excitation wavelengths of 255 nm and 405 nm to evaluate how CC and citric acid treatments influence the luminescent properties of the polymer composites. Also, NE 3 and TE 3 were subjected to 10 cycles of UV exposure at a wavelength of 255 nm for 5 minutes per cycle, separated by 1 h in darkness [26]. After each cycle, the emission spectra were evaluated as a percentage of the original intensity to determine photoluminescence stability.

Shore hardness of polymer composites

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The Shore D hardness of the polymer composites was measured using a durometer in Shore Hardness Units (S.H.U.), following ASTM D2240 standards [27]. Samples measuring 50 mm by 50 mm with a thickness of 2 mm were placed on a flat surface. The durometer's indenter was pressed perpendicularly onto each sample for 10 s to stabilize the reading. Three measurements were taken at different locations on each sample to account for surface variability, and the average was recorded as the final hardness value.

Adsorption test

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The oil adsorption test was conducted following the ASTM D570 standard for water adsorption [28]. The test was designed to evaluate and compare the adsorption capacities of the PE-CC composites for various non-polar liquids, including vegetable oil, n-hexane, and diesel. Water was used as a benchmark. Uniform samples of 10 mm by 10 mm and 2 mm thickness were weighed to determine their dry weight ( ). They were then immersed in the respective liquids at for 24 h in sealed containers to prevent evaporation. After immersion, the samples were removed, gently wiped to remove excess liquid, and reweighed ( ). Each test was performed in triplicate to ensure reproducibility and average values with standard deviations were reported. Adsorption capacity was calculated using the formula in Eq. 2.

Statistical analysis

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All measurements were performed in triplicate, with results expressed as mean ± standard deviation (SD). Differences between sample groups were analyzed using ANOVA, followed by Dunnett's multiple comparison test, with statistical significance set at . These statistical methods were chosen to assess the significance of variations in results obtained among the different composite formulations. Identifying statistically significant differences will confirm whether the combined effects of oleic acid treatment and citric acid-induced porosity contribute to improved functional properties. Statistical analysis was conducted using GraphPad Prism 8.

Results and Discussion

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Wettability of the OA-treated CC

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Surface modification of CC with OA, which was assessed through contact angle, improved its hydrophobicity, as shown in Fig. 1, and was consistent with those reported by Longkaew et al. [29], Al-Shirawi et al. [30], and Wang et al. [24]. Contact angles above , as observed for CC2 and CC3, confirm the hydrophobic nature of the treated CC surfaces, improving their compatibility with nonpolar matrices and reducing moisture uptake. In contrast, contact angles below , as seen in CC1, suggest more hydrophilic behavior and reduced effectiveness in nonpolar composite applications [31].

Fig. 1. Contact angles of calcium carbonate fillers after treatment with varying concentrations of oleic acid.

Fig. 1. Contact angles of calcium carbonate fillers after treatment with varying concentrations of oleic acid.

Weight loss due to citric acid treatment

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The weight loss of the sample due to citric acid treatment exhibited a clear trend associated with CC dissolution during the citric acid treatment, as presented in Table 1. Pure PE (NE) showed minimal weight loss of just , verifying its stability. However, composites containing CC (NE 1, NE 2, and NE 3) experienced statistically significant weight loss, ranging from to compared to the NE ( ). The standard deviation values ( , and 0.16 ) reflect slight variability in weight loss across the samples, with NE 1 exhibiting the highest deviation, likely due to variations in CC dispersion within the composites. The weight loss trends in composites with mixed phases suggest that the dispersion of CC particles influences the extent of dissolution. More homogeneous dispersion may lead to uniform dissolution during acid exposure, ultimately affecting the material's stability and performance. The balanced chemical equation describing CC dissolution during citric acid treatment is shown in Eq. 3.

During this reaction, escapes, reducing the material's overall mass. Rinsing with distilled water further removes the loosely bound insoluble calcium citrate, contributing to weight loss. These two events explain the observed mass reduction after citric acid treatment. These findings align with the substantial weight loss reported for glass-ionomer cement under acid treatment, in contrast to the minimal loss observed in resin composites in a comparative study [32].

Table 1. Filler composition, filler-to-polymer ratio, and weight loss after citric acid treatment of composite samples.

Sample | Filler | Filler OA treatment (%) | Filler to Polyethylene ratio | Weight Loss after citric acid treatment (%) | Corresponding citric acid-treated sample
NE | -- | -- | 0:100 | 0.01 ± 0.01 | TE
NE1 | CC1 | 0.00 | 60:40 | 8.96 ± 0.54 | TE 1
NE2 | CC2 | 0.50 | 60:40 | 7.88 ± 0.23 | TE 2
NE3 | CC3 | 1.50 | 60:40 | 7.84 ± 0.16 | TE 3

Crystalline structure of CC and composites

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X-ray diffraction analysis revealed the characteristic structures of PE and CC [33-35]. The XRD patterns of the OA-treated CC fillers, shown in Fig. 2a, were in the monoclinic phase and matched the ICDD card 01-070-0095. The prominent peaks and their matching planes were identified at , and . The treatment of CC with OA resulted in a progressive reduction in the intensity of these peaks with increasing OA concentration, aligning with previous studies [36]. This reduction suggests that OA-induced surface modifications altered the diffraction intensity without forming a new crystalline phase. For the pure PE samples (NE and TE) shown in Fig. 2b, the XRD analysis revealed characteristic diffraction peaks at and , corresponding to the (110) and (200) planes of the orthorhombic PE crystalline phase. These peaks were sharp and intense in NE, indicating high crystallinity. However, a slight reduction in the intensity of the (200) plane at was observed in the citric acid-treated sample (TE). This suggests a minimal impact of citric acid on the crystalline regions of the PE and the polymer's resistance to acid treatment [33, 37]. In the PE-CC composites (NE 1, NE 2, NE 3, TE 1, TE 2, TE 3), peaks corresponding to both PE and CC were observed, confirming that no chemical interaction occurred during the compositing process (Fig. 2b). In the composites, NE 1, NE 2, and NE 3, the PE peaks at and were significantly diminished, due to the dominant intensity of the CC peaks [38]. Following citric acid treatment (TE 1, TE 2, TE 3), the PE peaks became slightly pronounced, while the CC peaks showed a reduction in intensity. This reduction in CC peak intensity in the citric acid-treated composites confirms partial dissolution of CC during citric acid treatment. Despite these changes, the PE peaks remained discernible across all composites, suggesting that the polymer maintained its structural integrity within the matrix. The OA coating on CC appeared to have minimal impact on the XRD patterns of the composites, both before and after citric acid treatment. This observation indicates that while OA altered the surface properties of CC, it did not significantly affect the crystalline structures of the composite materials [39]. These findings indicate that while OA modifies surface properties, it does not induce significant crystalline phase changes, which is essential for maintaining mechanical stability in composite applications.

Fig. 2. X-ray diffractograms of the OA-treated CC (a), and the PE-CC composites (b).

Fig. 2. X-ray diffractograms of the OA-treated CC (a), and the PE-CC composites (b).

Effect ofand citric acid treatment on the functional groups ofand composites

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The FTIR spectrum (Fig. 3a) of the CC sample CC1 showed characteristic peaks at , , and . These corresponded to stretching, out-of-plane bending, and inplane bending vibrations, respectively, as have been reported by other authors [11, 29, 34]. In the OAtreated CC samples (CC2 and CC3), additional peaks appeared around , representing stretching vibrations. Also, the peaks at and exhibited increased intensity as the OA concentration increased, aligning with surface modifications of the CC particles [36]. The FTIR spectra of the pure PE samples presented in Fig. 3b show characteristic adsorption bands associated with PE [23, 36]. These include symmetric and asymmetric stretching vibrations of groups at approximately and , as well as bending vibrations around and .
Furthermore, the PE-CC composites (NE 1, NE 2, NE 3, TE 1, TE 2, and TE 3) had additional peaks corresponding to CC (Fig. 3b). These include peaks at and , while the expected peak at was merged with the bending peak at . In the citric acidtreated composites, a reduction in the intensity of the carbonate peaks at 1395 and was observed, confirming partial carbonate loss due to the treatment.

Fig. 3. FTIR spectra of the OA-treated CC (a), and the PE-CC composites (b).

Fig. 3. FTIR spectra of the OA-treated CC (a), and the PE-CC composites (b).

Morphological changes after oleic and citric acid treatment

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The SEM micrographs shown in Fig. 4a reveal the morphological differences across the samples particularly before and after citric acid modification. The surface of non-treated pure PE (NE) appeared smooth and continuous [24, 40]. However, in the acid-treated PE (TE), surface irregularities, undulations, and sharper edges were observed. These changes were attributed to localized stress, strain, or minor oxidative effects, particularly in amorphous regions of the polymer during citric acid treatment. In the composites, the incorporation of CC introduced various sizes of CC particles (up to about ) within the polymer matrix which were well-distributed. Unlike the findings of Ritonga et al. [36], moderate agglomeration was observed in the fillers, likely due to heating to dryness of the CC fillers during OA treatment. TE 1 and TE 3 displayed significant porosity, characterized by irregular voids, cavities, and surface undulations. These features are attributed to the partial dissolution of CC by its reaction to citric acid. TE 3, being a malleable composite due to the softening effect of OA treatment and the agglomeration of its fillers, exhibited larger pores, more irregular voids, and greater surface undulations than TE 1.

Changes in elemental composition after oleic and citric acid treatment

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The differences in elemental composition observed in EDS results were influenced by CC filler and chemical treatments as shown in Fig. 4b. In NE, the spectra showed a strong carbon peak (C-Kα) at approximately 0.277 keV while in NE 1 and NE 3, prominent calcium and oxygen peaks ( ) at 3.69 keV and 0.525 keV were observed respectively, confirming the presence of CC. Upon OA treatment of CC in NE 3, the oxygen peak intensity slightly increased. After citric acid treatment, traces of oxygen were detected in pure PE samples (TE), likely from citric acid residues. In TE 1 and TE 3, the calcium and oxygen peak intensities were lower than in untreated samples, indicating partial CC removal.

Effect of CC Fillers and Acid Treatments on the Surface Roughness of Composites

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The surface profiles of the materials (Fig. 4c) and their respective roughness parameters (Table 2) support the trends observed in the SEM micrographs. NE had the smoothest surface with the lowest RMS roughness ( 92.26 nm ) and mean roughness ( 68.38 nm ), reflecting its uniform morphology. Adding CC fillers in NE 1 and NE 3 increased surface roughness, with NE 3 showing a higher RMS roughness ( 183.80 nm ) than NE due to more heterogeneous surfaces and larger particle aggregations in NE 3 [41]. Citric acid-treated composites (TE 1 and TE 3) had lower roughness values than their untreated counterparts, due to the 'smoothing effect' of citric acid treatment. TE 3 exhibited larger pores (over ) and moderate RMS roughness ( 136.30 nm ), suggesting structural changes that may improve adhesion, wettability, and oil adsorption capacity.

Fig. 4. SEM micrographs (a), EDS analysis (b), and surface roughness mapping (c) of the PE-CC composites.

Fig. 4. SEM micrographs (a), EDS analysis (b), and surface roughness mapping (c) of the PE-CC composites.

Table 2. Surface roughness parameters of the PE-CC composites.

Sample | RMS Roughness (Sq) | Mean Roughness (Sa) | Maximum Peak (Sp) | Maximum Height Pit Depth (Sv)
NE | 92.2639 nm | 68.3794 nm | 0.567499 μm | 0.432501 μm
TE | 144.529 nm | 103.551 nm | 0.678620 μm | 0.321380 μm
NE1 | 160.855 nm | 110.089 nm | 0.635592 μm | 0.344801 μm
TE1 | 125.837 nm | 89.235 nm | 0.647850 μm | 0.352150 μm
NE3 | 183.804 nm | 127.822 nm | 0.567461 μm | 0.385481 μm
TE3 | 136.301 nm | 97.405 nm | 0.656183 μm | 0.343817 μm

Photoluminescent properties of the PE-CC composites

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The impact of citric acid treatment and CC surface modification on the photoluminescent properties of the composites was evaluated to determine how morphological and structural changes influence light emission. The photoluminescence (PL) spectra of PE and PE-CC composites when excited at 255 nm and 405 nm are displayed in Fig. 5A1 and Fig. 5B1. The characteristic broad emissions recorded are similar to those of polymeric materials in other similar studies [42, 43]. Generally, as the excitation wavelength increased, luminescence peaks shifted and narrowed demonstrating a wavelength-dependent emission behavior (Tareeva et al. 2020). The observed photoluminescence trends, including spectral shifts, changes in emission intensity, and peak narrowing, were attributed to surface defects and structural modifications introduced by citric acid treatment and the incorporation of OA-modified CC fillers in the polymer. At 255 nm excitation, all materials exhibited broad emissions at 405 nm , with the non-porous composites (NE 1, NE 2, NE 3) showing a broadening and slight shift toward higher emission wavelengths. In contrast, the porous citric acidtreated materials exhibited narrower emission peaks. Changes in pure PE were attributed to surface modifications and tension release, while in composites, OA-modified filler and citric acid-induced porosity influenced their luminescent properties. At 405 nm excitation, the observed broad emissions were centered around 570 nm , with untreated PE exhibiting lower intensity than treated PE, suggesting the formation of surface defects. Non-porous composites had higher intensity than their porous counterparts, suggesting that porosity negatively impacts PL. The CIE chromaticity diagrams (Fig. 5A2 and Fig. 5B2) further confirm a shift towards fainter violet in composites at 255 nm excitation, while excitation at 405 nm shows a cluster around the violet region, with NE 3 and TE 3 shifting to the yellow-green region, demonstrating tunable photoluminescent properties. The reduction in PL intensity in porous samples may be attributed to increased surface scattering and nonradiative recombination centers formed due to structural defects introduced by citric acid treatment. The samples NE 3 and TE 3 demonstrated notable photoluminescent stability, as illustrated in Fig. 6a and Fig. 6b. Overall, the structural modifications that enhance photoluminescence, such as altered surface states and functional group interactions, also contribute to the adsorption performance by affecting the material's wettability and porosity. This dual influence underscores the interplay between optical properties and surface activity.

Fig. 5. Photoluminescence spectra of the PE-CC composites at 255 nm (A1) and 405 nm (B1), along with the corresponding CIE chromaticity diagrams at 255 nm (A2) and 405 nm (B2).

Fig. 5. Photoluminescence spectra of the PE-CC composites at 255 nm (A1) and 405 nm (B1), along with the corresponding CIE chromaticity diagrams at 255 nm (A2) and 405 nm (B2).

Fig. 6. Photoluminescent stability of the PE-CC composites at 255 nm : NE 3 (a) and TE 3 (b).

Fig. 6. Photoluminescent stability of the PE-CC composites at 255 nm : NE 3 (a) and TE 3 (b).

Oil affinity and adsorption performance

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The oil affinity test result (Fig. 7a) and its statistical analysis (Table 3) reveal the effect of the oil type and sample modifications on adsorption performance. Polymers are inherently hydrophobic, and incorporating OA-treated fillers enhances this property by improving compatibility within the polymer matrix [44]. Treating the composite with citric acid introduces porosity by creating micropores (up to ) through its reaction with calcium carbonate, increasing the surface area and enhancing contaminant adsorption [21]. This combination of hydrophobicity and increased surface area makes the material more effective for capturing and retaining hydrophobic pollutants. The results indicated that water adsorption remains minimal in samples, consistent with PE's hydrophobicity, but increases significantly in the composites and after acid treatment (up to in

TE 1) due to enhanced hydrophilicity and porosity as reported by Jiao et al. (Jiao et al. 2023). Vegetable oil adsorption increased modestly from 5.21 % in NE to 18.75 % in TE 3, due to the fillers' hydrophobic OA treatment and citric acid-induced porosity. Jahani et al. also observed a similar trend in studies on dye-absorbent materials incorporating hydrophobic modifications [45]. Hexane and diesel followed similar patterns, with TE 3 achieving maximum adsorption ( and respectively), reflecting improved affinity for both polar and non-polar liquids. Statistical analysis showed that liquid type and sample modifications significantly affected adsorption, accounting for and of the variance, respectively, with their interaction contributing an additional 20.19 %. Dunnett's test showed significant differences across all comparisons ( ). In practical applications, optimal adsorption occurs when the material matches the liquid, particularly in areas like oil spill remediation or filtration, as their interaction significantly influences adsorption properties and performance. The low standard deviations among replicates indicate consistent structural changes and reliable performance across tests.

Table 3. ANOVA summary results for the liquid adsorption tests.

Source of Variation | Degrees of Freedom | Sum of Squares | Mean Square | F-value | P-value | Variance Contribution (%)
Liquid type | 3 | 457.5 | 152.5 | 975.37 | < 0.0001 | 23.05
Sample | 7 | 1116 | 159.5 | 1020.16 | < 0.0001 | 56.25
Interaction (Liquid x Sample) | 21 | 400.8 | 19.09 | 122.08 | < 0.0001 | 20.19
Residual (Error) | 64 | 10.01 | 0.1563 | - | - | -
Total | 95 | 1985 | - | - | - | 100

Shore hardness and wettability of the PE-CC composites

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The Shore hardness values, shown in Fig. 7b, reveal the effects of modifications on the material's rigidity. Pure PE (NE) had a baseline hardness of 55.6, with minimal deviation whereas a previous study reported 63.9 [46]. Citric acid treatment (TE) slightly reduced the hardness to 55.2 , with better consistency. CC reinforcement in NE 1 significantly increased hardness (64.4) (Hayeemasae and Ismail 2021), but citric acid-treated TE 1 (62.1) showed better consistency although Wierzbicka et al. [46] reported reduced Shore values when hexagon boron nitride was added alone but higher values when hexagon boron nitride and titanium were incorporated into PE. Similar trends were observed in NE 2 and TE 2, with TE 2 exhibiting reduced hardness. NE 3 and TE 3 displayed further reductions, indicating an increase in ductility and malleability to OA concentration and porosity (Ippolito et al. 2020). The statistical analysis shows significant differences in the hardness values ( 0.0001 ) with a strong data fit ( ). Dunnett's test highlighted significant differences in the comparison of NE against the other untreated and citric acid-treated composites (NE 2, NE 3, and TE 3), while NE vs. NE 1, NE vs. TE 1, and NE vs. TE 2 showed no significant differences. These results indicate that untreated composites are more rigid, while citric acid-treated materials are less rigid and better suited for applications requiring flexibility, porosity, and roughness.

Fig. 7. Oil adsorption capacity (a) and Shore hardness values (b) of the PE-CC composites.

Fig. 7. Oil adsorption capacity (a) and Shore hardness values (b) of the PE-CC composites.

The wettability of the materials was assessed using contact angle measurements, as shown in Fig. 8. The NE samples showed higher contact angles ( ), reflecting their hydrophobic surfaces and limited water affinity [47]. In contrast, the TE samples had lower contact angles ( , ), indicating that citric acid treatment increased surface porosity and made the surfaces more hydrophilic. Additionally, the presence of oleic acid in NE 3 and TE 3 contributed to higher hydrophobicity compared to NE 1 and TE 1. These results show that surface chemistry and porosity influence the water interaction behavior of the composites.

Fig. 8. Contact angles of the PE-CC composites before and after citric acid treatment.

Fig. 8. Contact angles of the PE-CC composites before and after citric acid treatment.

The surface modifications introduced by oleic acid and citric acid treatments have profoundly impacted the properties of the polyethylene-calcium carbonate composites. Citric acid treatment enhanced porosity and surface hydrophilicity, thereby improving oil adsorption capabilities. However, this treatment also resulted in reduced luminescence intensity and mechanical hardness, rendering the materials more flexible. Oleic acid modification enhanced the hydrophobic character of the material while improving compatibility between the filler and the polymer matrix.

Conclusion

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This study successfully fabricated polyethylene-calcium carbonate (PE-CC) composites with tailored structural and surface properties to enhance oil adsorption. The composites were fabricated via melt blending using a 60/40 filler-to-polymer ratio, incorporating calcium carbonate (CC) modified with , and oleic acid ( OA ) to improve hydrophobicity. Subsequent citric acid ( 1 M ) treatment induced porosity through partial dissolution of calcium carbonate, further refining the composite's performance. Structural characterization confirmed effective OA coating on CC, with XRD and FTIR analyses revealing reduced diffraction intensity and characteristic functional groups, indicating successful surface modification. XRD analysis of the composites verified the coexistence of PE and CC without chemical interaction, while the decrease in CC peak intensity after citric acid treatment of the PE-CC composites suggested partial CC dissolution. SEM imaging demonstrated uniform CC dispersion within the polymer matrix, with citric acid treatment creating voids up to 40 in TE 3, facilitating enhanced porosity. Elemental analysis supported this finding, showing calcium depletion after citric acid treatment. Surface roughness measurements indicated smoother profiles for citric acid-treated composites, while TE 3 exhibited moderate roughness with larger pores, improving adhesion and wettability. Wettability tests further reinforced this, showing increased hydrophilicity in citric acid-treated samples, enhancing water affinity. Photoluminescence analysis revealed blue-violet emissions with broad peaks centered at 405 and 570 nm under 255 and 405 nm excitation, respectively, suggesting potential optical applications. Oil adsorption studies indicated a significant increase in the uptake of both polar and non-polar liquids, particularly in TE 3, where higher porosity improved fluid retention. Shore hardness testing confirmed a reduction in material rigidity following citric acid and OA treatments, promoting flexibility without compromising structural integrity. These findings validate the chemical modifications employed in this study, demonstrating their effectiveness in enhancing porosity, surface interactions, and multifunctionality. The PE-CC composites have potential for environmental applications, particularly in oil remediation, where enhanced porosity and tailored surface properties are crucial for efficient adsorption and retention.

Funding

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This research was supported by the African Union and the Pan African University Life and Earth Sciences Institute through a Ph.D. scholarship awarded to Ayodunmomi Esther Olowofoyeku.

Acknowledgments

The original version of this paper is available on https://www.scientific.net/EC.11.7.pdf

Ayodunmomi Esther Olowofoyeku sincerely thanks the African Union and the Pan African University Life and Earth Sciences Institute for awarding a Ph.D. scholarship, which facilitated this research as a part of her doctoral research.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 25-38

doi: 10.4028/p-yjgnY5

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

Submitted:
2024-12-21

Revised:
2025-04-28

Accepted:
2025-05-05

Online:
2025-09-10

Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

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I Gusti Ayu Agung Istri Dwi Jovanca Devi , Andhika Fathurrohman , Alfa Rizky , Firyal Lutfi Fauziah , Muhammad Ezra Bena , Hikmatun Ni'mah , Fahimah Martak, Dra

¹Chemical Engineering Department, Faculty of Industrial Technology and Systems Engineering

Chemistry Department, Faculty of Science and Data Analytics

Institut Teknologi Sepuluh Nopember (ITS), Kampus ITS, Sukolilo, Surabaya 60111, Indonesia

dwijovanca7@gmail.com, andhikafathurrohman55@gmail.com, alfarzzkyy@gmail.com, gfahimahm@chem.its.ac.id

Keywords: Chitosan, Methylene Blue, Photodegradation, Silica, Xanthan Gum.

Abstract

Methylene Blue (MB) waste is damaging to both humans and the environment. Chitosan is one of the MB adsorbents that may be made from green mussel shells. Because CS compounds have a limited adsorption capacity for MB , a restricted surface area, and poor chemical stability, thus necessitating modification. CS/XG was created by combining the three chemicals silica ( ), tofu pulp, and the anionic substance Xanthan Gum (XG). hydrogel bio-composite with the aid of UV light, can absorb MB by photodegradation. The objective of this paper is to analyze the regeneration and photocatalysis kinetics based on the kinetic rate constant of the bio-composite photodegradation, and to identify the ideal circumstances of MB photodegradation by hydrogel biocomposite with Box-Behnken design. The CS/XG bio-composite was synthesized from chitosan (green mussel shell waste) and xanthan gum (tofu dregs waste) with added to adsorb methylene blue via photodegradation. The use of green mussel shells and tofu dregs is significant as it turns abundant waste into valuable materials, reducing pollution and supporting low-cost, eco-friendly wastewater treatment. The variables were concentration, and photodegradation time. The results showed that the optimum condition occurred at concentration 5.054 ppm ; and irradiation time 119.67 minutes with % degradation of 94.2%. After the 5th reuse of CS/XG.SiO2, the degradation only decreased from to , indicating good regeneration ability. Analysis of photodegradation kinetics showed accurate modelling using the Modified Elovich model with an value of 0.9805 and a photodegradation kinetic rate constant of .

Introduction

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The growth of the modern industrial sector has resulted in the increased use of dyes that are harmful to the environment. Methylene Blue (MB) is one of the cationic dyes widely used in industry today. Long-term exposure to methylene blue is reported to have negative impacts on health and the environment [1]. Therefore, removing this pollutant from waters is important for the environment. A material with a large adsorbing capacity to MB is chitosan (CS). Chitosan can be obtained through deacetylation of chitin compounds found in the shells of arthropods such as green mussels (Perna viridis L) because they contain chitosan [2]. Chitosan has an adsorption capacity of at alkaline pH [3] so it has the potential to be an adsorbent raw material. However, chitosan has several disadvantages, namely low chemical stability, low surface area, and small adsorption capacity for methylene blue. Modifications are needed to chitosan to adsorb larger amounts of methylene blue [4], such as the addition of anionic compound Xanthan Gum (XG). The
electrostatic interaction between the anionic groups of XG and the cationic groups of methylene blue can promote a stronger bond between the dye molecules and the composite material [4]. However, the addition of XG compound is not ideal to optimise the degradation ability of chitosan so that a photocatalyst material such as SiO 2 is needed to increase the surface area of the composite. The chosen degradation method is the photodegradation method due to low chemical usage, low operational costs, easy operation, and can be used repeatedly [5]. This is supported by previous research, the use of can degrade methylene blue perfectly for 90 seconds by photodegradation [6]. The combination of the three materials produces bio-composite materials that are effective in photodegradation of cationic textile dye waste such as methylene blue. There has been no previous research using chitosan from shellfish and xanthan gum from tofu dregs for MB photodegradation.
In this study, bio-composite was synthesised. SiO 2 with chitosan from green mussel shell waste and Xanthan Gum from tofu pulp waste that can adsorb methylene blue by photodegradation. Previous research synthesised similar composite materials but used commercial chitosan and Xanthan Gum. The dye used in the previous study was methyl orange and the usual degradation method. Other studies also synthesised chitosan from green mussel shells and Xanthan Gum from tofu pulp separately without being combined into one material and without being used to adsorb methylene blue. This is the novelty of this research.
The variables in this study are pH , time, and methylene blue concentration using statistical analysis of variable optimisation, namely multivariable Box-Behnken Design with three independent variables. In addition, we synthesised chitosan from green mussel shells and Xanthan Gum based on tofu pulp in the manufacture of XG. adsorbent. Finally, we conducted regeneration tests and analysed the photodegradation kinetics activity. The problem in this research is what is the optimum condition of methylene blue photodegradation using CS/XG. bio-composite and how is the regeneration ability and kinetic activity of photocatalysis based on the kinetic rate constant of bio-composite photodegradation. The purpose of this research is to determine the optimum condition of methylene blue photodegradation using bio-composite by BoxBehnken Design method and analyse the regeneration and photocatalysis kinetics of CS/XG. bio-composite photodegradation.

Research Methods

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Materials

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The tools used in this research are glass beaker, thermometer, magnetic stirrer, glass stirrer, hotplate, three neck flask, oven, filter paper, erlenmeyer, ultrasonic homogenizer BLIH-301, N4S UV-Vis spectrophotometer, autoclave, fed batch fermentor, centrifuge, and Vivaria 7 Watt UVC lamp. Meanwhile, the materials used in this research are wet tofu pulp obtained from a tofu factory in Surabaya, green mussel shells from the coast of Kenjeran Beach Surabaya, distilled water, deionised water, tetraethyl orthosilicate (TEOS) Merck, ammonium hydroxide ( ), acetone, acetic acid , ethanol, methylene blue, HCl solution, NaOH , filter paper, sucrose, citric acid, glutamic acid, , trace elements, and isolate Xanthomonas campestris bacteria.

Research Variables

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The independent variables used in this study are pH (3-11), time ( minutes), and methylene blue concentration (5-20 ppm) based on Box-behnken design analysis using Design Expert V11 software; the control variables are synthesis operating conditions, temperature, adsorbent composition and mass, test stirring speed, and UV light source; and the dependent variable is methylene blue catalytic photodegradation efficiency.

Research Procedure

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The flow diagram of this research shown below.

Fig. 1. Flow Diagram of The Research

Fig. 1. Flow Diagram of The Research

Synthesis of Chitosan from Green Mussel Shells

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Chitosan synthesis has been carried out based on previous research by Firyanto [7]. Chitosan was synthesised from green mussel shells (Perna viridis) through three processes, namely deproteination, demineralisation, and deacetylation. In the deproteination process, the crushed green mussel shells were added with 1 N NaOH in the ratio of 1:10 (w/v), stirred with a stirrer at 500 rpm , and heated at 90 oC for 90 minutes. The deproteinated sample was then rinsed with distilled water, filtered, and oven dried for 2 hours. Next, the dried samples were demineralised with 1 N HCl in a ratio of 1:10 and stirred with a stirrer at 70 oC with a speed of 500 rpm for 60 minutes. The demineralised samples were rinsed with distilled water, filtered, and oven dried for 2 hours. The process ended with deacetylation of chitin with solution in the ratio of into the dry demineralised sample and stirred with a 400 rpm stirrer at for 90 minutes. The remaining solid was rinsed with distilled water, filtered, and oven dried for 2 hours.

Fig. 2. Flow Diagram of Chitosan Synthesis from Green Mussel Shells

Fig. 2. Flow Diagram of Chitosan Synthesis from Green Mussel Shells

Xanthan Gum Synthesis Using Tofu Dregs

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Xanthan Gum synthesis has been carried out based on previous research by Gustiani et al. (2018). Wet tofu dregs were dried using an oven at and made a sterile tofu dregs solution with a concentration of . Then, inoculation of Xanthomonas campestris bacteria was carried out on Nutrient Broth (NB) liquid media for 24 hours. From the liquid media, of the media will be taken to be mixed into the sterile tofu pulp solution along with sucrose, citric acid, glutamic acid, , and trace elements. Then, fermentation was carried out for 5 days under batch conditions with a temperature of . After that, the fermentation results were dried using an oven at for 3 hours.

Fig. 3. Flow Diagram of Xanthan Gum Synthesis from Tofu Dregs

Fig. 3. Flow Diagram of Xanthan Gum Synthesis from Tofu Dregs

Synthesis of XG.SiO2 Composite

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The synthesis of XG. composite was carried out based on previous research by Rahmatpour [4]. The first stage prepared Xanthan Gum solution consisting of 50 mg of Xanthan Gum powder and 20 mL of distilled water in beaker A and stirred at for 6 hours. In beaker of ethanol and 1.5 mL of tetraethyl orthosilicate (TEOS) were dissolved. Meanwhile, in beaker C, 1 mL of 14.7 N ammonium hydroxide solution was prepared. Then, the solutions in beakers , and C were mixed in a round bottom flask and the reaction was carried out at for 5 hours in an gas environment. Then, 50 mL of acetone was added and the resulting sample was filtered. After that, the sample was dried in an oven at for 24 hours and a white powder XG. was obtained.

Fig. 4. Flow Diagram of XG. Synthesis

Fig. 4. Flow Diagram of XG. Synthesis

Synthesis of CS/XG.Composite

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The synthesis of CS/XG. composite was made with 0.4 g chitosan dissolved in 32 mL of acetic acid solution and stirred until a clear viscous solution was obtained. In a separate erlenmeyer, 57 mg of XG. was mixed in 8 mL of deionised water and homogenised with an ultrasonic homogenizer for 30 minutes. Then, the XG. suspension was added to the chitosan solution while stirring for 1 hour at . The hydrogels formed were dehydrated by soaking in 30 mL of ethanol for 24 hours with three ethanol changes. After that, the hydrogels were dried in an oven at for 24 hours.

Fig. 5. Flow Diagram of Synthesis

Fig. 5. Flow Diagram of Synthesis

Characterisation of Synthesised Materials

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Characterisation of the synthesised CS/XG. composite was carried out using FTIR, XRD, and SEM tests. FTIR was conducted to determine the functional groups of the composite. XRD to determine the crystal structure in the composite and its crystallinity. Meanwhile, SEM aims to determine the surface morphology of composites. For each of the synthesised compounds, namely chitosan, Xanthan Gum, and XG.SiO2, FTIR and XRD characterisation were also carried out to determine the success of the compound synthesis.

Methylene Blue Photodegradation Test

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The photodegradation test was conducted by preparing 100 mL of Methylene Blue (MB) solution with a concentration of . Then, 50 mg of composite was put into the solution at room temperature accompanied by a 200 rpm stirrer in the dark room for 20 minutes until it reached adsorption equilibrium. Then, irradiation was carried out by a 7 Watt UVC lamp for an irradiation time of minutes and a solution pH of according to each run. The following is an illustration of photodegradation testing.

Fig. 6. Illustration of Photodegradation Testing

Fig. 6. Illustration of Photodegradation Testing

After irradiation, the composite was separated by centrifugation at 1500 rpm for 5 min and the remaining MB concentration was calculated by absorbance with a UV-Vis spectrophotometer at a wavelength of 668 nm. The % degradation was calculated based on the following formula.

With and being the initial and final MB concentrations, respectively. Data analysis using Design Expert v11 software with statistical analysis of Box-Behnken polynomial design quadratic model with the following equation.

With R is the response (% degradation), Y is the factor coefficient, and , and C are the independent variable factors. The equation obtained is then used to predict the optimum condition of % degradation of multiple independent variables. The Box-Behnken factor design in this study is as follows.

Table 1. Range and Level of Independent Variables in Box-Behnken Design

Design Variable | Factor | Unit | Coded Level
|  |  | -1 | 0 | 1
A | pH | - | 3.00 | 7.00 | 11.00
B | MB Concetration | ppm | 5 | 12.5 | 20
C | Time | minute | 30.00 | 75.00 | 120.00

Reusability Test of Chitosan/XG.as Methylene Blue Photodegradation

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The reusability test was carried out by experimenting at the optimum conditions obtained based on the previous analysis. The composite that has been separated with filter paper was desorbed with solution. Then, the desorbed composite was reused up to five times and the % photodegradation was analysed at each repetition.

Photocatalysis Kinetics Test of Chitosan/XG.SiO2

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Photocatalysis kinetics test was conducted to test the photocatalytic activity of the composite. This was done by setting up photodegradation testing at optimum conditions and taking aliquots at every interval of 20 minutes to 120 minutes. Then, the calculation of MB concentration at each time and analysis of photocatalysis kinetics using several models, namely Order 0, 1, 2, and modified Elovich respectively with the following mathematical equations.

Table 2. Mathematical Equation of Kinetics Model

No. | Model | Kinetics Formula | Reference
1 | 0 Order | dCt/dt = -kphoto | Luo (2019)
2 | 1st Order | dCt/dt = -kphoto × Ct | Luo (2019)
3 | 2nd Order | dCt/dt = -kphoto × Ct² | Luo (2019)
4 | Modified Elovich | dCt/dt = -kphoto × Co × exp(β(Ct - Co)) | Luo (2019)

Result and Discussion

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Material Synthesis

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Chitosan was synthesised from green mussel shell waste with three stages, namely deproteination (protein removal), demineralisation (mineral dissolution), and deacetylation (removal of acetyl groups) with the final result in Figure 7.a. The resulting chitosan is white and smooth and has a % yield per stage, namely proteination, demineralisation, and deacetylation of ; and of green mussel shells with an overall yield of and obtained Deacetylation (DD) for chitosan of 87.8%, indicating good chitosan quality (%DD > 70%) [8].

Fig. 7. Material Synthesis Results: a. Chitosan(CS), b. Xanthan Gum, c. XG. , dan d. CS/XG.SiO2

Fig. 7. Material Synthesis Results: a. Chitosan(CS), b. Xanthan Gum, c. XG. , dan d. CS/XG.SiO2

Furthermore, Xanthan Gum was synthesised from tofu pulp waste using the help of Xanthomonas campestris bacteria with the results in Figure 7.b. Xanthan gum was beige in colour and smooth and obtained a yield of of the mass of dry tofu pulp used as fermentation media. After Xanthan Gum powder is obtained, the next step is to synthesise XG. using the Stober method with an alkaline atmosphere. XG. that has been synthesised can be seen in Figure 7.c and obtained a yield of of the mass of Xanthan Gum and tetraethyl orthosilicate (TEOS) used. CS/XG. as the last material that became the adsorbent was synthesised by forming a composite of chitosan and XG. with the results as shown in Figure 7.d obtained a yield of 50.06% of the mass of chitosan and used.

Characterization of Materials

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The following are the results of the FTIR and XRD spectra of the synthesised material.

Fig. 8. FTIR Spectrum (a) and XRD Spectrum (b) of Citosan (CS), Xanthan Gum (XG), XG.SiO2, dan CS/ XG. Synthetised

Fig. 8. FTIR Spectrum (a) and XRD Spectrum (b) of Citosan (CS), Xanthan Gum (XG), XG.SiO2, dan CS/ XG. Synthetised

Figure 8.a shows the FTIR spectra of synthesised chitosan (CS), Xanthan Gum (XG), XG.SiO2, and CS/XG.SiO2. The peaks at ; 2900-2964; 1600-1700; are due to the presence of stretching, stretching, stretching, and stretching vibrations in the four materials, respectively. In the FTIR spectra of chitosan and Xanthan Gum, there is a peak at 842.4 in the form of C-O-C vibrations which indicates the presence of asymmetric glycosidic bonds between N -acetylglucosamine and D -glucosamine monomers in chitosan polymers (Pang, 2024) and the presence of glycosidic bonds between glucose monomers and glucuronic acid in Xanthan Gum. The FTIR spectrum of XG. showed peaks at and indicating the vibrations of assymetric stretching and symetric stretching groups. The missing peak at which was previously in Xanthan Gum indicates that Xanthan Gum is involved
in the formation of mesoporous silica ( SiO 2 ) [4]. In addition, there are peaks at 1019.4 and 1075.3 which are the overlap of Si -O-Si in silica and C-O-C in chitosan and Xanthan Gum. The peak at 1590-1650 cm-1 shows the overlap of amide group in chitosan and carboxyl anion group in Xanthan Gum due to the combination of and . Broadened peak at due to the combination of , and stretching indicates the presence of intermolecular hydrogen bonds in [4].
Figure 3.b shows the XRD spectra of the synthesised chitosan (CS), Xanthan Gum (XG) and XG. . Chitosan shows a broadened peak at which indicates the attribution of semicrystalline polysaccharides. Xanthan gum also shows a broadened peak at which indicates similar to chitosan. Meanwhile, XG.SiO2 showed a broadened peak at ; slightly larger than the value of Xanthan Gum. This peak indicates the presence of mesoporous SiO 2 and looks widened which indicates that the mesoporous SiO 2 formed is included in the amorphous compound [4]. The following is an analysis of the crystallinity of the synthesised material.

Tabel 3. Crystallinity of Material Synthesised Based on XRD Data

Table 3 shows that CS/XG.SiO2experienced a reduction in crystallinity to compared to chitosan (CS), Xanthan Gum (XG), and XG. . This means that has an increasingly amorphous and porous form so that the surface area is getting bigger and has a positive impact on MB adsorption.

Fig. 9. Scanning Electron Microscopy Result of at various magnifications a) 500x, b) 2000 x , dan c) 5000x.

Fig. 9. Scanning Electron Microscopy Result of at various magnifications a) 500x, b) 2000 x , dan c) 5000x.

After all materials were tested with FTIR and XRD, CS/XG.SiO2 adsorbent was tested with SEM to see the morphology or surface of the material. Figure 9 shows the results of SEM testing of at various magnifications. At 5000x magnification (Figure 9.c), it can be seen that the surface of the synthesised has a rough and porous surface and does not show a shape with a separate phase. This indicates that CS and are suitable if combined into a single material into a hydrogel. In addition, the thickened layer shows that there is a coupling interaction between chitosan and XG. [4].

Testing Photodegradation Ability of CS/XG.SiO2

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Here is the methylene blue calibration curve at maximum wavelength ( ) nya ( 668 nm ) to determine the concentration of methylene blue before and after the test.

Fig. 10. Calibration Curve of Methylene Blue at

Fig. 10. Calibration Curve of Methylene Blue at

Based on Figure 10, the equation of the calibration straight line is with a value of curve is 0.99668 which is close to the value of one and the P -value which indicates that the correlation value is very good so that the curve is accurate in predicting the MB concentration value before and after the test.
Variable testing was based on the Box-Behnken statistical method of three variables, namely , MB concentration (B) in ppm, and time (C) in minutes consisting of 15 runs with the following experimental % photodegradation results.

Table 4. Photodegradation Testing Results with Box-Behnken Design

Run | Coded Level of Variables | Experimental Variables | % Degradation
| A | B | C | A | B | C |
1 | 1 | 0 | -1 | 11 | 12,5 | 30 | 60,3
2 | 0 | 1 | 1 | 7 | 20 | 120 | 73,5
3 | 0 | 0 | 0 | 7 | 12,5 | 75 | 53,3
4 | -1 | 1 | 0 | 3 | 20 | 75 | 9,7
5 | 1 | -1 | 0 | 11 | 5 | 75 | 73,2
6 | 0 | -1 | -1 | 7 | 5 | 30 | 51,6
7 | 1 | 1 | 0 | 11 | 20 | 75 | 63,0
8 | 0 | 0 | 0 | 7 | 12,5 | 75 | 55,2
9 | 0 | 0 | 0 | 7 | 12,5 | 75 | 51,6
10 | -1 | -1 | 0 | 3 | 5 | 75 | 10,9
11 | -1 | 0 | -1 | 3 | 12,5 | 30 | 8,1
12 | 1 | 0 | 1 | 11 | 12,5 | 120 | 71,1
13 | 0 | 1 | -1 | 7 | 20 | 30 | 42,3
14 | 0 | -1 | 1 | 7 | 5 | 120 | 89,0
15 | -1 | 0 | 1 | 3 | 12,5 | 120 | 16,0

Analysis of Variance (ANOVA), Residual, dan Prediction Model

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Statistical analyses were performed using Design Expert v11 software. ANOVA study was conducted on the developed model to determine the significance of the main factors affecting the response rate of the photocatalytic process and the results are presented in Table 4. The most suitable model is with and predicted values close to one, namely the quadratic model, with , and C are linear factors, , and are quadratic factors, and are , and interaction factors, respectively.

Table 5. ANOVA Analysis of Quadratic Model Experiments

Source | F-value | P-value | Significance | R² | Predicted R²
Model | 230.84 | < 0.0001 | Significant | 0.9976 | 0.9648
A | 1455.78 | < 0.0001 | Significant
B | 11.59 | 0.0192 | Significant
C | 103.61 | 0.0002 | Significant
AB | 0.0952 | 0.7701 | Not significant
AC | 14.43 | 0.0127 | Significant
BC | 0.0041 | 0.9515 | Not significant
A² | 466.07 | < 0.0001 | Significant
B² | 2.35 | 0.1855 | Not significant
C² | 6.27 | 0.0542 | Not significant
Lack of Fit | 6.08 | 0.1445 | Not significant |  |

Specifically, the F -value and P -value were used to determine the significance of each coefficient of the developed mathematical model. The F-value and P -value of the model were calculated to be 230.84 and , respectively. This implies that the independent variables used in the modelling are significant for the modelling of methylene blue photodegradation by . P -value indicates that the factor used is significant. In this case, the linear factors , and C , the quadratic factor , and the interaction AC were significant for the modelling of MB photodegradation. Whereas, the factors , and are not significant enough but necessary to determine the relationship between independent variables. The large P-value of Lack of Fit, indicates that there is no significant evidence to reject the null hypothesis, indicating that the model fits the data. This is also consistent with the residual analysis and model predictions as follows.

Fig. 11. Graphs a. Normal Plot of Residuals and b. Predicted vs Actual Data

Fig. 11. Graphs a. Normal Plot of Residuals and b. Predicted vs Actual Data

Based on Figure 11.a, it is found that the residual values are normally distributed around a straight line and in Figure 11.b, the predicted values are distributed close to the actual values so that the data obtained are valid and the prediction model can be used. In addition, the prediction value is 0.9648 which shows the model is accurate in predicting the results. The final equation of the Box-Behnken design quadratic model obtained is as follows.

Effect of Free Variables on % Degradation of Methylene Blue

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Analysis of the effect of the variables pH , methylene blue concentration, and irradiation time was carried out using 3D surface response graphs plotted to determine the effect of experimental variables on the response as follows.

Fig. 12. 3D Surface Response Graph of Interaction Between Two Variables on Methylene Blue Photodegradation

Fig. 12. 3D Surface Response Graph of Interaction Between Two Variables on Methylene Blue Photodegradation

Figure 12.a shows the effect of pH and initial concentration of methylene blue on the percentage degradation of methylene blue. The degradation efficiency gradually increased from pH 3 to pH 10 and finally decreased from pH 10 to pH 11 at constant MB concentration. This is because the surface charge of adsorbent depends on the protonation and deprotonation of functional groups so that changes in pH can change the surface charge. The MB removal rate is maximum in the red coloured region, precisely at pH around 10 . This is due to the weak electrostatic attraction between the negative groups of the dye and the positive groups of the adsorbent at higher pH levels (7-10). When the pH exceeds 10 , the OH concentration gradually increases and OH and MB become increasingly competing for binding to the CS/XG. surface, thus reducing MB interaction and degradation efficiency [4].

Fig. 13. Interaction of with Methylene Blue

Fig. 13. Interaction of with Methylene Blue

At constant pH , the photodegradation efficiency increased with the increase of irradiation time with an optimum condition of 120 minutes as shown in Figure 12.b This is because the longer the irradiation time, the more energy received by degrade methylene blue. Whereas, at constant time, the photodegradation efficiency first increases when the MB concentration is lower
until a peak and finally decreases when the MB concentration is higher. As shown in Figure 12.c, the optimum state is at 5 ppm MB . When MB is present at a low concentration, the active sites of the adsorbent are empty and sufficient to adsorb a large number of dye molecules. However, at high initial MB concentrations, the number of fixed active sites becomes easily filled, making MB photodegradation more difficult [4].

Free Variable Optimisation with Box-Behnken Design

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Optimisation of the independent variables was carried out using the previously calculated mathematical model equations to obtain the point with the highest % degradation. The following is an analysis of determining the point with three optimum variables.

Fig. 14. 2D Graph of Free Variable Optimisation Determination

Fig. 14. 2D Graph of Free Variable Optimisation Determination

Based on Box-Behnken design analysis, the point with optimum % degradation is located at the centre of the red colour, precisely at concentration , and irradiation time of 119.67 minutes with a predicted % degradation of 103.5%. After experimentation with the optimum variables, the degradation was . These results confirm the validity of the mathematical model of photodegradation of the synthesised CS/XG.SiO2 material.

Reusability Analysis of CS/XG.SiO2

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Reusability analysis is used to test the reuse of . The following is a graph of reusability.

Fig. 15. Graph of % MB Degradation on Reuse of

Fig. 15. Graph of % MB Degradation on Reuse of

Based on Figure 15, after the reuse of the percent degradation only decreased from to which indicates is effective when used repeatedly.

Analysis of MB Photodegradation Kinetics with CS/XG.

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The kinetics of methylene blue photodegradation with was conducted to obtain the rate constant value of methylene blue photodegradation. In this study, four commonly used kinetic models namely order 0, 1, 2, and modified Elovich were investigated using data generated from experimental processes at optimum conditions after Box-Behnken optimisation.

Fig. 16. Model Graph of Photodegradation Kinetics of MB with

Fig. 16. Model Graph of Photodegradation Kinetics of MB with

With parameter values for each kinetics model as follows.

Table 6. Parameter Values of Each MB Photodegradation Kinetics Model

Kinetics Model | Parameter | Value | Kinetics Model | Parameter | Value
0 Order | k (ppm.minute) | 0,0025 | 1st Order | k (/minute) | 0,0007
[A]₀ Calc. (ppm) | 3,5027 | [A]₀ Calc. (ppm) | 3,5041
[A]₀ Exp. (ppm) | 3,5126 | [A]₀ Exp. (ppm) | 3,5126
R² | 0,9766 | R² | 0,9778
2nd Order | k (L/mg.minute) | 0,0002 | Modified Elovich (β = 2) | k (/minute) | 0,0010
[A]₀ Calc. (ppm) | 3,5057 | [A]₀ Calc. (ppm) | 3,5150
[A]₀ Exp. (ppm) | 3,5126 | [A]₀ Exp. (ppm) | 3,5126
R² | 0,9789 | R² | 0,9805

Of the four models, the closest value model to one is the Modified Elovich model, which is 0.9805 which shows a very good correlation in the photodegradation of methylene blue by . This indicates that the methylene blue removal process consists of chemical adsorption and photodegradation processes that run synergistically [9]. The photodegradation rate constant value based on the Modified Elovich model is .

Summary

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CS/XG. hydrogel bio-composite has been successfully synthesised by combining chitosan (CS) compounds from green mussel shells (Perna viridis) and Xanthan Gum Silica (XG. SiO2) as shown by the results of FTIR, XRD, and SEM characterisation. The results showed that the optimum condition of photodegradation occurred at concentration of 5.054 ppm ; and UV irradiation time for 119.67 minutes. Under the optimum conditions, the % degradation was 94.2%. After the 5th reuse of CS/XG.SiO2, the %degradation only decreased from 94.2% to 79.4%, indicating that was effectively used repeatedly. The photodegradation kinetic rate constant value was based on the Modified Elovich model with . These findings highlight the strong potential of the CS/XG. hydrogel bio-composite for real-world applications, particularly in the treatment of textile wastewater containing dye pollutants. For future research, scaling up the synthesis process and exploring the use of visible light sources for photodegradation are recommended to further enhance the practicality and sustainability of this material in industrial settings.

References

The original version of this paper is available on https://www.scientific.net/EC.11.25.pdf

E. Erwanto, Y. Yulinda, and Q. Nabela, "Pengaruh Penambahan Ion Nitrat ( ) Terhadap Kinetika Fotodegradasi Zat Warna Metilen Biru Menggunakan Zeolit-TiO2," Jurnal Inovasi Teknik Kimia, vol. 5, no. 2, 2020.

B. Hastuti and N. Tulus, "Sintesis kitosan dari cangkang kerang (Anadara inflata) sebagai adsorben ion , " presented at the Seminar Nasional Kimia dan Pendidikan Kimia VII, 2015.

A. Huda, "Analisis Proses Adsorpsi Pewarna Methylene Blue Menggunakan Kitosan Hasil Ekstraksi dari Black Soldier Fly," Dissertation, Universitas Pertamina, 2023.

A. Rahmatpour and A. H. A. Hesarsorkh, "Chitosan and silica nanoparticles-modified xanthan gum-derived bio-nanocomposite hydrogel film for efficient uptake of methyl orange dye," Carbohydrate Polymers, art. no. 121721, 2023.

A. Ahmadi, M. Hajilou, S. Zavari, and S. Yaghmaei, "A comparative review on adsorption and photocatalytic degradation of classified dyes with metal/non-metal-based modification of graphitic carbon nitride nanocomposites: Synthesis, mechanism, and affecting parameters," Journal of Cleaner Production, vol. 382, art. no. 134967, 2023.

H. F. Aly and A. I. Abd-Elhamid, "Photocatalytic degradation of methylene blue dye using silica oxide nanoparticles as a catalyst," Water Environment Research, vol. 90, no. 9, pp. 807-817, 2018.

R. Firyanto, "Pemanfaatan Kitosan dari Limbah Cangkang Kerang Hijau (Perna viridis) sebagai Adsorban Logam Cu," Jurnal Teknik Kimia, vol. 23, no. 1, 2019.

J. Weißpflog, D. Vehlow, M. Müller, B. Kohn, U. Scheler, S. Boye, and S. Schwarz, "Characterization of chitosan with different degree of deacetylation and equal viscosity in dissolved and solid state-Insights by various complimentary methods," International Journal of Biological Macromolecules, vol. 171, pp. 242-261, 2021.

N. Hamri, A. Imessaoudene, A. Hadadi, S. Cheikh, A. Boukerroui, J. C. Bollinger, et al., "Enhanced adsorption capacity of methylene blue dye onto kaolin through acid treatment: Batch adsorption and machine learning studies," Water, vol. 16, no. 2, art. no. 243, 2024.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 39-52

doi: 10.4028/p-QWZ5u3

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

Submitted:
2025-05-01

Revised:
2025-07-12

Accepted:
2025-07-25

Online:
2025-09-10

Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

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I.G. Mkhize , E. Igberase

Durban University of Technology, Department of Chemical Engineering, Steve Biko Campus, Durban, South Africa

Email: ainnocentiaM2@dut.ac.za, *Email: bephraimi@dut.ac.za

Keywords: Simulation; Regeneration; Sustainable adsorbent; Adsorption kinetics, GCCHI beads, chitosan-chitin adsorbent, heavy metal removal, breakthrough analysis, Swan model.

Abstract

Water pollution by heavy metals constitutes a significant environmental and health risk, necessitating efficient and reusable adsorbents. The current study investigates the application of inexpensive biopolymer chitosan to extract and ions from aqueous solutions. Material characterization using X-ray diffraction (XRD) showed the amorphous nature (absence of peak at ), and Brunauer-Emmett-Teller (BET) analysis exhibited the mesoporous surface area of , suitable for the adsorption of metal ions. The Swan model was parameterized with batchderived adsorption parameters (i.e., for for ) and successfully predicted packed-bed breakthrough curves at optimum pH ( 7 for , 6 for ), with transport rates of and for a 1.2 m column. The material retained over removal efficiency after five regeneration cycles. These findings show the potential of chitosan for large-scale water treatment with high efficiency, model-driven design, and strong reusability.

Introduction

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Heavy metal pollution remains one of our most pressing environmental challenges, with cadmium ( ) and nickel ( ) representing persistent and toxic threats to ecosystems and human health. These hazardous metals are primarily discharged from industrial processes like metal plating, mining, and steel production [1,2]. They bioaccumulate in living organisms and, according to the United States Environmental Protection Agency (USEPA), can cause serious health issues such as cancer and organ damage [3]. Chitosan has attracted interest as a biosorbent due to its biocompatibility and metal-binding properties. However, its real-world use is limited by poor acid stability, low adsorption capacity, and inadequate selectivity in mixed-metal environments.

In this study, grafted-cross-linked chitosan (GCCHI) beads were developed as an innovative adsorbent material that offers enhanced performance for real-world water treatment applications. The research establishes three key advances: firstly, the authors demonstrated how strategic material modification through cross-linking with chloromethyl oxirane and subsequent grafting with polydopamine improves acid stability, adsorption capacity, and selectivity for target metals. Secondly, the authors provided the first comprehensive evaluation of chitosan-based adsorbents for competitive and removal under environmentally relevant conditions, filling a crucial gap in existing literature that predominantly focuses on single-metal systems. Thirdly, the Swan model was implemented as a predictive tool for column kinetics, enabling more accurate scaling from laboratory experiments to potential industrial applications.

The novelty of this work lies in its integrated approach that combines material science innovation with practical engineering considerations. Unlike previous studies that examined adsorption performance in isolation [4] This study systematically evaluates both the fundamental adsorption mechanisms and the operational parameters critical for real-world implementation. The GCCHI beads developed here exhibit exceptional regeneration capability, maintaining over of their initial adsorption capacity through multiple cycles. They significantly improve over conventional chitosan
adsorbents that typically show rapid performance degradation. Furthermore, the successful application of the Swan model provides a valuable tool for process optimization, addressing a longstanding challenge in translating batch adsorption results to continuous flow systems. Unlike conventional models like Thomas or Yoon-Nelson, the Swan model was utilized because it can predict column behavior directly from batch-derived parameters without further calibration. Its mechanistic description particularly includes film diffusion and intraparticle diffusion resistances, essential in properly simulating transport in porous chitosan-based adsorbents [5]. The model operates with zero initial concentration and constant inlet concentration boundary conditions. Established for chitosan systems to within error in breakthrough curve predictions, the Swan model has variable process conditions like flow rates and bed heights of . With this combination of features, scaling from laboratory to plant scale can be done more accurately, and information regarding rate-limiting adsorption mechanisms can also be obtained. The established efficacy of the model using biopolymer adsorbents and its ability to bridge batch and continuous-flow systems make it particularly appealing to evaluate the effectiveness of GCCHI beads for use in water treatment processes. This work advances our understanding of chitosan-based metal adsorption by bridging the gap between material development and process engineering. It provides a practical framework for developing more effective water treatment technologies. The findings offer tangible solutions to current limitations in heavy metal remediation while establishing methodologies that can be extended to other challenging wastewater contaminants.

Experimental

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Adsorbent production process

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Chitosan powder was purchased from Fengchen Group, China, while chloromethyl oxirane, acetic acid, sodium hydroxide, and polydopamine were purchased from Sigma-Aldrich, South Africa. The conversion to grafted chitosan composites (GCCHI) involves a dissolution of 30 grams of chitosan powder in a 10 percent acetic acid solution of one liter. For the cross-linking reaction, a solution of chloromethyl oxirane is added and thoroughly stirred for 2 hours. The formed solution is pumped to a bath of 1 M sodium hydroxide, where precipitation of solid CCHI beads occurs. To accomplish the grafting step, 5 g of such beads are mixed with polydopamine solution in the open-neck flask. The mixture is irradiated using high-power microwaves at medium-low power. Polydopamine is used as a flexible cross-linker that can improve the adhesion abilities of the beads, and this is done within a 20 -minute process. The last step makes it possible to functionalize the chitosan composite material further.

Characterization of adsorbent

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The Shimadzu XRD model 7000 was used to capture diffraction patterns, which were obtained using a Bruker D8 Advance diffractometer (Germany) using radiation ( ), and the intensities were recorded in a range from 10 to 90 degrees. Nitrogen adsorption measurement at 77 K was used to characterize the specific surface area of beads, pore volume, and pore size. The Brunauer-Emmett-Teller (BET) technique was employed to analyze the nitrogen adsorption isotherms and calculate the surface area and porosity of the beads. A Micromeritics Tristar 3000 coupled analyzer (Tokyo, Japan) was used for the analysis.

Packed Bed Adsorption Experiment

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The packed bed adsorption experiment was conducted in a glass cylindrical polystyrene column that measured 0.587 meters in depth and had an interior diameter of 0.0342 meters. The column was loaded with pre-activated GCCHI beads to achieve the height of 1.2 m . The investigation was carried out at room temperature, employing atomic absorption spectrometry to examine the and ions in the aqueous mixture before and after adsorption, explicitly using a Varian SpectrAA-10 for this analysis. 85 grams of GCCHI were used for this experiment. During the experiment, the solution pH was kept constant ( 7 for and 6 for ). Using pH 7 for offers the optimal deprotonation of chitosan
amino groups for optimum metal binding without nickel hydroxide precipitation. For , the optimal pH is 6 to ensure sufficient accessibility of the amines while avoiding premature cadmium hydrolysis. Both values ensure optimal efficiency in adsorption and ensure metal ion solubility. They are also conditions identified by earlier experimental work that are optimal [6]. The selection of pH ensures a realistic representation by the Swan model for packed bed columns.
The experimental setup allowed for the precise measurement of the concentration of and ions before and after the adsorption process. This was essential for determining the adsorption efficiency and capacity of the GCCHI beads. The use of atomic absorption spectrometry provided a reliable method for quantifying the metal ions, as it is well-established in the literature for its accuracy and sensitivity in detecting trace metals in various matrices [7].

Isotherm experiment

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Isotherm tests placed 4 g of GCCHI beads into 250 mL Erlenmeyer flasks, each filled with 100 mL of nickel and cadmium solution at an initial concentration. The initial concentration was made from a stock solution and then adjusted to the optimal pH . The Erlenmeyer flasks were placed in a labcon incubator for 50 minutes at an agitation speed of 120 rpm to achieve equilibrium. Isotherms were carried out at room temperature. Following equilibrium, a transparent metal solution was collected and examined using an atomic absorption spectrophotometer (Varian SpectrAA-10) obtained from Tokyo, Japan, to determine the amount of metal ions adsorbed. The equilibrium adsorption capacity was calculated from the mass balance equation as shown in Eq.1.

Where is the equilibrium adsorption capacity, and are the initial and equilibrium concentration ( ) of heavy metal ion in solution, respectively. At the same time, is the volume and is the weight of the adsorbent.

Kinetic experiment

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4 g of GCCHI beads were combined with 100 mL of metal ion solution in a 250 mL Erlenmeyer flask with starting concentrations. The initial concentration was derived from a stock solution and then adjusted to the desired pH . To achieve equilibrium, the Erlenmeyer flasks were put in a labcon incubator, and the solutions were shaken at 120 rpm at room temperature. Samples were obtained at intervals of 30 minutes, 60 minutes, 90 minutes, 120 minutes, and 150 minutes and evaluated for metal ion removal using an atomic absorption spectrophotometer.

Langmuir and Freundlich Models for Adsorbent Binding Capacity

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Adsorption isotherms are essential for evaluating how the adsorption process functions, particularly in determining the binding capacity of adsorbents. Two widely used models, the Langmuir and the Freundlich isotherms, are often applied for this purpose. The Langmuir model assumes monolayer adsorption, meaning that adsorption occurs at specific homogeneous sites on the adsorbent surface, leading to single-layer adsorption. This behavior is mathematically represented by the linear form of the Langmuir isotherm, shown in Eq. 2 [8].

The Langmuir constant represents the maximal adsorption capacity, while the bonding energy of adsorption is shown by . The shows how to affirm that the adsorbate ions are bound to GCCHI beads. Greater values denote substantially enhanced metal ion binding affinities. The slope and intercept of vs Ce might be used to determine the parameters of the Langmuir model. The separation factor ( ), which was employed to assess whether an adsorption system is favorable or unfavorable, as given in Eq. 3, can be used to represent the fundamental properties of the Langmuir model. RL greater than , and RL between 0 and 1 denote unfavorable, linear, and favorable circumstances.

Considering how diverse surfaces interact in equilibrium, the Freundlich isotherm was developed. The isotherm originates from the notion that the distribution of adsorption sites is connected substantially to the degree of adsorption. It also suggests that the higher the adsorption sites, the quicker they saturate [9] Eq. 4 gives this model's linear description.

The constants and n correspondingly signify the adsorption intensity and capacity. The adsorbent's likelihood of being classified as more reactive increases with increasing values [10,11] The slope and intercepts of the logqe against the logCe plot can be used to determine the parameters of this model. The range of n values should be between 1 and 10 .

Influence of Kinetic Models

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The process dynamics play a critical role in determining the residence time of adsorbate ions, with kinetic models frequently employed to explore these effects. Among the most widely used are the pseudo-first-order kinetics, introduced by Lagergren, and the pseudo-second-order kinetic model, as represented in Eqs. 5 and 6. These models are essential for analyzing the mechanisms that control adsorption processes, offering insights into the underlying factors regulating ion interactions and system efficiency.

Correspondingly, qe and qt represent the proportion of metal ions absorbed on the adsorbent ( ) at equilibrium and time t . The pseudo-first-order kinetics' rate constant is . The straight-line plot of versus Allows for the determination of the rate constant.

Where is the rate constant for a pseudo-second-order model, and and have the same definitions. Eq. 6 slope and intercept of the fitted line of vs. t determines the values of and .

Evaluation of Model Accuracy through Error Analysis

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The effectiveness of the pseudo-first-order and pseudo-second-order kinetic models was evaluated by applying Marquardt's percent standard deviation (MPSD) test, as illustrated in Eq. 7. This nonlinear statistical method compares experimental data against predicted data concerning the equilibrium adsorption capacity qe.

where N is the number of measurements, P is the number of parameters in the model, and are experimental and predicted uptake rates, respectively.

Column Regeneration

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Desorption investigations commenced when the outlet concentrations of and ions were close to the inlet concentrations. The spent GCCHI beads underwent several washes in 2 L of purified water before desorption. Subsequently, the column was vacuum dried to ensure complete surface drying before desorption with 0.1 M HCl at a rate. After the regeneration procedure, the

GCCHI beads were rinsed with purified water to remove excess acid. The vacuum drying method utilized in this study ensured that the GCCHI beads were adequately dried, which is crucial for the subsequent desorption phase.

Application of the Shrinking Core Model to Adsorption Kinetics

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The shrinking core model was utilized to elucidate the kinetics of adsorption processes. The emphasis on the model is described in the work of [12]. This model posits that the adsorbate is confined within an active core. This suggests that intraparticle dispersion through the adsorbate-filled shell is the primary resistance to mass transfer during the uptake process. This phenomenon adheres to the distribution equation presented in Eq. 8.

However, various studies have employed empirical correlations to estimate the mass transfer coefficient, as demonstrated in [13,14]. The semi-empirical relationship outlined in Eq. 9 was utilized to facilitate this estimation.

In which the Reynolds number, Re, has no dimensions, The Schmidt number, Sc, has no dimensions. And the Sherwood number, Sh, has no dimensions,
where is the efficient dispersion coefficient is the bulk mixture ion concentration is the radius of the bead It is the metal ion density and the fraction filled capacity.

The ratio of metal loading to total capacity varies from the initiation of binding until equilibrium is reached. This ratio, denoted as ( ), is represented in Eq. 10. Furthermore, the effective dispersion coefficient can be determined by fitting it to Eq. 8, utilizing equilibrium values obtained from the experimental assessment of time-dependent binding alongside the achieved value.

Results and Discussion

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XRD analysis of CHI, CCHI, and GCCHI Beads

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X-ray diffraction (XRD) was carried out on a Bruker D8 Advance diffractometer (Germany) using a radiation source ( , anticathode: copper). The diffractometer was operated at 40 kV and 40 mA using a to scan range with a step size of and a scan rate of . XRD analysis of CHI, CCHI, and GCCHI beads revealed distinct peak patterns influencing their adsorption performance. The CHI beads exhibited a characteristic peak at ( 110 planes), consistent with the literature [15], indicating a densely packed structure that may limit functional group accessibility. In contrast, CCHI beads retained this peak but required cross-linking for acidic stability. GCCHI beads showed a shifted peak at with reduced intensity, signaling lower crystallinity due to disrupted hydrogen bonds from grafting. This structural loosening enhanced adsorption by exposing more groups. The amorphous nature of GCCHI, evidenced by broader peaks and loss of the peak, correlated with higher surface area availability [15]. Aligning with its superior adsorption capacity. These findings underscore the crystallinity-adsorption
trade-off: ordered structures hinder metal ion access but improve robustness, while amorphous domains optimize binding sites at the expense of durability. The Swan model effectively linked these structural changes to dynamic adsorption behavior, supporting tailored material design for water treatment applications.

Fig. 1. XRD pattern of (a) CHI, (b) CCHI, and (c) GCCHI beads, respectively.

Fig. 1. XRD pattern of (a) CHI, (b) CCHI, and (c) GCCHI beads, respectively.

Surface Area and Porosity Characterization of Chitosan Beads Using BET and BJH Techniques.

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The nitrogen adsorption-desorption isotherms in Figures 2a and 2b were applied to assess surface area and the pore size distribution on CHI , CCHI , and GCCHI using the BET and BJH methods. Significant variations in the isotherms are due to the mesoporous structure of the beads. The GCCHI bead sample shows the type IV isotherm characterized by a large hysteresis loop and high relative pressure factor. In contrast, CHI and CCHI bead samples show typical adsorption behavior. Quantitative studies show that the surface area and pore volume of the GCCHI beads are observably greater than those of CHI and CCHI samples.
The pore volume of the CHI, CCHI, and GCCHI beads is , and , respectively, while the surface area is , and , respectively. The increase in BET surface area and pore volume for the GCCHI beads is mainly because of the development of new pores, a process caused by introducing additional amine groups as pillars into the bead matrix. Such increased porosity and surface area of the GCCHI beads enable greater efficiency in adsorption and desorption processes of pollutants, thereby increasing their potential in environmental remediation applications. Such findings have also been reported in other research [16]. Highlighting the significance of structural modification in improving biopolymer materials' adsorption capacity.

Fig. 2. Nitrogen adsorption/desorption isotherms at 77 K for GCCHI beads, (a) BET, (b) BJH technique.

Fig. 2. Nitrogen adsorption/desorption isotherms at 77 K for GCCHI beads, (a) BET, (b) BJH technique.

Evaluation of Breakthrough Curves forandAdsorption in a Column System

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The breakthrough profiles for the adsorption of metal ions were evaluated under a controlled experimental setup characterized by a bed height of 1.20 m , a constant flow rate of , and an inlet concentration of [14]. The input parameters utilized in the column model are detailed in Table 1.

Table 1. Variables applied in predicting experimental data.

Variables | Amount
Weight of wet beads (g) | 85
Average adsorbent size (mm) | 1.3
Density ρ (kg/m³) | 1100
Surface area per unit weight, α m²/kg | 88.7
The pH of the mixture of cadmium | 6.0
The pH of the mixture of nickel | 7.0
Equilibrium constant | 2.5×10⁻³
GCCHI beads capacity (mmol/g) | 5.2
n and m | 1.0
Adsorbate's molecular diffusion coefficient in water (m²/s) | 2.0. 10⁻⁹
Adsorbate's external mass transfer coefficient, k (m/s) | 3.92. 10⁻⁶

Figures 3a and 3b present the breakthrough curves for and ions, respectively. A particle model was formulated to represent the experimental breakthrough curves, as shown in Eq. 8. The Swan model was employed due to its superior predictive capabilities regarding the experimental breakthrough curves, mainly by incorporating pH equilibrium values. The pH model is instrumental in calculating equilibrium results, which subsequently allows for determining the maximum adsorption capacity ( ) and the equilibrium constant ( ) from the equilibrium data.

Fig. 3. Breakthrough curves for the adsorption of (a) and (b) ions onto GCCHI beads, with a flow rate of , influent concentration of , and temperature of .

Fig. 3. Breakthrough curves for the adsorption of (a) and (b) ions onto GCCHI beads, with a flow rate of , influent concentration of , and temperature of .

The external mass transfer coefficient, a critical parameter in the modeling process, was derived through an empirical relationship between the Reynolds and Schmidt numbers, as articulated in Eq. 9. The diffusion coefficients were iteratively adjusted to achieve a satisfactory fit between the model and the experimental data. The diffusion coefficients were established at for ions and for ions. The agreement between the model predictions and experimental breakthrough curves confirms the model's credibility for predicting adsorption processes.

Kinetic Parameter Analysis of Metal Ion Adsorption onto GCCHI Beads

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The kinetic parameters for the batch mode adsorption of metal ions onto GCCHI beads are summarized in Table 2. The data indicate a clear preference for the pseudo-second-order kinetic model over the pseudo-first-order model in describing the adsorption of and ions. Specifically, the correlation coefficients ( ) for the pseudo-second-order model are significantly higher, approaching unity, which suggests a better fit to the experimental data than the pseudo-firstorder model. The experimental qe values were 1.89 and for and ions, respectively. This observation aligns with findings from previous studies that emphasize the effectiveness of the pseudo-second-order model in capturing the kinetics of metal ion adsorption, indicating that the adsorption process is likely governed by chemisorption mechanisms involving interactions between the adsorbent's functional groups and the metal ions [17]. The Mean percentage standard deviation (MPSD) values further corroborate these findings, with lower MPSD values for the pseudo-second-order model indicating a strong agreement between experimental and predicted data. Conversely, the higher MPSD values associated with the pseudo-first-order model reflect a poor fit, reinforcing the conclusion that the pseudo-second-order model is more suitable for these adsorption processes [18]

Table 2. Kinetic variables for the adsorbate binding onto GCCHI beads at (7) and (6), 120 RPM of agitation, and 70 min of contact.

Metal
ions
Pseudo-first-order parameters
Pseudo-second-order parameters

k₁
(min⁻¹)
qe(pred)
(mmol/g)
MPSD
R²
k₂
(g/mmol.min)
qe(pred)
(mmol/g)
MPSD
R²

Ni²⁺
0.04
2.21
9.34
0.78
7.44
1.55
0.45
0.97

Cd²⁺
0.01
1.87
10.65
0.73
7.14
1.86
1.11
0.97

Isotherm result

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The correlation coefficient ( ) was assessed to measure the effectiveness of the used models. Table 3 lists the isotherm model variables for adsorbate binding onto GCCHI at room temperature. readings for the adsorption of and ions onto GCCHI beads suggest that the results are well characterized by the Langmuir model ( ), as opposed to the Freundlich model value ( ). The maximum adsorption capacity ( ) obtained from the Langmuir model was 220 and for and ions, respectively. The ' ' values for the and ions were 0 and 0.38 , respectively. These values indicate a better adsorption mechanism [19].

Table 3. Binding of metal ions onto GCCHI beads at room temperature analyzed according to the Langmuir and the Freundlich isotherm models.

Pollutants
Langmuir parameters
Freundlich parameters

Qmax
(mg/g)
RL
(L/mg)
R²
n
Kf (mg/g)
R²

Ni²⁺
220
0.66
0.99
4.45
14.87
0.74

Cd²⁺
226
0.37
0.99
4.32
14.11
0.72

Qmax Comparison

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The maximum adsorption capacity obtained in this study was compared with that in the literature for the adsorption of and ions on various adsorbents (Table 3). It can be shown that GCCHI beads are highly effective for removing metal ions.

Table 3. Adsorption capacity comparison with other adsorbents.

Adsorbent | Target Metal | Max Adsorption Capacity (mg/g) | Reference
GCCHI beads (hypothetical) | Ni²⁺ | 220 | This study
| Cd²⁺ | 226 | This study
Fe₃O₄-ZrO₂@APS nanocomposite | Ni²⁺ | 128 | [20]
| Cd²⁺ | 113 | [20]
Zeolite | Cd²⁺ | 48.63 | [21]
Activated carbon | Ni²⁺ | 100 | [22]
Montmorillonite (Fe-modified) | Cd²⁺ | 5.86 | [23]

Regeneration and Recovery of Metal Ions from Utilized GCCHI Adsorbents

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The rapid elution of and from GCCHI beads achieves remarkable concentration enrichment, desorbing ions from an initial to over (Table 4). This process occurs as protons displace metal ions from binding sites, with the beads' porous structure facilitating migration into
solution. Internal diffusion emerges as the rate-limiting step, while decreasing recovery efficiency across cycles reflects active site saturation and potential complex formation. pH -dependent surface charge and metal speciation further influence desorption effectiveness, consistent with established adsorption principles.

Table 4. Removal efficiency of and ions at each stage of desorption

Degradation circle | Removal efficiency for Ni²⁺ ions | Removal efficiency for Cd²⁺ ions
1st circle | 98.21 | 96.78
2nd circle | 98.33 | 96.98
3rd circle | 98.48 | 96.95
4th circle | 98.45 | 96.92
5th circle | 98.22 | 96.56

Desorption of and ions occurred rapidly within the first 30 minutes (Figure 4), followed by a gradual decline in concentration, indicating varying rates throughout the process. The results align with studies using 1 M HCl for efficient adsorbent regeneration [3], confirming its effectiveness for heavy metal recovery. These findings underscore the importance of modeling desorption kinetics to optimize adsorption-desorption cycles.

Fig. 4. Regeneration curves for and ions employing a flow rate of 0.1 M HCl mixture.

Fig. 4. Regeneration curves for and ions employing a flow rate of 0.1 M HCl mixture.

Durability and Efficiency of GCCHI Beads in Adsorption-Desorption Cycles

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Five consecutive adsorption-desorption cycles demonstrated the reusability of GCCHI beads, with breakthrough curves revealing consistent performance (Figure 5). While the beads maintained stable mass retention and adsorption capacity in the first cycle, subsequent cycles showed a gradual mass loss ( ) and a slight improvement in removal efficiency from cycles 2 to 4, likely due to acidinduced pore opening and improved bead uniformity. However, long-term durability remains challenging, as declining adsorption efficiency and structural stability were observed in later cycles.

Despite this, GCCHI beads outperformed many chitosan-based adsorbents in the literature [24,25] highlighting their potential for practical applications with further optimization. Most research indicates chitosan derivatives lose capacity after five cycles [26,27]. The developed adsorbent maintains more than efficiency for and even after several regenerations. The finding indicates that GCCHI beads perform better than pure chitosan and compete with modified composites in reusability. The future development of GCCHI beads for widespread adsorption requires either matrix changes to chitosan materials or protective chemical implementation to enhance operational stability.

Fig. 5. Breakthrough curve for the five cycles of (a) and (b) ions adsorption onto GCCHI beads.

Fig. 5. Breakthrough curve for the five cycles of (a) and (b) ions adsorption onto GCCHI beads.

Mechanisms and Real-world Relevance

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The and adsorption on GCCHI beads is chelation-induced via metal ion-functional group interactions of chitosan and pH -dependent electrostatic interactions. Kinetic changes are observed upon breakthrough curves in which is typically marked by delayed breakthrough compared to , since is a softer Lewis acid with a higher binding affinity. The shape of the curves shows the adsorption kinetics, whereby steeper slopes indicate higher kinetics governed by pore diffusion and less steep slopes indicate surface diffusion control. As far as applications are concerned, the adsorption capacity and regenerability of the GCCHI beads position them to be applied for industrial wastewater treatment, particularly in metal plating and mining industries, where heavy metal pollution is prevalent. The ability to reuse and regenerate the beads on multiple occasions without any loss in performance presents an economic option over conventional treatment techniques. Also, the soundness of applying the Swan model to simulate breakthrough behavior makes it possible for water treatment systems to be designed on a scale that will fulfill environmental standards for heavy metal discharge. This approach not only overcomes the technical issues in water purification but is also a sustainable practice that employs a biodegradable adsorption material. This work illustrates that combining material science with process engineering is a significant step towards practical, efficient, and green technology for removing heavy metals.

Conclusion

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The study proved the efficiency of chitosan derivatives, specifically GCCHI, in adsorbing and ions from aqueous solution. The adsorption performance of the GCCHI bead depends solely on working conditions, including pH . The highest removal efficiencies of and were achieved at pH 6 and 7, respectively. Notable alterations were made to CHI beads, which resulted in increased surface areas, large pore volumes, and greater amounts of active sites. The modification method applied to CHI increased its adsorption capacity, making it the best candidate for environmental remediation compared to other chitosan derivatives. The removal efficiency remained the same during this study after repeated regeneration cycles. Research must prioritize the actual wastewater use of GCCHI in upcoming investigations.

Acknowledgments

The original version of this paper is available on https://www.scientific.net/EC.11.39.pdf

The author wishes to thank the Durban University of Technology's Department of Chemical Engineering for providing continuous working facilities.

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The original version of this paper is available on https://www.scientific.net/EC.11.39.pdf

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The original version of this eBook is available on https://www.scientific.net/book/engineering-chemistry-vol-11/978-3-0364-1890-2

Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 53-61

doi: 10.4028/p-SNQEz3

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

Submitted:
2025-01-30

Revised:
2025-06-14

Accepted:
2025-06-18

Online:
2025-09-10

Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

The original version of this paper is available on https://www.scientific.net/EC.11.53.pdf

Dina Rika Silviana , Dylia Rahmadyanti , Retno Asih , Haniffudin Nurdiansah , Mochamad Zainuri , and Darminto

¹Department of Physics, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia

Department of Material and Metallurgical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia

dinarikasilviana2405@gmail.com, dyliaarahmadyanti@gmail.com, retno.asih@its.ac.id, hanif_nurdiansah@its.ac.id, zainuri@physics.its.ac.id, darminto@physics.its.ac.id

Keywords: Biomass-derived graphene oxide (GO), Green synthesis, Modified Tour method, Pyrolysis

Abstract

Biomass has recently become attractive as a feedstock for 'green' graphene oxide (GO) as it promotes an environmentally friendly route. Here, we report a novel approach in the synthesis of large-sized GO from biomass using a simple single pyrolysis step, followed by processing via a modified Tour method. The single pyrolysis process produces a thin carbon layer with amorphous character, which is then further exfoliated using the permanganate oxidation method in a mixture of hydrochloric acid and phosphoric acid at low temperature. The novelty of this research lies in the combination of an efficient biomass pyrolysis process with a customised chemical approach to produce high-quality GO sustainably. XRD, SEM-EDX, and FTIR analyses showed that the modified GO has a more regular structure, contains fewer secondary phases, and has lower noncarbon functionalities compared to the untreated large-sized GO. The obtained GO materials have potential applications in the fields of energy storage, sensors, and environmentally friendly composite materials.

Introduction

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Graphene is a graphite consisting of thin sheets of molecular bonds between carbon atoms. Graphene has strong, thin, transparent, and conductive properties. The two-dimensional structure of graphene contributes to the high specific surface area, flexibility, conductivity, dispersion, and good thermal stability [1]. Researchers have used the mechanical, electronic, and optical characteristics of Graphene to develop electronic materials [2]. Graphene has derivatives such as graphene oxide and graphene-reduced oxide. Graphene oxide consists of oxygen and hydrogen atoms that are bound to carbon atoms in a hexagonal structure [1]. With a sheet thickness of 0.34 nm , graphene is the thinnest and strongest nanomaterial to date. Graphene has three carbon atoms that are bound through the bindings. Due to the failure of the electron p to form the bond, the remaining electron p forms a binding p with the atom around it [3]. Different forms of graphene as the composite material of graphite can be wrapped in a zero-dimensional ball structure, rolled into a onedimensional structure (CNT), or stacked into a three-dimensional layered structure [4]. Multilayered graphene (FLGS), graphene oxide (GO), reduced graphene Oxide (rGO), and graphene nanosheets have different physicochemical characteristics [5].

Graphene oxide and its derivatives are used as nanomaterial-based materials due to its enormous surface area and superior chemical strength. Graphite has been made from agricultural and planting waste and can be converted to graphene oxide. The graphene oxide obtained from biomass is also cheap, renewable, and environmentally friendly. Graphene oxide also contains carbon (C) based hexagon ring [6]. Generally, graphene oxide is made by chemical exfoliation of graphite powder
using strong oxidants such as that are dissolved in concentrates. Graphene oxide can function as a surfacing agent in size depending on amphiphilicity [7]. With its high monolayer surface area, graphene oxides are one of the chemicals that play an important role in the development of graphene and its derivatives [8]. Graphene oxide has a curved shape due to the presence of oxygen groups, while graphene has a planar structure [9]. The graphene oxide sheet's structure and surface properties determine the oxide graphene's application. Because of crystal distortion and defects, graphene oxide has electrically insulating properties [10].

Reduced graphene oxide is a derivative of graphene that has many defects and oxygen functions. The oxygen function of reduced graphene oxides is much lower than that of oxide graphene [11]. Reducing graphene is widely used in a variety of technologies, including hydrogen storage, photovoltaics, microwave absorbers, and supercapacitors [12]. Epitactic growth, chemical vapor deposition (CVD), hydrothermal, and skin exfoliation (mechanical, thermal, and chemical) are some of the methods of synthesis that have been used to produce reduced graphene oxides [13]. In the elimination of graphite in the formation of graphene derivatives, there are chemical efforts such as intercalation, chemical derivation, thermal expansion, reduction of oxidation, use of surfactants, or a combination of both [14]. The physical properties of the graphene derivatives influence the electrical and magnetic characteristics of the material. Reduced graphene oxide is a derivative of graphene found in a hybridized mixture of sp2 and sp3 in a two-dimensional structure that contains surface function groups of oxygen atoms, such as epoxy, carbonyl, hydroxyl, and carboxyl [15]. Functional graphene, chemically modified graphene, and reduced graphene are some of the other names for rGO [16].

In carbon, four valence electrons form a bond that produces the structure of the bee nest. Then, another valence electron is remote from the bond and produces high-voltage graphene sheet mobility [17]. In the periodic system of class IV, carbon (C) has properties comparable to silicon and germanium (Ge). The energy tape (Eg) of carbon(C) ranges from 0 to 6 eV , which allows it to be used as a conductor, semiconductor, or even a good isolator [18]. There are many natural sources of carbon in nature, most of which come from mining activities, such as graphite, coal, and intan, as well as natural gas and liquid hydrocarbons such as oil and gas. Biomaterials derived from plants, both as products (bioproducts) and as waste (biowaste), are another natural source of carbon [13]. Carbon is the most studied and used material in a variety of fields such as batteries, fuel cell electrodes, supercapacitors, and adsorbent materials. The amorphous carbon (A) and the crystal (G, graphite, and fullerene) are the two main allotropes of carbon [1].

In the synthesis of graphene-derived compounds, it is difficult to produce on a large scale. So far, coal has been used as a base material for graphene, because it is easily accessible and contains carbon elements for the manufacture of nanoscale structures. However, coal-based graphene is not environmentally friendly [19]. Therefore, alternative precursors are used for the synthesis of graphene-derived compounds from waste that contains high carbon and is environmentally friendly. One of the abundant and potential wastes used as a precursor is cocopeat. The larger the size of the dust of the coconut strap, the less water it can hold. With a porosity of more than of its volume, coconut rope dust has a high air content ( of the volume) [20]. Coconut belt fibers are very easy to obtain, weighing about of the coconut fruit, so they can be used to make carbon from natural fiber [21]. Coconut is one of the important agricultural commodities in Indonesia. Coconut belt waste can be converted into cocopeat which can be a functional precursor material of graphene derivatives thus producing environmentally friendly green carbon [6]. Once the coconut strap is smoothed, it will form cocopets or fine cocoa strap powder. In coconut seeds, there is cellulose that has a hydroxyl or OH group in its molecular structure. If coloring reacts with cellulase, a compound with a covalent or hydrogen bond will form. The distribution of the size of the dust particles of the coconut strap greatly affects its physical properties [22].

This research synthesized biomass-based graphene oxide using a single pyrolysis method. The single pyrolysis method can be produced on a large scale, more simply, and without chemical solvents. However, as a result of this synthesis, secondary phases or impurities emerge from the biomass precursor and the use of catalysts during the pyrolysis process. To overcome these problems, additional treatment is required to remove impurities. Methods to remove impurities include Liquid Phase Exfoliation (LPE), Distillation, Recrystallisation, Chromatography, Extraction, Filtration, Electrolysis, Ion Exchange, Sublimation, and Decantation. This study used the Tour method to purify GO from coconut fiber. The Tour technique is one of the few graphene oxide methods that have been developed so far and is believed to produce thinner and cleaner graphene oxide. Tour technique does not involve the use of sodium nitrate, this approach does not release harmful gases into the atmosphere. So the Tour method is safer and more effective for oxidizing graphite [23]. In addition, the Tour Method does not need to use high temperatures because it can be done at room temperature. It is expected that using the Tour Method can produce thin graphene oxide [24]. This study aims to determine the structure and morphology of graphene oxide before and after the Tour Method.

1. Method

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This research used a single pyrolysis method to obtain graphene oxide from cocopeat. The process is adapted from (Asih dkk, 2024), which produces Graphene Coconut (GC) from Old Coconut Shells (OCS) using a one-step pyrolysis method. Initially, the coconut fiber is separated from the coconut fruit. After that, the coconut fiber is washed using water and dried in the sun. Dry coconut fiber is ground into small, uniform pieces called cocopeat. Aluminum foil coated with catalyst is rolled and inserted into a cylindrical glass tube with a copper plate lid. Next, the cocopeat is put into a cylindrical glass tube with a weight ratio of catalyst to cocopeat of . Then, the sample was heated in a furnace at for 1 hour , and then the temperature was increased to for 3 hours [25].

Fig. 1. A Schematic diagram of the Single Pyrolysis method route

Fig. 1. A Schematic diagram of the Single Pyrolysis method route

After obtaining graphene oxide from cocopeat, synthesis was then carried out using the Tour method shown in Figure 1. and are used as starting materials for the Tour method. 30 ml of was mixed with 3.3 ml of in an Erlenmeyer flask and stirred for 30 minutes at room temperature. The Erlenmeyer flask is placed in a container containing ice cubes. After that, 1 gram of graphene oxide powder and 6 grams of were slowly added and stirred again for 30
minutes at room temperature until the solution changed color from purple to green. Then the Erlenmeyer flask was removed from the ice bath, and the solution was stirred for 2 hours at until the solution changed color to dark brown. While stirring was in progress, 100 ml of distilled water and 10 ml of were added to the solution. After stirring, the Erlenmeyer flask was closed using aluminum foil and left overnight. After that, the solution was centrifuged for 20 minutes. Next, the precipitated solution was washed using a mixture of distilled water and HCl with a volume ratio of 1:10 in 250 ml . Then the samples were dried using an oven.

Fig. 2. A schematic diagram of the Tour method route

Fig. 2. A schematic diagram of the Tour method route

Characterizations performed to investigate the structure of the samples include X-ray Diffraction (XRD), Transform Infrared (FTIR), and Scanning Electron Microscope (SEM). X-ray Diffraction (XRD), was used to identify the crystal structure of the samples. Fourier Transform Infrared (FTIR) was performed to identify the chemical composition of the material. A Scanning Electron Microscope (SEM) was used to observe the structure and morphology of the samples.

2. Results and Discussion

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The X-ray diffraction graph of graphene oxide before and during the Tour approach is described in Figure 1. Both before and after the Tour technique, the samples showed wide peaks measuring around and , which indicate amorphous characteristics. Due to dispersion from different directions, these two peaks are broad and belong to the amorphous phase. These peaks show that the phase resembling graphene oxide has reduced. Using the Tour technique resulted in a decrease in the secondary phase's peak intensity. This graph displays an amorphous phase of graphene oxide. Moreover, samples can be cleaned using the Tour technique.

Fig. 3. XRD graph of Graphene Oxide before and after the Tour Method

Fig. 3. XRD graph of Graphene Oxide before and after the Tour Method

A graph of the infrared graphene oxide's Fourier transformation both before and after the Tour technique is shown in Figure 2 and Table 1. Prior to using the Tour approach, the sample showed that bonds were present in peaks 2910 and 2846, bonds were present in peaks 2405 and 2162, and bonds were present in peaks 679. As for the sample, peak 2914 and peak 2842 reveal bonds, peak 2312 reveals bonds, and peak 1538 reveals bonds. This is all after using the Tour technique. Therefore, it can be said that both samples before and after the Tour procedure included and bonds. Following the application of the Tour technique, the H bond vanishes and a new peak arises at , signifying the creation of a bond. The transmittance% and the kind of functional groups generated are influenced by the functional groups generated from the two samples. Variations in the binding strength of the compounds when vibrations arise from the absorption of infrared radiation energy are the reason for this variation in transmittance. By measuring how much infrared light is absorbed, the Fourier Transform Infrared test can provide details about a sample's molecular makeup and composition.

Fig. 4. Graphene Oxide FTIR graph before the Tour Method and after the Tour Method

Fig. 4. Graphene Oxide FTIR graph before the Tour Method and after the Tour Method

Table 1. Comparison of Chemical Bonds Before and After the Tour Method

Peak (cm⁻¹) | Bond
| Before the Tour method | After the Tour method
679 | C=C-H | —
2914 – 2842 | C-H | C-H
~2300 | C≡C | C-C
1538 | — | C=C

The scanning electron microscope (SEM) images of graphene oxide before the application of the Tour method are shown in Figure 3. Three samples were observed at different magnifications: 2500x [Figure 3(a)], 5000x [Figure 3(b)], and 10000x [Figure 3(c)]. Based on these images, it can be seen that the untreated graphene oxide exhibits an irregular sheet-like structure with a relatively rough surface and noticeable layer agglomeration. The GO sheets appear to stack in a disordered manner, indicating that the exfoliation process was not fully effective. This kind of structure may limit the available active surface area and negatively impact the performance of GO in applications such as sensors or energy storage systems.

Fig. 5. SEM of Graphene Oxide before Tour Method (a)2500x (b)5000x (c)10000x

Fig. 5. SEM of Graphene Oxide before Tour Method (a)2500x (b)5000x (c)10000x

Figure 4 presents SEM images of graphene oxide after applying the Tour method, with magnifications of 2500x [Figure 4(a)], 5000x [Figure 4(b)], and 10000x [Figure 4(c)]. It is evident that the GO morphology underwent significant changes: the layers became thinner, more evenly dispersed, and the surface structure appeared smoother and more homogeneous. These observations indicate that the modified Tour method successfully enhanced the exfoliation process, resulting in GO with a more uniform layer thickness distribution.

This morphological transformation is crucial, as thinner and more uniform surface structures can increase the specific surface area, improve electronic and mechanical properties, and enhance the material's interaction with ions or other molecules in various functional applications. Therefore, the improved morphology observed through SEM analysis directly supports the potential of Tour-method-derived graphene oxide for high-performance applications such as supercapacitors, filtration membranes, or advanced composite materials.

Fig. 6. SEM of Graphene Oxide after Tour Method (a)2500x (b)5000x (c)10000x

Fig. 6. SEM of Graphene Oxide after Tour Method (a)2500x (b)5000x (c)10000x

3. Conclusion

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XRD analysis revealed the presence of broad peaks around and , both before and after the application of the Tour method, indicating the amorphous nature of the resulting graphene oxide (GO) material. Notably, the implementation of the Tour method led to a reduction in the intensity of peaks associated with secondary phases, suggesting enhanced purity and improved structural ordering of the GO. FTIR analysis demonstrated a significant chemical transformation, evidenced by the disappearance of the bond and the emergence of a peak at , confirming the formation of bonds-characteristic of a more conjugated and stable graphene structure. Further SEM analysis revealed that the morphology of GO produced via the Tour method consisted of thinner and more uniform layers compared to untreated GO, indicating improved exfoliation efficiency. These findings highlight the advantages of the modified Tour method as a simple yet effective approach to purify and refine biomass-derived graphene oxide. The main scientific contribution of this study lies in presenting an environmentally friendly synthesis strategy capable of producing GO with superior structural and morphological properties. Looking ahead, the GO material obtained through this method holds strong potential for various high-tech applications, including energy storage materials, carbon-based sensors, and functional composites for sustainable electronic devices.

4. Acknowledgements

The original version of this paper is available on https://www.scientific.net/EC.11.53.pdf

The authors express their gratitude to our partner, namely PT. Gnomac has provided the graphene oxide material.

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The original version of this paper is available on https://www.scientific.net/EC.11.53.pdf

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Engineering Chemistry, ISSN: 2813-6535, Vol. 11, pp 63-77

doi: 10.4028/p-N7SbTD

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

Submitted:
2024-12-02

Revised:
2025-03-16

Accepted:
2025-03-21

Online:
2025-09-10

Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

The original version of this paper is available on https://www.scientific.net/EC.11.63.pdf

Faried Latief , Putri Istichomah , Bagas Haqi Arrosyid , Ratih Amalia , Muhammad Fahroji , Trivadila , Akmal Zulfi , Andika Fajar , Andika Widya Pramono , and Alfian Noviyanto

Reseach Center for Advanced Materials, National Research and Innovation Agency (BRIN), Kawasan Puspiptek, Tangerang Selatan 15314, Banten, Indonesia

College of Vocational Studies, IPB University, JI. Kumbang No. 14 Cilibende, Bogor, 16128, Indonesia

Nano Center Indonesia, JI. Puspiptek No.A-12 Setu, Tangerang Selatan, Banten 15314, Indonesia

Department of Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia

Department of Chemistry, Faculty of Mathematics and Natural Science, IPB University, JI. Tanjung Kampus IPB Dramaga, Bogor 16680, Indonesia

Research Center for Environmental and Clean Technology, National Research and Innovation Agency, Bandung 40135, Indonesia

Research Center for Nanotechnology System, National Research and Innovation Council (BRIN), Kawasan Puspiptek, Tangerang Selatan 15314, Banten, Indonesia

Departement of Mechanical Engineering, Mercu Buana University, JI. Meruya Selatan Teknologi, Kebun Jeruk, Jakarta 11650, Indonesia

istichomahputri@apps.ipb.ac.id, bagashaqiarrosyid@nano.or.id, ratih@nano.or.id,

Corresponding author: a) fariedlatief@gmail.com

Keywords: Composite Nanofibers, PVDF/BiFeO3, electrospinning, optimum formulation, energy storage materials.

Abstract

The composite nanofibers of (PVDF/BF) signify a notable advancement in the domain of piezoelectric nanogenerators (PENGs), providing a high surface area alongside enhanced physicochemical properties for energy harvesting and storage applications. These nanofibers were synthesized through the electrospinning technique, which enables the creation of porous fibers by the dissolution of polymers in volatile solvents. This study investigates the crystalline and chemical structures of PVDF/BF nanofibers with modified formulations. X-ray diffraction (XRD) analysis has confirmed the presence of a rhombohedral (R3c) phase, characteristic of both and the PVDF phase. The measured fiber diameters for pure PVDF and PVDF/BF composites varied from approximately 400 nm to 950 nm . Fourier-transform infrared (FTIR) spectroscopy has identified absorption bands at , which correspond to the functional groups of , as well as at for PVDF. Moreover, Raman spectroscopy has validated molecular vibrational shifts for and PVDF within the range of 2973-2977 cm . The incorporation of within the PVDF/BF nanofibers enhances the formation of the electroactive -phase, thereby potentially improving their electrical properties.

Introduction

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In recent years, the growing demand for sustainable and renewable energy sources has led to the exploration of innovative technologies . There are several alternative energy sources, including solar energy materials (silicon, perovskite, and organic photovoltaic materials) [3-5], wind energy materials (steel, aluminum, and composite materials) [6], hydropower materials (concrete, steel, coating, and high-strength alloy) [7], geothermal energy materials (steel, high-temperature alloy, ceramic, and heat-resistance materials) [8], biomass and biofuel materials (organic materials and waste materials) [9,10], and piezoelectric materials (Bismuth ferrite (BF), and lead zirconate titanate (PZT), and nanomaterials) [11,12]. These materials represent how various energy technology pathways have been explored, offering cleaner and more sustainable future energy.

Piezoelectric materials are unique substances that generate electrical charges when subjected to mechanical stress, such as pressure, vibration, and bending. Their ability to transduce mechanical force into usable electricity has driven wide-used applications such as sensors, actuators, and energyharvesting devices [13-15]. Recent progress in piezoelectric materials has led to the development of piezoelectric nanogenerators (PENGs). PENGs utilize piezoelectric materials at the nanoscale, which can convert mechanical energy from ambient vibrations, human movement, or other mechanical forces into electrical energy, making them ideal for powering small-scale electronic devices like sensors, wearable electronics, flexible and portable devices, or medical implants [16,17]. Since tunable microstructure holds a pivotal part in this field, the advancement of materials porosity becomes promising. One of them is the development of nanofibers PENGs which promotes unique advantages due to their high surface area and enhanced energy conversion efficiency [18,19].

The most common and versatile method in fabricating nanofibers is electrospinning. This technique allows to generate fibers at the nanoscale with controlled properties, including voltage, flow rate, humidity, and the distance between the syringe nozzle and the collector [20]. It involves the use of electrical forces to draw jet-formation from the needle to the collector. The immediate evaporation of solvent during the spinning process would frequently generate simultaneous amorphous and semi-crystalline materials. This typical morphology is further known in polycrystalline nanofibers (PNFs) that are particularly interesting due to their multiple crystalline grains, giving them distinct mechanical, electrical, and optical properties [21-23] for are beneficial in ceramics or metal oxide-based materials.

One of the well-established energy storage devices is bismuth ferrite -based materials which have photovoltaic, photocatalytic, magnetic, and multiferroic (both ferromagnetic and ferroelectric) properties [24]. These promising features are owing to its electronic structure, where has lone pair electrons, and is strongly hybridized with empty orbital of Bi atom and orbital of the O atom [25,26]. The main issues with include structural instability, mechanical fragility, short life cycles, and a lack of flexibility. Therefore, it is essential to obtain capacitors that offer high performance, energy density, and advanced stability, while also ensuring high sustainability and low-cost production. Notably, bismuth ferrite nanofibers have emerged as a highly effective material for piezoelectric applications, leveraging their significant sustainability and efficiency in mechanical energy harvesting, thus opening new possibilities for next-generation energy solutions.

Polyvinylidene fluoride (PVDF) is a piezoelectric polymer known for its flexibility and chemical resistance, commonly used in wearable sensors and flexible electronics. The -phase of PVDF is the preferred phase that combines strong ferroelectric and piezoelectric properties [27]. Even though its piezoelectric effect is lower than ceramics, its considerable flexibility, lightweight properties, and high specific surface area are still worthwhile for the structural advancement [28]. The PVDF- composite nanofiber is expected to provide elastic interaction to the surface produced by the modifying agent, which can alter the spin structure of the magnetic field in
the interfacial region, leading to improved contact. The structural changes cause to exhibit alterations in the Fe-O-Fe bond angle of octahedral , so the redistribution of charge and dipole orientation in the polymer matrix results in a higher coupling.

In this work, the composite nanofiber has been modified to optimize its structural and vibrational properties. The flexible polycrystalline nanofibers, composed of electrospun embedded in a PVDF polymer matrix through a sol-gel and electrospinning method, provide the ability to tune the electrical properties, durability, and morphology of materials.

Experimental

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Synthesis

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The powder materials are used in this study prepared by sol-gel auto combustion method by using Bismuth(III) nitrate for analysis Merck (Cat. No. 1.01878.0100), Iron(III) nitrate nanohydrate Merck (Cat. No. 1.03883.0250), and Citric acid monohydrate from SAP Chemicals (purity ) [24,29]. This method merges the benefits of sol-gel processing and combustion synthesis, facilitating low-temperature fabrication and lower energy consumption compared to traditional methods. The sol-gel process begins with weighing metal precursors (Bismuth nitrate and Iron nitrate) and a chelating agent (Citric acid) according to stoichiometry at 0.02 mol . These components are then dissolved in deionized water to create a stable sol, which is subsequently transformed into a gel. Once the gel is formed, the autocombustion process occurs. In this stage, the gel experiences spontaneous combustion due to the exothermic reaction between nitrates as oxidizers and citrate as fuel. [30]. Following the autocombustion process, the powder undergoes purification and crystallization through calcination at a temperature of for 2 hours.

Fig. 1 displays the synthesis process from nanofiber . The synthesized powder and Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF) polymer from Merck (CAS No. 9011-17-0) were weighed according to predefined ratios: 2.5 g of PVDF with 0 g of BF for pure PVDF, 1.250 g of PVDF with 1.250 g of BF for a or PVDF/BF (50:50) composition, and 0.825 g of PVDF with 1.650 g of BF for a or (33:66) composition. DMAc was added in an amount of 5 mL and then placed into a 10 mL beaker. The PVDF powder was dissolved by gradually pouring it into the beaker containing DMAc [31]. After PVDF dissolved, material and 3.5 mL of DMAc were added and then re-dissolved for approximately 16 hours. The polymer dissolution process was conducted at a stirring speed of 300 rpm and a heating temperature of . The next step was the electrospinning process, where the polymer solution was placed in a syringe and extruded through a small needle under the influence of a high-voltage electric field at 15 kV with a 15 cm distance. [32,33]. The applied voltage will cause the polymer solution to form jets, forming a fine network that dries and collects as nanofibers. A Taylor cone forms according to the applied voltage [34]. The cone shape can last as long as the solution supply, surface tension, and viscosity are all stable.

Fig. 1. Synthesis process from PVDF/BF nanofiber using electrospinning process.

Fig. 1. Synthesis process from PVDF/BF nanofiber using electrospinning process.

Material Characterization

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The particle size was measured using a Particle Size Analyzer (PSA) (Zetasizer Pro (ZSU 2300), Malvern, England). The crystalline structure and phase identification of the composite PVDF/BiFeO3 nanofiber were recorded via X-ray Diffraction (XRD) with a source (Bruker D8 Advance 3 Kw ). Additionally, molecular vibrations were examined using a Fourier Transform Infrared Spectrometer (FTIR) (NicoletTM FTIR Spectrophotometer), as well as Raman spectra and Raman microscopy, which were recorded at room temperature with Raman spectroscopy (DXR3xi ThermoFisher Scientific).

Results and Discussion

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Synthesis Nanofibers

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Fig. 2 illustrates the physical appearance of the resulting nanofibers. The nanofibers formed from each formulation show an increase in brown color concentration from pure PVDF nanofiber (Fig. 2.a) to PVDF/BF (50:50) (Fig. 2.b). This increase is associated with the addition of BF material, which enhances the color intensity in the resulting nanofibers. Qualitative observations of this color can serve as a preliminary analysis of the optimal ratio of BF materials that can be composited with PVDF polymers. The formulations for pure PVDF and PVDF/BF (50:50) remain homogeneous and stable throughout the ten-hour electrospinning process. However, the visual appearance of the nanofibers indicates a reduction in color intensity over time. The nanofiber formulation for PVDF/BF Fig. 2.c) yields a pinkish-white color similar to that of pure PVDF nanofibers. This suggests that the incorporation of into the polymer matrix during nanofiber formation is not yet optimal. Despite the brown color of the solution, it is visually inferred that the optimal formulation is .

In the formulation, the nanofiber solution could not be perfectly mixed, indicating inhomogeneity when there is a significant increase in the amount of material added [35]. The nanofiber solution in the PVDF/BF formulation also shows a decrease in viscosity with the addition of BF material. This results in a thinner solution compared to pure PVDF and . The outcomes of the electrospinning process heavily depend on the conditions of the prepared solution [36]. The solution must consider several factors, such as polymer concentration, viscosity, solvent type, and structure [37]. Low polymer concentrations result in sparsely distributed molecules in the solvent, leading to low viscosity of the solution. This causes the formation of an
unstable polymer network and results in smaller fibers with many beads. In contrast, PVDF/BF (50:50) produces fibers with a more uniform diameter and smooth morphology without beads. Meanwhile, at high concentrations, the viscosity of the solution becomes significantly high, leading to substantial steric hindrance, which further restricts the molecules' ability to move freely [38]. Inhomogeneous material particles will create aggregates, disrupting the uniform distribution of the polymer solution and potentially impacting the morphology of the nanofibers.

Fig.2. The PVDF/BF nanofibers result from the electrospinning process (a) PVDF, (b) PVDF/BF , (c) PVDF/BF (33:66) with the scale in centimeter.

Fig.2. The PVDF/BF nanofibers result from the electrospinning process (a) PVDF, (b) PVDF/BF , (c) PVDF/BF (33:66) with the scale in centimeter.

Crystalline Structure and Microstructure

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The nanofiber samples were characterized using XRD, as shown in Fig. 3, which illustrates the characteristics of the crystal structure before and after being composited with a polymer matrix. The phase analysis was then compared with the Crystallography Open Database (COD) No. 210-2915 for the phase and the International Center for Diffraction Data (ICDD) No. 00-0421650 for PVDF, indicating the successful synthesis of and nanofiber PVDF/BF. The resulting diffractogram demonstrates the presence of the rhombohedral structure (space group R3c), with rhombohedral as the primary phase from [39]. There are doublet peaks at the diffraction index (104) and (110) which are characteristic peaks of pure [24]. Small peaks associated with the secondary phases appear at the diffraction indices , ( 013 ), and (-121) for Bismuth Iron Oxide ( ), Sillenite (Fe-bearing) , and Bismite . [40-42]. The phase shows in three main peaks including ; and . In addition, there are also positions at ; and . The secondary phase is Bismuth which appears positions at ; and . Another minor phase is Sillenite (Fe-bearing) ( ) at ; and , while Bismuth iron oxide is identified at of ; and .

Overall, there is no significant difference between the results of powder and composite PVDF/BF ( ) nanofibers. The diffraction pattern of PVDF displays two broad peaks at , which correlate with the -phase, -phase, and -phase forms of PVDF [43,44]. Rietveld refinement was conducted on the XRD pattern of calcined BF powder to determine its unit cell structure and symmetry. The final fitting parameters obtained from the Rietveld refinement were , and , indicating a good fit between the experimental and calculated profiles. The lattice constants estimated from the refinement were and .

Fig. 3. XRD pattern from powder calcined at for 2 h and composite nanofiber. Insects clearly show the highest peak of PVDF in the range around .

Fig. 3. XRD pattern from powder calcined at for 2 h and composite nanofiber. Insects clearly show the highest peak of PVDF in the range around .

PVDF/BF nanofibers typically exhibit a uniform fiber distribution with diverse orientations, which is commonly recognized as non-woven. This characteristic morphology of both pure PVDF and PVDF/BF nanofibers was analyzed using Raman microscopy. The resulting image facilitates the identification of individual fibers, enabling accurate fiber diameter measurements that are further analyzed using ImageJ software. Observation of nanofiber morphology was conducted by placing the nanofibers during the spinning process for 15 seconds, which were then observed at a magnification of 50x.

The morphology results of PVDF and PVDF/BF nanofibers are shown in Fig 4. Nanofibers were observed at a magnification of 50x. Based on visual observations, a nanofiber with a faint white color was obtained for the pure PVDF polymer. In contrast, PVDF/BF (50:50) and PVDF/BF (33:66) exhibited bead-like fibers. The measured fiber diameters for the pure PVDF and PVDF/BF (50:50) samples were 933 nm and 415 nm , respectively. The results indicate that increasing the material-topolymer ratio in the nanofiber solution leads to a reduction in fiber diameter. However, for the PVDF/BF (33:66) formulation, fiber size could not be accurately observed due to the considerably high viscosity of the nanofiber solution, which was not fully dissolved. This likely obscured the jet formation during the spinning process. The instability of the PVDF/BF (33:66) solution is further evidenced by material sedimentation due to phase separation.

The fabrication of pure PVDF and PVDF/BF nanofibers was carried out using the same parameters for voltage control, flow rate, and needle-to-collector distance. Differences in the resulting fiber size may be attributed to the presence of side jets, which are affected by variations in the concentration of the nanofiber solution [45]. This aligns with the average measurements of PVDF/BF nanofibers, which exhibit a smaller fiber size due to the lower viscosity of the polymer solution used to produce pure PVDF. Solutions with low viscosity create beaded fibers because of insufficient polymer concentration in the precursor solution [46]. Solutions with low viscosity contain a greater
proportion of solvent molecules than polymer molecules, which makes solvent-intermolecular interactions more prevalent. When these solvent interactions are considerably stronger than charge interactions, polymer intermolecular forces, or polymer-solvent interactions, the polymer finds it difficult to move toward the collector, impeding fiber formation [47]. Furthermore, the fiber vibrational properties in PVDF, PVDF/BF (50:50) and PVDF/BF (33:66) are observed through Raman and FTIR as explained in the following paragraph.

Fig. 4. Microstructure from fabricated nanofiber and composite nanofiber (a) PVDF, (b) PVDF/BF , and (c) PVDF/BF (33:66).

Fig. 4. Microstructure from fabricated nanofiber and composite nanofiber (a) PVDF, (b) PVDF/BF , and (c) PVDF/BF (33:66).

Vibrational Properties

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To conduct a deeper analysis of the chemical structure in the composite , characterization techniques such as Raman spectroscopy and FTIR are employed. Fig. 5 displays the FTIR spectra of PVDF and the composite PVDF/BF nanofiber. The positions of the prominent characteristic bands in the spectra are listed in Table 1. PVDF polymer exhibits several different phases, including the , and phases, each with distinct atomic arrangements and chain orientations. The chemical structure of PVDF can be represented as , where n denotes the number of repeating units in the polymer chain. The difluoromethylene ( ) and methylene functional groups were identified in the FTIR spectra of the nanofiber, indicating the properties derived from PVDF [38].

The vibrational peak at corresponds to symmetric stretching from the phase, while the peaks at , and represent the symmetric group of difluoromethylene from the -phase. The additional peaks at 1074 and are associated with the stretching mode of the asymmetric group from the -phase. The next peak at reflects the transformation from the -phase to the -phase. The wave number peaks observed at , and are present for both pure PVDF and PVDF/BF (50:50). Furthermore, the spectrum peaks at , and for PVDF/BF ( ) confirm the peaks of the -phase from PVDF. More detailed peaks from the -phase are also detected for pure PVDF at 511,878 , and at 509,874 , and , and PVDF/BF (33:66) at 510,877 , and , respectively. The last -phase was identified for pure PVDF, PVDF/BF (50:50), and PVDF/BF (33:66) as follows: 431 and . Based on all these spectra, the presence of , and phases is clearly identified in all samples, indicating that PVDF-based nanofibers have been successfully fabricated.

Typically, the absorption mode in the range below is associated with the bond between inorganic elements [48]. This range of areas is evident with the addition of multiferroic materials like , which can be observed from the presence of and groups primarily in PVDF/BF (50:50), identified at to . Additionally, the Bi-O stretching of BiO 6 was identified at , and the of octahedral is reflected at 439 and . Other

Fe-O and Bi-O stretchings of and octahedra are prominently represented at 550 , 555, 555 , and in PVDF/BF ( ), while their intensity is lower in PVDF/BF ( ). This result suggests that the presence of is more pronounced at higher concentrations, reaching its optimal proportion at PVDF/BF (50:50). Meanwhile, the peak intensity between and is less pronounced compared to PVDF/BF ( ) and is almost similar to that of pure PVDF, indicating that this formulation is less effective in dissolving BF into the PVDF matrix.
nanoparticles can interact with PVDF chains through physical or chemical bonds, changing the distribution of chain conformations and enhancing the formation of electroactive phases ( -phase and -phase) [49]. Conversely, the PVDF/BF (33:66) formulation experienced a decrease in the intensity of the FTIR results, which may be due to the fact that during the preparation of the PVDF/BF ( ) nanofiber solution, materials could no longer be completely dissolved. Increasing the concentration of to an extreme level can disrupt solution stability and cause sedimentation, which leaves the pre-solution thinner. Higher concentrations of nanoparticles in PVDF/BF ( ) can also lead to the formation of agglomerates, which reduce the homogeneity of the material and disrupt the distribution of the crystal phases in the nanofibers.

Fig. 5. FTIR spectra from fabricated nanofiber and composite nanofiber (a) PVDF, (b) PVDF/BF , and (PVDF/BF . Inset shows more detail the and bonding.

Fig. 5. FTIR spectra from fabricated nanofiber and composite nanofiber (a) PVDF, (b) PVDF/BF , and (PVDF/BF . Inset shows more detail the and bonding.

Table 1. FTIR band assignments of , and nanofiber.

No.
Wave number (cm⁻¹)
References
Identification

PVDF
PVDF/BF(50:50)
PVDF/BF(33:66)

1.
-
413
411
410
Bending of Fe-O and Bi-O groups

2.
-
539
539
539
Bi-O stretching of BiO₆

3.
-
440
439
440
Fe-O of FeO₆ octahedral

4.
-
555
554
555
Fe-O and Bi-O stretching of BiO₆ and FeO₆ octahedral

5.
489
487
489
480
489
CF₂-bending and wagging α-phase

6.
612
761
796
612
761
796
612
761
796
614
763
795
α-phase

7.
839
839
839
840
1275
α-phase in raw powder
converted into β-phase

8.
511
878
1276
510
875
1276
509
874
1276
511
840
1275
β-phase

9.
431
1430
431
1430
431
1430
431
1429
γ-phase

10.
1400
1400
1400
1406
CF₂ symmetric stretching, α-phase

11.
1175
1177
1175
1170
Symmetrical stretching of CF₂ group, β-phase

12.
1073
1073
1073
1073
Asymmetrical stretching of CF₂ group, β-phase

The Raman shift spectrum of nanofibers was obtained using a laser power of 1.5 mW , an exposure time of 10 Hz , and a number of scans up to 500 . The results are represented in Fig. 6 and Table 2. The main peaks for each formulation in sequence for PVDF/BF (50:50) and PVDF/BF (33:66) were 2979, 2973, 2973, and , which corresponded to the Raman spectrum of the polymer in its -phase. The identified spectrum confirmed that there was more phase than -phase due to the PVDF polymer used in the nanofiber manufacturing process. The spectrum of the pure phase at was very strong, indicating that the main contribution to the peak at arose from the phase. Notably, one of the strongest lines in the Raman spectrum of the -phase at is only present as a shoulder in the spectrum that shows peaks at , and for the -phase and -phase of PVDF. The presence of a strong Raman peak at , characteristic of the -phase, appearing only as a shoulder in the spectrum with peaks at , and , suggests a phase conversion from -phase to -phase, along with the formation of the -phase in PVDF. This transformation is similar to that observed in the system, where ZnO acts as a nucleating agent, facilitating an efficient phase transition from -phase to -phase, thereby enhancing piezoelectric properties . A similar effect has been reported in the PVDF/PZT system, where PZT particles promote -phase formation within the composite structure [52]. Furthermore, in the PVDF-TrFE/BaTiO3 system, the addition of combined with a two-step poling method resulted in a high -phase fraction in nanofiber samples [53].

Raman spectroscopy was also performed to identify the chemical structure of rhombohedral in and , which exhibit R 3 c symmetry and comprise + 9E) Raman active modes. These include 4 A1-symmetry longitudinal-optical (A1) optical modes and 8 E modes that represent the crystal characteristics of [48]. Modes E-1, A1-1, A1-2, A13, E-2, E-3, and E-5 closely align with the modes of the material structure. In contrast, E-2, A1-4, and E-4 show slight shifts, which are attributed to variations in material concentration. Raman spectra analysis indicates features below that represent Bi atoms in the perovskite structure,
while high-frequency vibrations above correspond to the stretching vibrations of octahedral Fe atoms . Three primary vibration modes at , and around the frequency bands of , and 216-218 signify the covalent bond between Bi and O , as well as the distortion caused by tetrahedral Bi atoms. The A1-4 vibration mode, located around 430-435 , reflects the stretching vibrations of octahedral Fe atoms . The E vibration mode, occurring around 266-609 , results from the distortion of octahedral . [24].

Fig. 6. Raman spectroscopy spectrum of PVDF, PVDF/BF (50:50), and PVDF/BF (33:66) nanofiber. The inset shows the Raman shift .

Fig. 6. Raman spectroscopy spectrum of PVDF, PVDF/BF (50:50), and PVDF/BF (33:66) nanofiber. The inset shows the Raman shift .

Table 2. Peak position of Raman active modes of , and nanofiber.

No.
Raman shift (cm⁻¹)
References
Mode/Identification

PVDF
PVDF/BF(50:50)
PVDF/BF(33:66)

1.
-
73.44
73.44
72.95
E-1

2.
-
135.15
135.15
136.99
A₁-1

3.
-
169.86
169.86
169.31
A₁-2

4.
-
218.08
218.08
218.59
A₁-3

5.
-
266.89
277.86
266.23
E-4

6.
-
353.07
356.92
352.71
E-6

7.
-
432.13
435.99
428.84
A1-4

8.
-
115.87
115.87
115.88
E-2

9.
-
468.78
464.92
466.65
E-7

10.
-
526.83
530.00
528.00
E-8

11.
-
603.00
609.00
601.64
E-9

12.
796
798
796
799
795
α-phase

13.
880
1276
877
1274
880
1276
840
842
1278
β-phase

14.
1431
1433
1431
1433
1435
CH₂, (β-phase)

15.
2981
2973
2981
2974
CH₂ symmetric
stretching (β-phase)

Conclusion

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The nanofiber solution was successfully synthesized using the electrospinning method, incorporating various formulation variations: PVDF, PVDF/BF (50:50), and PVDF/BF (33:66). The measured fiber diameters for pure PVDF and PVDF/BF composites ranged from approximately 400 nm to 950 nm . Observing the physical appearance, PVDF/BF ( ) shows a notable resemblance to the solution color and visually exhibits the highest homogeneity. Characterization of the PVDF/ nanofibers was conducted using XRD, FTIR, and Raman spectroscopy, revealing the presence of , and phases of the PVDF polymer, as well as the functional groups of the material. The potential dielectric properties are indicated by the results of nanofiber characterization using FTIR and Raman spectroscopy, which demonstrate the enhancement of functional groups and Raman shifts in the and phases of the PVDF/BF nanofiber, along with the Bi-O and Fe-O functional groups.

Acknowledgements

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This study was financially supported by the Center of Excellence Advanced Materials at Nano Center Indonesia. The authors would like to express their gratitude to Nano Center Indonesia for providing their facilities and characterization.

References

The original version of this paper is available on https://www.scientific.net/EC.11.63.pdf

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Keywords Index

A

And Oil-spill Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

B

Biomass-derived Graphene Oxide (go) Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

Breakthrough Analysis Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

C

Calcium Carbonate Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Carbon Dots Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

Chitosan Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Chitosan-chitin Adsorbent Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

Citric Acid Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Composite Nanofibers Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

E

Electrospinning Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Energy Storage Materials Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Environmental Remediation Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

G

Gcchi Beads Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

Green Synthesis Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

H

Heavy Metal Removal Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

M

Methylene Blue Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Modified Tour Method Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

O

Oil Absorption Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

Oil Contaminant Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Oleic Acid Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Optimum Formulation Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

P

Photodegradation Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Photoluminescent Polymers Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Porous Composites Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Pvdf/bifeo3 Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Pyrolysis Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

S

Silica Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Simulation; Regeneration; Sustainable Adsorbent; Adsorption Kinetics Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

Swan Model Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

X

Xanthan Gum Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Authors Index

A

Amalia, R. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Aremu, A. Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Arrosyid, B. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Asih, R. Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

B

Bena, M. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

D

Darminto, D. Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

Devi, I. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

F

Fahroji, M. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Fajar, A. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Fathurrohman, A. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Fauziah, F. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

I

Igberase, E. Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

Isnaeni, I. Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

Istichomah, P. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

L

Latief, F. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

M

Martak, F. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Mkhize, I. Application of the Swan Model for the Adsorption of and on Chitosan Derivative in a Packed Bed Column

N

Ni'mah, H. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

Noviyanto, A. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Nurdiansah, H. Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

O

Olorunnisola, A. Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

Olowofoyeku, A. Citric Acid-Treated Polyethylene-Calcium Carbonate Composites with Tunable Photoluminescence, Porosity, and Adsorption Properties for Oil Contaminants Remediation

P

Pramono, A. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

Putri, I. Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

R

Rahmadyanti, D. Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

Rizky, A. Fabrication of Silica-Modified Green Mussel Shell-Based Chitosan Hydrogel Bio-Composite and Xanthan Gum from Tofu Dregs as Methylene Blue Photodegradator

S

Silviana, D. Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

T

Trivadila, T. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique

W

Widyastuti, W. Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation

Z

Zainuri, M. Enhancing Sponge Absorbency with Carbon Dots for Cost-Effective Oil Spill Remediation; Structural Investigation of Biomass-Derived Graphene Oxide Prepared by a Single Step Pyrolysis Followed by a Modified Tour Method

Zulfi, A. Synthesis, Structural, and Vibrational Properties of PVDF/BiFeO3 Nanofibers using Electrospinning Technique