Engineering Chemistry Vol. 9

Abstract: This study investigates the corrosion inhibition properties of Salak (Salacca zalacca) peel extract as a green inhibitor on AISI 1040 steel in a 1M HCl acidic environment and focusing on secondary metabolites such as flavonoids and tannins. The qualitative phytochemical analysis showed antioxidant activity of the inhibitor extract was categorized as moderate with an IC50 value of 105.219 ppm. Functional group analysis using FTIR indicated that the flavonoids and tannins in the extract acted as antioxidants and inhibited corrosion growth. The weight loss test revealed the highest inhibition efficiency 11.13% was achieved at a concentration of 200 ppm after 20 days of immersion. In the potentiodynamic polarization test, the corrosion rate was 0.025 mm/year at the same concentration and immersion time. These results suggest that Salak (Salacca zalacca) peel extract can effectively inhibit corrosion at spesific concentrations but its efficiency diminishes at higher concentrations.

Abstract: This study aimed to determine the effect of concentration and immersion time of Salak (Salacca zalacca) Seed extract as a green inhibitor on the corrosion inhibition efficiency and corrosion rate of AISI 1040 steel in a 1M HCl environment. The chemical composition of AISI 1040 steel was confirmed using OES testing to verify its compliance with AISI 1040 chemical standards. The antioxidant activity of the salak (Salacca zalacca) seed extract was determined through the 1,1-Diphenyl-2-Picrylhydrazyl (DPPH) test yielding an IC50 value of 192.55 ppm, indicating weak antioxidant activity. Qualitative phytochemical analysis confirmed the presence of flavonoids and tannins in the extract, as verified by Fourier Transform Infrared (FTIR) testing. The study explored concentration variations ranging from 100 to 500 ppm and immersion time variations of 10 to 30 days were used. The highest inhibition efficiency was obtained at 500 ppm concentration, while the lowest was at 100 ppm, with values of 40.26% and 18.90% respectively. Additionally, the corrosion rate was reduced to 0.035 mm/year at the highest concentration of 500 ppm. These findings demonstrated the potential of salak (Salacca zalacca) seed extract as an eco-friendly, effective corrosion inhibitor for AISI 1040 steel.

Abstract: This study investigates the electrochemical reduction of quinine (QN) detection using boron-doped diamond electrodes (BDD). Different pulse voltammetry (DPV) of QN in a 0.1 M PB solution exhibits reduction peaks at -0.86 V (vs. Ag/AgCl). Additionally, the effects of pH and scan rate were explored to investigate the reduction mechanism within a potential range of -1.4 V to -0.4 V (vs. Ag/AgCl). Furthermore, a linear calibration curve was observed in the concentration range of 2 μM to 25 μM (R²=0.99) with a detection limit of 0.62 μM (S/B=3).

Abstract: The development of non-enzymatic glucose biosensor has been the concern of many researchers mainly because enzymes based sensor despite having excellent sensitivity and selectivity, has the limitations such as poor stability, complicated enzyme immobilization, critical operating conditions such as optimum temperature and reproducibility. This study developed a cheap biocompatible non-enzymatic glucose biosensor based on silver nanoparticle (AgNPs) stabilized with sodium tripolyphosphate (NaTPP) cross-linked chitosan. Direct electron transfer and electro-catalytic activity of the AgNPs modified glassy carbon electrode (AgNPGCE) was investigated using potentiometric and amperometric techniques. AgNPs was prepared and characterized by Fourier transform Infra-red spectroscopy (FTIR), X-ray diffractometry (XRD) and Scanning electron microscopy (SEM). The crystalline size of the AgNPs was revealed with XRD. However, the SEM micrograph of AgNPs revealed the spherical shape with a non-uniform granular shape attributed to bio-mediated ionic gelation process. The FTIR spectra of AgNPs shown peaks at 1054 – 1645 cm^-1 suggesting the presence of phosphonate linkages between ammonium, -NH₃⁺ of chitosan and -PO₃^2- moieties of NaTPP during cross linking process. Electro-catalytic oxidation of glucose at the AgNPGCE surface and the mechanism involved in glucose oxidation was revealed via cyclic voltammetry. The AgNPGCE showed a better electrochemical response towards glucose. This glucose sensor showed high sensitivity at +0.54 V. A low detection limit of 1.22 µM (the confident level κ = 3), and wide linear range of 2 to 24 µM with a correlation coefficient of 0.9987 were obtained. The calculated parameters revealed that AgNPGCE had shown better overall electrochemical performance and response than enzymatic biosensor.

Abstract: A novel series of fatty betaines containing a pyrimidine ring with different alky chain lengths were synthesized by condensation of fatty N,N'-diphenylalkylamidines with a specific highly reactive malonic ester derivative under mild conditions. The chemical structures of products were characterized by common spectroscopic analyses (FTIR, mass spectra, ¹H NMR, and ¹³C NMR spectrometry). Equilibrium surface tension and conductivity as a function of concentration of dodecyl pyrimidinum betaine (betaine with a 12 -carbon alkyl chain) in ethanolic solutions were measured and the critical micelle concentration (CMC) was determined at 30 °C. The results showed that the critical micelle concentration (CMC) of dodecyl pyrimidinum betaine is 0.925 mmol/L and the corresponding surface tension (γ_CMC) is 25.38 mN/m respectively. These results revealed that the synthesized fatty pyrimidinium betaines are efficient amphoteric surfactants making them promising candidates for applications in a very large number of areas.

Abstract: Light is essential for plant growth and plays a crucial role in photosynthesis. However, sunlight often falls short of ensuring photosynthesis efficiency due to its wavelength composition, changing weather conditions, and the unique characteristics of plants, which create challenges for agricultural productivity. To address this, many innovative farming practices have been developed, including controlled environment agriculture, which creates microclimates that optimize conditions for plants. To improve light efficiency in these microclimates, researchers have turned to luminescent and light-conversion materials. These materials are incorporated into polymers to convert underutilized wavelengths, such as UV and blue light, into photosynthetically active radiation (PAR). Luminescent materials like fluorescent pigments, quantum dots, and rare-earth-doped compounds, when incorporated into polymers, produce films that enhance light absorption and improve spectral energy distribution. They have shown great potential to increase crop yield, biomass, and the quality of fruits and vegetables. Despite their potential, challenges remain on the path to widespread adoption. Environmental impact, scalability, and economic feasibility are significant concerns. This review explores the integration and functionality of photoluminescent polymer nanocomposites as light-converting materials. It also examines current limitations while offering future perspectives on how these materials can be used for sustainable light solutions to improve agricultural productivity.

Abstract: The exceptional properties of chitosan and its effective technique of adsorbing contaminants even to near-zero concentrations are the primary reasons for special attention. The adsorption studies analyzed various elements, including pH, concentration, contact time, and adsorbent dose. The study used these factors as input data, with the output data concentrating on MB removal efficiency. For prediction and optimization, MB adsorption used response surface methodology/central composite design (RSM-CCD), artificial neural network (ANN), and adaptive neuron-fuzzy inference system (ANFIS) models. For developing the ANN and ANFIS models, 70% of the data was allocated for training, and 15% was dedicated to validation and testing. Based on the RSM-CCD findings, the optimization outcome for the process parameters was obtained at pH 7, contact time 55 minutes, 6.0 grams of adsorbent, and MB concentration of 125 mg/L. However, an ideally trained neural network is described using training, testing, and validation phases, and the R² values at these phases were found to be 0.99987, 1, and 1, respectively. The statistical findings showed that the ANFIS approach outperforms the RSM and ANN model approaches.