Publications by authors named "Chaibakhsh N"

Article Synopsis
  • The study explores the photocatalytic efficiency of a ZnS/TiO nanocomposite for degrading Acid Blue 113 dye when exposed to UV light, highlighting limitations due to its wide bandgap and low adsorption capacity.
  • Surface modification of the nanocomposite was conducted using dielectric-barrier discharge plasma with nitrogen and tetrafluoromethane gases, resulting in improved photocatalytic performance.
  • The modified N-plasma-treated nanocomposite demonstrated nearly double the efficiency of the untreated version, achieving about 95% dye degradation in 25 minutes, offering a cost-effective solution for wastewater treatment.
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  • * Researchers developed a NiO@FeO nanocomposite that efficiently degrades the antibiotic ciprofloxacin through a catalytic ozonation process, achieving 100% removal at optimal conditions.
  • * The study demonstrated the nanocatalyst's high performance and stability, maintaining 88.37% efficiency after multiple uses, making it a promising solution for treating pharmaceutical contaminants in water.
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In this study, the efficiency of a single-stage combined photocatalysis-algae treatment process in the removal of the anticancer drug, flutamide (FLU), from aqueous solution has been evaluated. The removal abilities of the individual blue-green alga ( sp.), nano-sized MoS photocatalyst under visible light irradiation, and combined photocatalysis-algal treatment process were investigated.

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In this study, quince seed mucilage (QSM) has been introduced as a novel biocoagulant for the pretreatment of leachate obtained from a composting facility. Response surface methodology (RSM) was used to study and optimize the effect of pH, QSM dosage and time on the coagulation performance. At the optimum conditions using 1370 mg L of QSM at pH 3.

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  • The study explores the use of flaxseed mucilage (FSM) as an eco-friendly coagulant in a method to remove sodium dodecyl sulfate (SDS), an anionic surfactant, from wastewater.
  • The optimum conditions for the coagulation process were found to be at a pH of 7.0, with a dosage of 100 mg/L of FSM, carried out over 30 minutes.
  • In the subsequent photo-Fenton-like oxidation stage using a MnFeO nanocatalyst, complete removal of SDS was achieved with 76 mg of the catalyst and 1.07 mL of hydrogen peroxide in just 17 minutes, demonstrating the method's effectiveness for treating industrial effluents
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Recently, the intrinsic enzyme-like activities of some nanoscale materials known as "nanozymes" have become a growing area of interest. Nanosized spinel substituted ferrites (SFs) with general formula of MFeO, where M represents a transition metal, are among a group of magnetic nanomaterials attracting researchers' enormous attention because of their excellent catalytic performance, biomedical applications and capability for environmental remediation. Due to their unique nanoscale physical-chemical properties, they have been used to mimic the catalytic activity of natural enzymes such as peroxidases, oxidases and catalases.

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A novel and sensitive electrochemical cholesterol biosensor was developed based on immobilization cholesterol oxidase (ChOx) on the polyaniline/crystalline nanocellulose/ionic liquid modified Screen-Printed Electrode (PANi/CNC/IL/SPE). A thin layer of ionic liquid (IL) was spin coated on the modified electrode to enhance the electron transferring. Crystalline nanocellulose was prepared from Semantan bamboo (Gigantochloa scortechinii) via acid hydrolysis and it was used to synthesize a nanocomposite of PANi/CNC via in situ oxidative polymerization process.

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Most substrate for esterification has the inherent problem of low miscibility which requires addition of solvents into the reaction media. In this contribution, we would like to present an alternative and feasible option for an efficient solvent-free synthesis of menthyl butyrate using a novel thermostable crude T1 lipase. We investigated the effects of incubation time, temperature, enzyme loading and substrate molar ratio and determined the optimum conditions.

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Response surface methodology was employed to study the effect of formulation composition variables, water content (60%-80%, w/w) and oil and surfactant (O/S) ratio (0.17-1.33), as well as high-shear emulsification conditions, mixing rate (300-3,000 rpm) and mixing time (5-30 minutes) on the properties of sodium diclofenac-loaded palm kernel oil esters-nanoemulsions.

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A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000mg/L), various organic loading rates (OLRs) (0.281, 0.

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Immobilized Candida antarctica lipase B-catalyzed esterification of xylitol and two fatty acids (capric and caproic acid) were studied in a solvent-free system. The Taguchi orthogonal array method based on three-level-four-variables with nine experiments was applied for the analysis and optimization of the reaction parameters including time, substrate molar ratio, amount of enzyme, and amount of molecular sieve. The obtained conversion was higher in the esterification of xylitol and capric acid with longer chain length.

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Immobilized Candida antarctica lipase B, Novozym 435, was used as the biocatalyst in the esterification of adipic acid with four different isomers of butanol (n-butanol, sec-butanol, iso-butanol, and tert-butanol). Optimum conditions for the synthesis of adipate esters were obtained using response surface methodology approach with a four-factor-five-level central composite design concerning important reaction parameters which include time, temperature, substrate molar ratio, and amount of enzyme. Reactions under optimized conditions has yielded a high percentage of esterification (>96%) for n-butanol, iso-butanol, and sec-butanol, indicating that extent of esterification is independent of the alcohol structure for primary and secondary alcohols at the optimum conditions.

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Article Synopsis
  • The study explored the esterification of succinic acid with oleyl alcohol using immobilized Candida antarctica lipase B (Novozym 435) as a catalyst, employing response surface methodology (RSM).
  • A total of 21 experiments were conducted to assess the effects of four variables: temperature (35-65°C), time (30-450 min), enzyme amount (20-400 mg), and alcohol:acid molar ratio (1:1-8:1), and a partial cubic equation provided a high R² value of 0.9853 for modeling the reaction.
  • Findings indicated that temperature significantly impacted ester synthesis, with optimal conditions achieving an esterification percentage of 85.0% at 41.1°C
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Dimethyl adipate (DMA) was synthesized by immobilized Candida antarctica lipase B-catalyzed esterification of adipic acid and methanol. To optimize the reaction conditions of ester production, response surface methodology was applied, and the effects of four factors namely, time, temperature, enzyme concentration, and molar ratio of substrates on product synthesis were determined. A statistical model predicted that the maximum conversion yield would be 97.

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Immobilized Candida antarctica lipase-catalyzed esterification of adipic acid and oleyl alcohol was investigated in a solvent-free system (SFS). Optimum conditions for adipate ester synthesis in a stirred-tank reactor were determined by the response surface methodology (RSM) approach with respect to important reaction parameters including time, temperature, agitation speed, and amount of enzyme. A high conversion yield was achieved using low enzyme amounts of 2.

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Article Synopsis
  • An artificial neural network (ANN) using the Levenberg-Marquardt algorithm was employed to predict the yield of dioctyl adipate synthesis, utilizing immobilized Candida antarctica lipase B as a biocatalyst.
  • The model incorporated four input variables: temperature, time, enzyme amount, and substrate molar ratio, and performed best with seven hidden nodes, achieving high accuracy with R² values of 0.9998 for training and 0.9241 for validation datasets.
  • While the radial basis function network was found to be more accurate, it struggled with unseen data; the feedforward backpropagation model successfully predicted ester yields within the defined parameter ranges.
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