High-performance NiO@Fe3O4 magnetic core-shell nanocomposite for catalytic ozonation degradation of pharmaceutical pollution.

Pharmaceuticals that are present in superficial waters and wastewater are becoming an ecological concern. Therefore, it is necessary to provide high-performance methods to limit the harmful ecological effects of these materials to achieve a sustainable environment. In this research, NiO@Fe3O4 nanocomposite was prepared by the co-precipitation method and utilized in the catalytic ozonation process for the degradation of 1-cyclopropyl-6-fluoro-4-oxo-7-piperazin-1-yl-quinoline-3-carboxylic acid (ciprofloxacin antibiotic), for the first time. The influencing parameters in the degradation process were analyzed and optimized via response surface methodology (RSM). The optimal ciprofloxacin removal efficiency (100%) was found at pH = 6.5, using 7.5 mg of the NiO@Fe3O4 nanocatalyst and 0.2 g L-1 h-1 ozone (O3) flow, applied over 20 min. Results showed a significant synergistic effect in the analyzed system, which makes the proposed catalytic ozonation process more efficient than using the catalyst and ozone separately. Also, based on the kinetic analysis data, the catalytic ozonation process followed the pseudo-first-order model. In addition, the nanocatalyst showed high recyclability and stability (88.37%) after five consecutive catalytic ozonation process cycles. In conclusion, the NiO@Fe3O4 nanocatalyst/O3 system can be effectively used for the treatment of pharmaceutical contaminants.

Efficient removal of cytotoxic drugs from wastewater by single-stage combined photocatalysis-algae treatment process.

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 (Anabaena sp.), nano-sized MoS2 photocatalyst under visible light irradiation, and combined photocatalysis-algal treatment process were investigated. Using response surface optimization technique, 85.1% of the FLU removal was achieved at the optimum conditions of pH 7.0, nanophotocatalyst dose of 15.23 mg and 12.12 mL of the alga in 30 min. Compared to the individual biological and chemical treatment methods, a higher FLU removal efficiency was obtained at a shorter reaction time by using the combined treatment system. Kinetics study showed that FLU removal by the algal treatment, photocatalysis, and the combined processes followed the modified Freundlich, pseudo-first-order, and nonlinear sigmoidal kinetic models, respectively. The results indicate that a synergistic effect appears when algal treatment process and photocatalysis are performed simultaneously. The novel combined system is a low-cost and efficient microalgae-based technology for the removal of cytotoxic compounds from wastewaters.

Coagulation/Fenton oxidation combined treatment of compost leachate using quince seed mucilage as an effective biocoagulant.

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-1 of QSM at pH 3.8 and 29 min, 45.0% COD reduction was achieved in the coagulation-flocculation (CF) stage. After CF pretreatment stage, Fenton oxidation (FO) process was applied on the leachate. Maximum COD reduction was obtained at pH 2.5, H2O2 concentration of 190 mM, and Fe2+ concentration of 1.64 mM. At the optimum conditions of the combined treatment process, up to 84.4% COD, 99.4% turbidity and 98.2% BOD were removed. The combined CF/FO process using QSM in the CF stage was found to be an effective method for the treatment of compost leachate.

Highly efficient removal of surfactant from industrial effluents using flaxseed mucilage in coagulation/photo-Fenton oxidation process.

In this study, flaxseed mucilage (FSM) has been used as a green coagulant in the pretreatment stage of a combined process for the removal of an anionic surfactant, sodium dodecyl sulfate (SDS). In the post-treatment stage, heterogeneous photo-Fenton-like oxidation using MnFe2O4 nanocatalyst was applied to remove the remained SDS. Using response surface methodological approach, optimum condition in the coagulation process was obtained at pH 7.0, FSM dose of 100 mg L-1 and 30 min. In the photo-Fenton oxidation process, complete SDS removal was achieved using 76 mg of the nanocatalyst, 1.07 mL of H2O2 at 17 min. Application of the combined process on the real wastewater samples indicates that the proposed method can be used effectively for the treatment of industrial effluents containing surfactants.

Enzyme mimetic activities of spinel substituted nanoferrites (MFe2O4): A review of synthesis, mechanism and potential applications.

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 MFe2O4, 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. In addition, various nanocomposite materials based on SFs have been introduced as novel artificial enzymes. This review mainly highlights the synthetic approaches for newly developed SF-nanozymes and also the structural/experimental factors that are effective on the kinetics and catalytic mechanisms of enzyme-like reactions. SF-nanozymes have been found potentially capable of being applied in various fields such as enzyme-free immunoassays and biosensors for colorimetric detection of biological molecules. Therefore, the application of SF nanoparticles, as efficient enzyme mimetics have been detailed discussed.

Optimized fabrication of newly cholesterol biosensor based on nanocellulose.

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. FESEM and TEM images showed high porosity of the nanostructure with no phase separation, revealing the homogenous polymerization of the monomer on the surface of the crystalline cellulose. Research surface methodology (RSM) was carried out to optimize the parameters and conditions leading to maximize the performance and sensitivity of biosensors. The PANi/CNC/IL/GLU/ChOx-modified electrode showed a high sensitivity value of 35.19 µA mM/cm-2 at optimized conditions. The proposed biosensor exhibited a dynamic linear range of 1 µM to 12 mM (R2 = 0.99083) with the low Limit of Detection of 0.48 µM for cholesterol determination. An acceptable reproducibility (RSDs ≤3.76%) and repeatability (RSDs ≤3.31%) with the minimal interference from the coexisting electroactive compounds such as ascorbic acid, uric acid and glucose was observed for proposed biosensor.

Formulation development and optimization of palm kernel oil esters-based nanoemulsions containing sodium diclofenac.

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. The two response variables were droplet size and viscosity. Optimization of the conditions according to the four variables was performed for preparation of the nanoemulsions with the minimum values of particle size and viscosity. The results showed that the experimental data could be sufficiently fitted into a third-order polynomial model with multiple regression coefficients (R(2) ) of 0.938 and 0.994 for the particle size and viscosity, respectively. Water content, O/S ratio and mixing time, quadrics of all independent variables, interaction between O/S ratio and mixing rate and between mixing time and rate, as well as cubic term of water content had a significant effect (P<0.05) on the particle size of nanoemulsions. The linear effect of all independent variables, quadrics of water content and O/S ratio, interaction of water content and O/S ratio, as well as cubic term of water content and O/S ratio had significant effects (P<0.05) on the viscosity of all nanoemulsions. The optimum conditions for preparation of sodium diclofenac nanoemulsions were predicted to be: 71.36% water content; 0.69 O/S ratio; 950 rpm mixing rate, and 5 minute mixing time. The optimized formulation showed good storage stability in different temperatures.

Enzymatic production of a solvent-free menthyl butyrate via response surface methodology catalyzed by a novel thermostable lipase from Geobacillus zalihae.

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. The high conversion of menthyl butyrate catalyzed by crude T1 lipase in a solvent-free system is greatly affected by temperature and time of the reaction media. The highest yield of menthyl butyrate was 99.3% under optimized conditions of 60 °C, incubation time of 13.15 h, 2.53 mg, 0.43% (w/w) enzyme to substrate ratio and at molar ratio of butyric anhydride/menthol 2.7:1. Hence, the investigation revealed that the thermostable crude T1 lipase successfully catalyzed the high-yield production of menthyl butyrate in a solvent-free system. The finding suggests that the crude T1 lipase was a promising alternative to overcome shortcomings associated with solvent-assisted enzymatic reactions.

Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network.

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, 0.563, 1.124, 2.248, and 3.372kg COD/(m(3)day)) and cyclic time (12, 24, and 48h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O&G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44kg COD/(m(3)day), TDS of 78,000mg/L and reaction time (RT) of 40h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100mg/L and met the discharge limits.

Chemometric analysis of lipase-catalyzed synthesis of xylitol esters in a solvent-free system.

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. The optimum conditions derived via the Taguchi approach for the synthesis of xylitol caprate and xylitol caproate were reaction time, 29 and 18h; substrate molar ratio, 0.3 and 1.0; enzyme amount, 0.20 and 0.05g, and molecular sieve amount of 0.03g, respectively. The good correlation between the predicted conversions (74.18% and 61.23%) and the actual values (74.05% and 60.5%) shows that the model derived from the Taguchi orthogonal array can be used for optimization and better understanding of the effect of reaction parameters on the enzymatic synthesis of xylitol esters in a solvent-free system.

Modeling and optimization of lipase-catalyzed production of succinic acid ester using central composite design analysis.

Esterification of succinic acid with oleyl alcohol catalyzed by immobilized Candida antarctica lipase B (Novozym 435) was investigated in this study. Response surface methodology (RSM) based on a five-level, four-variable central composite design (CCD) was used to model and analyze the reaction. A total of 21 experiments representing different combinations of the four parameters including temperature (35-65°C), time (30-450 min), enzyme amount (20-400 mg), and alcohol:acid molar ratio (1:1-8:1) were generated. A partial cubic equation could accurately model the response surface with a R(2) of 0.9853. The effect and interactions of the variables on the ester synthesis were also studied. Temperature was found to be the most significant parameter that influenced the succinate ester synthesis. At the optimal conditions of 41.1°C, 272.8 min, 20 mg enzyme amount and 7.8:1 alcohol:acid molar ratio, the esterification percentage was 85.0%. The model can present a rapid means for estimating the conversion yield of succinate ester within the selected ranges.

Effect of alcohol structure on the optimum condition for novozym 435-catalyzed synthesis of adipate esters.

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. Minimum reaction time (135 min) for achieving maximum ester yield was obtained for iso-butanol. The required time for attaining maximum yield and also the initial rates in the synthesis of di-n-butyl and di-sec-butyl adipate were nearly the same. Immobilized Candida antarctica lipase B was also capable of esterifying tert-butanol with a maximum yield of 39.1%. The enzyme is highly efficient biocatalyst for the synthesis of adipate esters by offering a simple production process and a high esterification yield.

Lipase-catalyzed dimethyl adipate synthesis: response surface modeling and kinetics.

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 97.6%, at the optimal conditions of 58.5 degrees C, 54.0 mg enzyme, 358.0 min, and 12:1 molar ratio of methanol to adipic acid. The R(2) (0.9769) shows a high correlation between predicted and experimental values. The kinetics of the reaction was also investigated in this study. The reaction was found to obey the ping-pong bi-bi mechanism with methanol inhibition. The kinetic parameters were determined and used to simulate the experimental results. A good quality of fit was observed between the simulated and experimental initial rates.

Optimized lipase-catalyzed synthesis of adipate ester in a solvent-free system.

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 2.5% w/w at 60 degrees C, reaction time of 438 min, and agitation speed of 500 rpm. The good correlation between predicted value (96.0%) and actual value (95.5%) implies that the model derived from RSM allows better understanding of the effect of important reaction parameters on the lipase-catalyzed synthesis of adipate ester in an organic solvent-free system. Higher volumetric productivity compared to a solvent-based system was also offered by SFS. The results demonstrate that the solvent-free system is efficient for enzymatic synthesis of adipate ester.

Application of artificial neural network for yield prediction of lipase-catalyzed synthesis of dioctyl adipate.

In this study, an artificial neural network (ANN) trained by backpropagation algorithm, Levenberg-Marquadart, was applied to predict the yield of enzymatic synthesis of dioctyl adipate. Immobilized Candida antarctica lipase B was used as a biocatalyst for the reaction. Temperature, time, amount of enzyme, and substrate molar ratio were the four input variables. After evaluating various ANN configurations, the best network was composed of seven hidden nodes using a hyperbolic tangent sigmoid transfer function. The correlation coefficient (R2) and mean absolute error (MAE) values between the actual and predicted responses were determined as 0.9998 and 0.0966 for training set and 0.9241 and 1.9439 for validating dataset. A simulation test with a testing dataset showed that the MAE was low and R2 was close to 1. These results imply the good generalization of the developed model and its capability to predict the reaction yield. Comparison of the performance of radial basis network with the developed models showed that radial basis function was more accurate but its performance was poor when tested with unseen data. In further part of the study, the feedforward backpropagation model was used for prediction of the ester yield within the given range of the main parameters.