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The global attention has been focused on degradation of the environmental organic pollutants through green methods such as advanced oxidation processes (AOPs) under sunlight. However, AOPs have not yet been efficient in function of the photocatalyst that has been used. In this work, firstly, CaCu3Ti4O12 nanocomposite was simultaneously synthesized and decorated in different amounts of graphene oxide to enhance photodegradation of the organics. The result of the photocatalyst characterization showed that the sample with 8% graphene presented optimum photo-electrical properties such as low band gap energy and a great surface area. Secondly, the photocatalyst was applied for photodegradation of an organic model in a batch photoreactor. Thirdly, to scale up the process and optimize the efficiency, the photodegradation was modeled by multivariate semi-empirical methods. As the optimized condition showed, 45 mg/L of the methylorange has been removed at pH 5.8 by 0.96 g/L of the photocatalyst during 288 min of the light irradiation. Moreover, the photodegradation has been scaled up for industrial applications by determining the importance of the input effective variables according to the following organics order>photocatalyst>pH> irradiation time. [ABSTRACT FROM AUTHOR]

It is believe that 80% industrial of carbon dioxide can be controlled by separation and storage technologies which use the blended ionic liquids absorber. Among the blended absorbers, the mixture of water, N-methyldiethanolamine (MDEA) and guanidinium trifluoromethane sulfonate (gua) has presented the superior stripping qualities. However, the blended solution has illustrated high viscosity that affects the cost of separation process. In this work, the blended fabrication was scheduled with is the process arranging, controlling and optimizing. Therefore, the blend’s components and operating temperature were modeled and optimized as input effective variables to minimize its viscosity as the final output by using back-propagation artificial neural network (ANN). The modeling was carried out by four mathematical algorithms with individual experimental design to obtain the optimum topology using root mean squared error (RMSE), R -squared ( R 2 ) and absolute average deviation (AAD). As a result, the final model (QP-4-8-1) with minimum RMSE and AAD as well as the highest R 2 was selected to navigate the fabrication of the blended solution. Therefore, the model was applied to obtain the optimum initial level of the input variables which were included temperature 303–323 K, x [gua], 0–0.033, x [MDAE], 0.3–0.4, and x [H 2 O], 0.7–1.0. Moreover, the model has obtained the relative importance ordered of the variables which included x [gua] > temperature > x [MDEA] > x [H 2 O]. Therefore, none of the variables was negligible in the fabrication. Furthermore, the model predicted the optimum points of the variables to minimize the viscosity which was validated by further experiments. The validated results confirmed the model schedulability. Accordingly, ANN succeeds to model the initial components of the blended solutions as absorber of CO 2 capture in separation technologies that is able to industries scale up. [ABSTRACT FROM AUTHOR]

Background: In fabrication of ZnO-based low voltage varistor, Bi2O3 and TiO2 have been used as former and grain growth enhancer factors respectively. Therefore, the molar ratio of the factors is quit important in the fabrication. In this paper, modeling and optimization of Bi2O3 and TiO2 was carried out by response surface methodology to achieve maximized electrical properties. The fabrication was planned by central composite design using two variables and one response. To obtain actual responses, the design was performed in laboratory by the conventional methods of ceramics fabrication. The actual responses were fitted into a valid second order algebraic polynomial equation. Then the quadratic model was suggested by response surface methodology. The model was validated by analysis of variance which provided several evidences such as high F-value (153.6), very low P-value (<0.0001), adjusted R-squared (0.985) and predicted R-squared (0.947). Moreover, the lack of fit was not significant which means the model was significant. Results: The model tracked the optimum of the additives in the design by using three dimension surface plots. In the optimum condition, the molars ratio of Bi2O3 and TiO2 were obtained in a surface area around 1.25 point that maximized the nonlinear coefficient around 20 point. Moreover, the model predicted the optimum amount of the additives in desirable condition. In this case, the condition included minimum standard error (0.35) and maximum nonlinearity (20.03), while molar ratio of Bi2O3 (1.24 mol%) and TiO2 (1.27 mol%) was in range. The condition as a solution was tested by further experiments for confirmation. As the experimental results showed, the obtained value of the non-linearity, 21.6, was quite close to the predicted model. Conclusion: Response surface methodology has been successful for modeling and optimizing the additives such as Bi2O3 and TiO2 of ZnO-based low voltage varistor to achieve maximized non-linearity properties. [ABSTRACT FROM AUTHOR]

Background: The complexity of reactions and kinetic is the current problem of photodegradation processes. Recently, artificial neural networks have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the non-linear relationships between variables in complex systems. In this study, an artificial neural network was applied for modeling p-cresol photodegradation. To optimize the network, the independent variables including irradiation time, pH, photocatalyst amount and concentration of p-cresol were used as the input parameters, while the photodegradation% was selected as output. The photodegradation% was obtained from the performance of the experimental design of the variables under UV irradiation. The network was trained by Quick propagation (QP) and the other three algorithms as a model. To determine the number of hidden layer nodes in the model, the root mean squared error of testing set was minimized. After minimizing the error, the topologies of the algorithms were compared by coefficient of determination and absolute average deviation. Results: The comparison indicated that the Quick propagation algorithm had minimum root mean squared error, 1.3995, absolute average deviation, 3.0478, and maximum coefficient of determination, 0.9752, for the testing data set. The validation test results of the artificial neural network based on QP indicated that the root mean squared error was 4.11, absolute average deviation was 8.071 and the maximum coefficient of determination was 0.97. Conclusion: Artificial neural network based on Quick propagation algorithm with topology 4-10-1 gave the best performance in this study. [ABSTRACT FROM AUTHOR]

Photocatalytic degradation of p-cresol was carried out using ZnO under UV irradiation. The amount of photocatalyst, concentration of p-cresol and pH were studied as variables. The residual concentration and mineralization of p-cresol was monitored using a UV-visible spectrophotometer and total organic carbon (TOC) analyzer, respectively. The intermediates were detected by ultra high pressure liquid chromatography (UPLC). The highest photodegradation of p-cresol was observed at 2.5 g/L of ZnO and 100 ppm of pcresol. P-cresol photocatalytic degradation was favorable in the pH range of 6-9. The detected intermediates were 4-hydroxy-benzaldehyde and 4-methyl-1,2-benzodiol. TOC studies show that 93% of total organic carbon was removed from solution during irradiation time. Reusability shows no significant reduction in photocatalytic performance in photodegrading p-cresol. [ABSTRACT FROM AUTHOR]

Abstract: The optimization processes of photo degradation are complicated and expensive when it is performed with traditional methods such as one variable at a time. In this research, the condition of ortho-cresol (o-cresol) photo degradation was optimized by using a semi empirical method. First of all, the experiments were designed with four effective factors including irradiation time, pH, photo catalyst's amount, o-cresol concentration and photo degradation % as response by response surface methodology (RSM). The RSM used central composite design (CCD) method consists of 30 runs to obtain the actual responses. The actual responses were fitted with the second order algebraic polynomial equation to select a model (suggested model). The suggested model was validated by a few numbers of excellent statistical evidences in analysis of variance (ANOVA). The used evidences include high F-value (143.12), very low P-value (<0.0001), non-significant lack of fit, the determination coefficient (R2 = 0.99) and the adequate precision (47.067). To visualize the optimum, the validated model simulated the condition of response (photo degradation %) be using a few number of three dimensional plots (3D). To confirm the model, the optimums were performed in laboratory. The results of performed experiments were quite close to the predicted values. In conclusion, the study indicated that the model is successful to simulate the optimum condition of o-cresol photo degradation under visible-light irradiation by manganese doped ZnO nanoparticles. [ABSTRACT FROM AUTHOR]

Background: The interactions of p-cresol photocatalytic degradation components were studied by response surface methodology. The study was designed by central composite design using the irradiation time, pH, the amount of photocatalyst and the p-cresol concentration as variables. The design was performed to obtain photodegradation % as actual responses. The actual responses were fitted with linear, two factor interactions, cubic and quadratic model to select an appropriate model. The selected model was validated by analysis of variance which provided evidences such as high F-value (845.09), very low P-value (<.0.0001), non-significant lack of fit, the coefficient of R-squared (R2 = 0.999), adjusted R-squared (R2adj = 0.998), predicted R-squared (R2pred = 0.994) and the adequate precision (95.94). Results: From the validated model demonstrated that the component had interaction with irradiation time under 180 min of the time while the interaction with pH was above pH 9. Moreover, photocatalyst and p-cresol had interaction at minimal amount of photocatalyst (< 0.8 g/L) and 100 mg/L p-cresol. Conclusion: These variables are interdependent and should be simultaneously considered during the photodegradation process, which is one of the advantages of the response surface methodology over the traditional laboratory method. [ABSTRACT FROM AUTHOR]

The introduction of low detection limit ion selective electrodes (ISEs) may well pave the way for the determination of trace targets of cationic compounds. This research focuses on the detection of titanium (III) cation using a new PVC-membrane sensor based on synthesized tris(2pyridyl) methylamine (tpm) ionophore. The application and validation of the proposed sensor was done using potentiometric titration, inductively coupled plasma atomic emission spectrometry (ICP-AES), and atomic absorption spectrometry (AAS). The membrane sensor exhibited a Nernstian response to the titanium (III) cation over a concentration range of 1.0×10×-6-1.0×10-2 Mand pH range from 1-2.5. The Nernstian slope, the lower of detection (LOD), and the response time (t95%) of the proposed sensor were 29.17 ± 0.24 mV/dec, 7.9 × 10-7 M, and 20 s, respectively. The direct determination of 4-39 μg/ml of titanium (III) standard solution showed an average recovery of 94.60 and a mean relative standard deviation of 1.8 at 100.0 μg/ml. Finally, the utilization of the electrodes as end-point indicators for potentiometric titration with EDTA solutions for titanium (III) sensor was successfully carried out. [ABSTRACT FROM AUTHOR]

This paper deals with the comparative study on glycerolysis of palm fatty acid distillate (PFAD) in a solvent free system at different reaction conditions in an attempt to get maximum degree of FFA% reduction for biodiesel feedstock. Initially, optimization of varied reaction parameters was performed under all the different reaction conditions using artificial neural network (ANN) based on the genetic algorithm (GA). It has been found that the reduction of acidity varies with varying reaction conditions with maximum reaction rate observed in case of reaction carried-out in open reactor system with inert gas flow, followed by the reaction in open reactor system without inert gas flow and then in case of reaction under the close reactor system. In the most favorable case, 1.5 mg KOH /g PFAD of FFA (free fatty acid) was achieved after 90 min of reaction time with an excess glycerol of 4% at 220 °C. The results from the ANN model show good agreement with experimental results. Thus, the glycerolysis in open reactor system with inert gas flow (N 2 ) option is much-preferred option compared to acid esterification for the same biodiesel plant capacity, particularly for high-FFA feedstocks. [ABSTRACT FROM AUTHOR]

Biosynthesis of noble metal nanoparticles is a vast developing area of research. In the present study, silver nanoparticles (Ag-NPs) were synthesized from aqueous silver nitrate through a simple and biosynthetic route using water extract of Curcuma longa ( C. longa) tuber powder, which acted simultaneousl as a reductant and stabilizery. The as-prepared samples are characterized using UV-Visible, XRD, TEM, SEM, EDXF, and FT-IR techniques. The formation of Ag-NPs is evidenced by the appearance of the signatory brown color of the solution and UV-vis spectra. Formation of Ag/ C. longa was determined by UV-Vis spectroscopy where surface plasmon absorption maxima can be observed at 457-415 nm from the UV-Vis spectrum. The XRD analysis shows that the Ag-NPs are of a face-centered cubic structure. Well-dispersed Ag-NPs with anisotropic and isotropic morphology for 5, 10, and 20 mL of C. longa water extract having a size less than 10 nm are seen in TEM images. The optimum volume extraction to synthesize smallest particle size was 20 mL with mean diameter and standard division 4.90 ± 1.42 nm. FT-IR spectrum indicates the presence of different functional groups in capping the nanoparticles with C. longa. The zeta potential analysis results indicated that the charge of C. longa was negative and increased in Ag/ C. longa emulsion with increasing of volumes of extract used (10-20 mL). The most needed outcome of this work will be the development of value-added products from C. longa for biomedical and nanotechnology-based industries. [ABSTRACT FROM AUTHOR]

In this study, estimation capabilities of the artificial neural network (ANN) and the wavelet neural network (WNN) based on genetic algorithm were investigated in a synthesis process. An enzymatic reaction catalyzed by Novozym 435 was selected as the model synthesis process. The conversion of enzymatic reaction was investigated as a response of five independent variables; enzyme amount, reaction time, reaction temperature, substrates molar ratio and agitation speed in conjunction with an experimental design. After training of the artificial neurons in ANN and WNN, using the data of 30 experimental points, the products were used for estimation of the response of the 18 experimental points. Estimated responses were compared with the experimentally determined responses and prediction capabilities of ANN and WNN were determined. Performance assessment indicated that the WNN model possessed superior predictive ability than the ANN model, since a very close agreement between the experimental and the predicted values was obtained. [ABSTRACT FROM AUTHOR]

Hydroxamic acids and their derivatives have low toxicities and show wide range of biological activities. Copper complexes of phenyl fatty hydroxamic acids (Cu-PFHs) were prepared in a biphasic organic / aqueous medium from phenyl fatty hydroxamic acids (PFHAs) and copper nitrate. The products were separated by decantation of organic phase from aqueous phase followed by evaporation of the solvent. Elemental analysis, UV-Vis spectra and FTIR spectra showed that Cu-PFHs were formed in the solution from the complexation of PFHAs and copper ion. The antibacterial activity of PFHAs and Cu-PFHs from canola and palm kernel oils were investigated against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) using well diffusion method. The results showed that Cu-PFHs have higher antibacterial activity compared to PFHAs. Antibacterial activity of Cu-PHAs from canola oil against E.coli was significantly higher than chloramphenicol and cefotaxime. [ABSTRACT FROM AUTHOR]

Different biological methods are gaining recognition for the production of silver nanoparticles (Ag-NPs) due to their multiple applications. The use of plants in the green synthesis of nanoparticles emerges as a cost effective and eco-friendly approach. In this study the green biosynthesis of silver nanoparticles using Callicarpa maingayi stem bark extract has been reported. Characterizations of nanoparticles were done using different methods, which include; ultraviolet-visible spectroscopy (UV-Vis), powder X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray fluorescence (EDXF) spectrometry, zeta potential measurements and Fourier transform infrared (FT-IR) spectroscopy. UV-visible spectrum of the aqueous medium containing silver nanoparticles showed absorption peak at around 456 nm. The TEM study showed that mean diameter and standard deviation for the formation of silver nanoparticles were 12.40 ± 3.27 nm. The XRD study showed that the particles are crystalline in nature, with a face centered cubic (fcc) structure. The most needed outcome of this work will be the development of value added products from Callicarpa maingayi for biomedical and nanotechnology based industries. [ABSTRACT FROM AUTHOR]

Novel ionophores comprising various hydroxide and amine structures were immobilized onto poly(vinyl chloride) (PVC) matrices, and these were examined to determine Ti(III) selectivity. To predict the selectivity of Ti(III), a PVC membrane was used to investigate the binding of Ti(III) to c-methylcalix[4]resorcinarene (CMCR). The study showed that the chelating ligand, CMCR, was coordinated selectively to Ti(III) at eight coordination sites involving the oxygen atoms at the interface of the membrane/solution. The membrane was prepared, based on CMCR as an ionophore, sodium tetrakis(4-fluorophenyl) borate (NaTFPB) as a lipophilic ionic additive, and dioctylphthalate (DOP) as a plasticizer. The immobilization of the ionophore and surface characterization studies revealed that the performance of CMCR-immobilized PVC was equivalent to that of mobile ionophores in supported liquid membranes (SLMs). The strengths of the ion-ionophore (CMCR-Ti(OH)(OH2)52+) interactions and the role of ionophores on membranes were studied via UV-Vis, Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and and X-ray diffraction (XRD). [ABSTRACT FROM AUTHOR]

The roles of green chemistry in nanotechnology and nanoscience fields are very significant in the synthesis of diverse nanomaterials. Herein, we report a green chemistry method for synthesized colloidal silver nanoparticles (Ag NPs) in polymeric media. The colloidal Ag NPs were synthesized in an aqueous solution using silver nitrate, polyethylene glycol (PEG), and ß-D-glucose as a silver precursor, stabilizer, and reducing agent, respectively. The properties of synthesized colloidal Ag NPs were studied at different reaction times. The ultraviolet-visible spectra were in excellent agreement with the obtained nanostructure studies performed by transmission electron microscopy (TEM) and their size distributions. The Ag NPs were characterized by utilizing X-ray diffraction (XRD), zeta potential measurements and Fourier transform infrared (FT-IR). The use of green chemistry reagents, such as glucose, provides green and economic features to this work. [ABSTRACT FROM AUTHOR]

Liquid-liquid iron(III) extraction was investigated using benzyl fatty hydroxamic acids (BFHAs) and methyl fatty hydroxamic acids (MFHAs) as chelating agents through the formation of iron(III) methyl fatty hydroxamate (Fe-MFHs) or iron(III) benzyl fatty hydroxamate (Fe-BFHs) in the organic phase. The results obtained under optimized conditions, showed that the chelating agents in hexane extract iron(III) at pH 1.9 were realized effectively with a high percentage of extraction (97.2% and 98.1% for MFHAs and BFHAs, respectively). The presence of a large amount of Mg(II), Ni(II), Al(III), Mn(II) and Co(II) ions did affect the iron(III) extraction. Finally stripping studies for recovering iron(III) from organic phase (Fe-MFHs or Fe-BFHs dissolved in hexane) were carried out at various concentrations of HCl, HNO3 and H2SO4. The results showed that the desired acid for recovery of iron(III) was 5 M HCl and quantitative recovery of iron(III) was achieved from Fe(III)-MFHs and Fe(III)-BFHs solutions in hexane containing 5 mg/L of Fe(III). [ABSTRACT FROM AUTHOR]