Synthesis of Ag-ZnO with multiple rods (multipods) morphology and its application in the simultaneous photo-catalytic degradation of methyl orange and methylene blue.

In this study, the photo-decolorization of a mixture of methylene blue (MB) and methyl orange (MO) was investigated using Ag-ZnO multipods. The photo-catalyst used, ZnO multipods, was successfully synthesized. The surface of ZnO microstructure was modified by deposition of different amounts of Ag nanoparticles (Ag NPs) using the photo-reduction method. The as-prepared samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-Vis and atomic absorption spectroscopy. The photo-catalytic efficiency of Ag-ZnO is mainly controlled by the amount of Ag NPs deposited on the ZnO surface. The results obtained suggest that Ag-ZnO containing 6.5% Ag NPs, has the highest photo-catalytic performance in the simultaneous photo-degradation of dyes at a shorter time.

An on-line spectrophotometric determination of trace amounts of thiourea in tap water, orange juice, and orange peel samples using multi-channel flow injection analysis.

In this work, a flow injection analysis (FIA) method was introduced for the determination of trace amounts of thiourea in tap water. This method is based upon the inhibition effect of thiourea on the reaction between meta-cresol purple (MCP) and potassium bromate catalyzed by bromide ions in a sulfuric acid medium. In the presence of thiourea, an induction period appears in the reaction system, and as a result, the absorbance of MCP increases at 525 nm in the FIA manifold. The chemical and FIA variables are studied and optimized using the univariate and Simplex optimization methods. Under the optimum conditions, thiourea can be determined in the range of 0.100-13.0 µg mL(-1). The limit of detection (3σ) for thiourea was found to be 0.0310 µg mL(-1). The relative standard deviations (RSDs) for six replicate determinations of 0.500, 5.00, and 12.0 µg mL(-1) of thiourea were 4.0%, 1.8%, and 1.2%, respectively. The proposed method was also applied for the determination of thiourea in orange juice and orange peel samples with recoveries in the range of 98.0-101%. The analytical speed of the method was calculated to be about 120 sample per hour.

Modelling of cytotoxicity data (CC50) of anti-HIV 1-[5-chlorophenyl) sulfonyl]-1H-pyrrole derivatives using calculated molecular descriptors and Levenberg-Marquardt artificial neural network.

A nonlinear quantitative structure anti-HIV activity relationship study was presented for modelling and predicting pyrryl aryl sulfones cytotoxicity data. Levenberg-Marquardt artificial neural network was used to link molecular structures and cytotoxicity data. A data set consisting of 27 derivatives of 1-[5-chlorophenyl) sulfonyl]-1H-pyrrole was used in this study. Among a large number of calculated descriptors, only eight significant molecular descriptors were obtained by stepwise regression, as the most feasible descriptors, and then they were used as inputs for neural network. The data set was randomly divided into 20 training and 7 validation sets and the neural network architecture and its parameters were optimized. The prediction ability of the model was evaluated using the validation data set, leave-one-out cross-validation and response randomization method. The mean square errors and mean absolute errors for the validation data set were 0.0067 and 0.066, respectively, and for the leave-one-out method, they were 0.013 and 0.087, respectively. The results obtained showed the excellent prediction ability and stability of the proposed model in the prediction of cytotoxicity data of the corresponding anti-HIV analogues.

Prediction of cytotoxicity data (CC(50)) of anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives by artificial neural network trained with Levenberg-Marquardt algorithm.

A Levenberg-Marquardt algorithm trained feed-forward artificial neural network in quantitative structure-activity relationship (QSAR) was developed for modeling of cytotoxicity data for anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives. A large number of descriptors were calculated with Dragon software and a subset of calculated descriptors was selected with a stepwise regression as a feature selection technique. The 28 molecular descriptors selected by stepwise regression, as the most feasible descriptors, were used as inputs for feed-forward neural network. The neural network architecture and its parameters were optimized. The data were randomly divided into 31 training and 11 validation sets. The prediction ability of the model was evaluated using validation data set and "one-leave-out" cross validation method. The root mean square errors (RMSE) and mean absolute errors for the validation data set were 0.042 and 0.024, respectively. The prediction ability of ANN model was also statistically compared with results of linear free energy related model. The obtained results show the validity of proposed model in the prediction of cytotoxicity data of corresponding anti-HIV drugs.

Simultaneous determination of cobalt, nickel and palladium in micellar media using partial least square regression and direct orthogonal signal correction.

A simple, novel and sensitive spectrophotometric method was described for the simultaneous determination of cobalt, nickel and palladium. The method is based on the complex formation of Co, Ni and Pd with 1-(2-pyridylazo)-2-naphtol (PAN) in Tween-80 micellar media. All factors affecting on the sensitivity were optimized and the linear dynamic range for determination of Co, Ni and Pd was found. The experimental calibration matrix was designed by measuring the absorbance over the range of 520-700 nm for 21 samples of 0.10-1.0, 0.050-0.50 and 0.050-4.0 microg ml(-1) of Co, Ni and Pd, respectively. The partial least square (PLS) modeling based on singular value decomposition (SVD) was used for the multivariate calibration of the spectrophotometric data. The direct orthogonal signal correction was used for pre-processing of data matrices and the prediction results of model, with and without using direct orthogonal signal correction, were statistically compared. The effects of various anions and cations on selectivity of the method were investigated. The proposed method was successfully applied to the determination of Co, Ni and Pd in water and alloy samples.