A New Sensitive Fluorescence Sensor and Photocatalyst for Determination and Degradation of Sodium Valproate Using g-C3N4@Fe3O4@CuWO4 Nanocomposite and FCCD Optimization.

In this research, carbon nitride nanocomposite coupled with Fe3O4 and CuWO4 was thermally synthesized and characterized by different techniques, including SEM, TEM, XRD, EDX, and FTIR. Due to sodium valproate's luminescence quenching of this nanocomposite, a reliable, accurate, sensitive, selective, and fast-acting sodium valproate assay was proposed. Optimization of this fluorescent sensor was carried out by the FCCD approach. In the optimum conditions, the plot of sodium valproate concentration versus nanocomposite fluorescence emission showed a linear response (R2 = 0.9918), with a range of 0-0.55 µM, the limit of detection (S/N = 3) equal to 0.85 nM and limit of qualification equal to 2.82 nM. Photocatalytic activity of g-C3N4@Fe3O4@CuWO4 (40%) nanocomposite exhibited a good potency to sodium valproate degradation. Active species of degradation including superoxide radicals, holes, and hydroxyl radicals were investigated using ammonium oxalate, benzoquinone, and 2-propanol to identify the mechanism of photodegradation action. The activity of benzoquinone in the photocatalytic process led to a reduction in the rate of analyte degradation, which indicates the prominent role of superoxide radicals compared to other species in the degradation process. The degradation rate of the analyte using the Fenton reagent was found to be around two times more than in the Fenton reagent-free process. The possible mechanism for the fluorescence sensor and photocatalytic degradation reaction was also discussed.

Global and local QSPR models to predict supercooled vapour pressure for organic compounds.

In this study, a quantitative structure-property relationship (QSPR) approach was used for estimation of logarithmic values of supercooled liquid vapour pressure (log PL) of a large set of structurally diverse organic compounds. This set includes 12 local sets of aromatic and aliphatic hydrocarbons, polychlorinated biphenyls, ethers, polychlorinated and brominated diphenylethers, polychlorinated naphthalenes and alcohols. Some simple models based on the linear relationship between log PL and VolSurf descriptors were developed as global models, and a general equation as a simple way to calculate the supercooled liquid vapour pressure of organic chemicals was provided. A descriptor representing the hydrophilic regions (WO1) of organic chemicals showed the highest correlation with log PL and resulted in a one-parameter global model characterized by satisfactory statistical performance; calibration (r2c) and prediction (r2p) correlation coefficient of 0.84 and 0.85, respectively. Moreover, local QSPR models were also developed for each subset of organic compounds and, as expected, the statistical results obtained from these models were better than the global one. From the descriptors involved in the models, it is concluded that the hydrophilic and hydrophobic regions at different energy levels and polarizability usually determine the variation of supercooled liquid vapour pressure of organic compounds.

3D-QSAR studies on the toxicity of substituted benzenes to Tetrahymena pyriformis: CoMFA, CoMSIA and VolSurf approaches.

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis were performed on the toxicity of a large set of substituted benzenes toward ciliate Tetrahymena pyriformis. The 3D-QSAR studies were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and VolSurf techniques. The optimal CoMFA and CoMSIA models obtained from the training set were all statistically significant with correlation coefficients (R(2)) greater than 0.79 and absolute error less than 0.33 in log units. The predictive ability of the models was externally evaluated through the prediction of a test set (20 percent of the whole data set) that were not included in the training set. A simple and fairly good predictive linear model based on VolSurf descriptors was also developed that showed an adequate prediction power of the toxicity (pIGC50) of substituted benzenes. Validation, reliability and robustness of models were also evaluated by leave-one-out, leave-four-out, bootstrapping and progressive scrambling approaches. The results confirmed that in addition to hydrophobic effects, electrostatic and H-bonding interactions also play important roles in the toxicity of substituted benzenes. The information obtained from CoMFA and CoMSIA 3-D contour maps could be useful to explain the toxicity mechanism of substituted benzenes.

Comparative molecular field analysis and comparative molecular similarity index analysis studies on 1H NMR chemical shift of NH group of diaryl triazene derivatives.

Comparative molecular field analysis (CoMFA), comparative molecular field analysis region focusing (CoMFA-RF) for optimizing the region for the final partial least square analysis, and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) models of (1)H NMR chemical shift of NH proton of diaryl triazene derivatives. The best orientation was searched by all-orientation search (AOS) strategy to minimize the effect of the initial orientation of the structures. The predictive abilities of CoMFA-RF and CoMSIA models were determined using a test set of ten compounds affording predictive correlation coefficients of 0.721 and 0.754, respectively, indicating good predictive power. For further model validation, cross validation (leave one out), progressive scrambling, and bootstrapping were also applied. The accuracy and speed of obtained 3D-QSAR models for the prediction of (1)H NMR chemical shifts of NH group of diaryl triazene derivatives were greater compared to some computational well-known procedures.