Using density functional theory, two mechanisms of covalent adsorption of benzenesulfonamide in water in the presence of functionalised carbon nanotubes were investigated. COOH– and COCl–functionalised carbon nanotubes can bond to the benzenesulfonamide via OH (OH pathway) and Cl (Cl pathway) groups, respectively. The activation energy and activation Gibbs free energy of the two pathways have been calculated and compared with each other. It was found that the OH pathway has an energy barrier higher than the Cl pathway and, in contrast to the Cl pathway, product formation is endothermic and non-spontaneous, being thus the reason for the dominance of the Cl pathway. All the calculations were performed using a hybrid density functional method (B3LYP) in the solution phase (polarised continuum model or PCM).

In this work, using quantum mechanics, different fluxional mechanisms in a Pd(η 2 -olefin) complex including sulfur inversion, olefin pseudo rotation, Pd-olefin bond dissociation, propeller-like olefin rotation and a bimolecular process have been investigated theoretically in a solvent environment using the polarisable continuum model (PCM). The activation energy, activation enthalpy and activation Gibbs free energy of the different pathways have been calculated and compared with each other and with experimental results. These activation energies for olefin pseudo rotation, Pd-olefin bond dissociation and propeller-like olefin rotation are greater in comparison with those for the sulfur inversion and bimolecular process, which demonstrates that these latter mechanisms are the dominating paths and make the main contributions in the reaction. The computed activation enthalpies of the sulfur inversion and bimolecular process pathways are in good agreement with the experimental values. All of the calculations have been performed using a hybrid density functional method (B3LYP) in the solution phase.

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ABSTRACT. The different calculated quantum chemical descriptors by DFT method were used for prediction of some sulphanilamide Schiff bases inhibitor activity as a binding constant (log K). Multiple linear regression (MLR) and artificial neural network (ANN) were employed for developing the useful quantitative structure activity relationship (QSAR) model. The obtained results presented superiority of ANN model over the MLR one. The offering QSAR model is very easy to computation and Physico-Chemically interpretable. Sensitivity analysis was used to determine the relative importance of each descriptor in ANN model. The order of importance of each descriptor according to this analysis is: molecular volume, molecular weight and dipole moment, respectively. These descriptors appear good information related to different structure of sulphanilamide Schiff bases can participate in their inhibitor activity.