Sharif Digital Repository

The inhibition effects of sodium dodecylbenzenesulphonate (SDBS) and hexamethylenetetramine (HA) on the corrosion of mild steel in sulphuric acid solution have been studied using weight loss, electrochemical impedance and Tafel polarisation measurements. For HA, a monotonous increase in inhibition efficiency is observed as a function of concentration. For SDBS, however, an optimum in the inhibition efficiency is observed for a concentration close to 250 ppm, which is ascribed to the formation of hemi-micellar aggregates that provoke inhibitor desorption from the metal/solution interface at higher concentrations. Upon mixing HA and SDBS, concentration regions showing synergistic and... 

The objective of this study was to investigate the synergistic effect of TBP on the system D2EHPA/kerosense/M2+ with respect to the extraction of some transitional metals. Although the presence of M2EHPA as an impurity in D2EHPA shifts the extraction curves to lower pH, empirical results show that the extraction curves shift to the right due to the addition of TBP and the counterbalance effect of M2EHPA. The results indicate that the equivalent concentration of D2EHPA decreases as a function of concentration of TBP because of the formation of hydrogen bonds between TBP and D2EHPA. Based on this finding, the D2EHPA equivalent concentration was determined by using a modifying factor for TBP... 

Bayesian regularised genetic neural network (BRGNN) has been used for modelling the inhibition activity of 141 biphenylalanine derivatives as integrin antagonists. Three local pattern search (PS) methods, simulated annealing and threshold acceptance were combined with BRGNN in the form of a hybrid genetic algorithm (HGA). The results obtained revealed that PS is a suitable method for improving the ability of BRGNN to break out from the local minima. The proposed HGA technique is able to retrieve important variables from complex systems and nonlinear search spaces for optimisation. Two models with 8-3-1 artificial neural network (ANN) architectures were developed for describingα 4β 7 and α 4β... 

The present work focuses on the development of an interpretable quantitative structure-activity relationship (QSAR) model for predicting the anti-HIV activities of 67 thiazolylthiourea derivatives. This set of molecules has been proposed as potent HIV-1 reverse transcriptase inhibitors (RT-INs). The molecules were encoded to a diverse set of molecular descriptors, spanning different physical and chemical properties. Monte Carlo (MC) sampling and multivariate adaptive regression spline (MARS) techniques were used to select the most important descriptors and to predict the activity of the molecules. The most important descriptor was found to be the aspherisity index. The analysis of variance...