Model Compound Studies on the Devulcanization of Natural Rubber Using 2, 3-Dimethyl-2-Butene

The mechanism of devulcanization of sulfur-vulcanized natural rubber with aromatic disulfides and aliphatic amines has been studied using 23-dimethyl-2-butene (C5H1,) as a low-molecular weight model compound. First C6H12 was vulcanized with a mixture of sulfur, zinc stearate and N-cyclohexyl-2-benzothiazylsulfenamide (CBS) as accelerator at 140 °C, resulting in a mixture of addition products (C(,H 1 i-S,-C5H 1 i ). The compounds were isolated and identified by High Performance Liquid Chromatography (HPLC) with respect to their various sulfur ranks. In it second stage, the vulcanized products were devulcanized using the agents mentioned above at 200 °C. The kinetics and chemistry of the breakdown of the sulfur-hridges were monitored. Both devulcanization agents decompose sulfidic vulcanization products with sulfur ranks equal or higher than 3 quite effectively and with comparable speed. Di phenyldisulfide as devulcanization agent gives rise to a high amount of mono- and disulfidic compounds formed during the devulcanization, hexadecylamine, as devulcanization agent, prevents these lower sulfur ranks from being formed.

Studies on the Dipping Characteristics of RVNRL and NRLatex Compounds

ABSTRACT: The dipping characteristics of radiation-vulcanized natural rubber latex and natural rubber latex compounds were investigated with a lab-model semiautomatic dipping machine. The effect of the variation of the speed of immersion and withdrawal, dwell time, compound viscosity, and concentration of coagulant on the thickness of the latex deposit was investigated. The results of the study show that the deposit thickness depends on the withdrawal speed of the former, the concentration of the coagulant, dwell times, and the viscosity of the latex compounds

“Investigations on Vibrational Overtones in the NIR region and Laser Induced Fluorescence in some selected compounds”

The central theme of this research concerns the study of vibrationally excited molecules. We have used the local mode description of such vibrational states, and this -model has now gained general acceptance. A central feature of the model is the Wloealizafion of vibrational energy. A study of these high—energy localized states provides example, becauseof this localization, overtone spectra, which measure the absorption of T vibrational energy, are extremely sensitive to the properties of X-H bonds. We also use -overtone spectra to study the conformation of molecules, i.e., the relative internal orientation of their bonds. The thesis comprises six chapters

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576