Spin coating technique has been applied in this work to prepared Xerogel films doped with Rhodamine 6G laser dyes. The solid host of laser dye modifies its spectroscopic properties with respect to liquid host. During the spin coating process the dye molecules suffer from changing their environment. The effects of three parameters were studied here: the spinning speed, multilayer coating and formaldehyde addition

In this study, the kinetics for the reaction of tert-butanol esterification with acetic acid in the presence of Dowex 50Wx8 catalyst was investigated. The reaction kinetic experiments were conducted in 1000 milliliter vessel at temperatures ranged from 50 - 80 oC, catalyst loading 25-50 g/L, and the molar ratios of acetic acid to tert-butanol from 1/3 – 3/1. The reaction rate was found to increase with increasing temperature and catalyst loading. It was also found the conversion of the tert-butanol increases as the molar ratio of acid to alcohol increases from 1/3 – 3/1. The Non-ideality of the liquid phase was taken into account by using activities instead of molar fractions. The activity coefficients were calculated according to th

Adsorption and ion exchange are examples of fixed-bed sorption processes that show transient behavior. This means that differential equations are needed to design them. As a result, numerical methods are commonly utilized to solve these equations. The solution frequently used in analytical methods is called the Thomas solution. Thomas gave a complete solution that adds a nonlinear equilibrium relationship that depends on second-order reaction kinetics. A computational approach was devised to solve the Thomas model. The Thomas model's validity was established by conducting three distinct sets of experiments. The first entails the adsorption of acetic acid from the air through the utilization of activated carbon. Following

The primary focus of the study factor reverse polymerization styrene polymer kinetics and distribution weight Aljaia in Blma Aldhur free reverse The study was conducted wi Mamahakah and using the Monte Carlo method

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance