Desulphurization and Denitrification of Diesel Oil using Ionic Liquids: Experiments and Quantum Chemical Predictions discusses how quantum chemical calculations are applied to investigate the fundamental nature of the IL-sulphur-nitrogen systems at atomic and molecular levels. The book will help readers understand the nature of the structural relationship between molecules such as ionic liquid + aromatic sulphur + aromatic nitrogen system(s). In addition, COSMO-RS (Conductor Like Screening Model for Real Solvents) predictions and subsequent experimentation are discussed to evaluate the performance of ionic liquids for desulphurization and denitrification of diesel oil.

Covers application of Deep Eutectic Solvents (DES) in extraction of aromatics and polyaromatics from fuel oil by Liquid-Liquid extraction Studies eutectic behavior with respect to hydrocarbon and aqueous solutions Describes molecular dynamics insights of extraction by DES Explores possible industrial applicability of potential DES Includes results from Gaussian, NAMD and PACKMOL software packages

This book provides a comprehensive overview of ionic liquid based separation techniques. The glimpse of thermodynamic predictive models along with global optimization techniques will help readers understand the separation techniques at molecular and macroscopic levels. Experimental and characterization techniques are coupled with model based predictions so as to provide multicomponent data for the scientific community. The models will focus more on the a-priori based predictions which gives higher emphasis on hydrogen-bonded systems. Particle Swarm Optimization (PSO) technique will also eventually help the readers to apply optimization technique to an extraction process. The overriding goal of this work is to provide pathways for leading engineers and researchers toward a clear understanding and firm grasp of the phase equilibria of Ionic Liquid systems.

This book provides a comprehensive overview of ionic liquid based separation techniques. The glimpse of thermodynamic predictive models along with global optimization techniques will help readers understand the separation techniques at molecular and macroscopic levels. Experimental and characterization techniques are coupled with model based predictions so as to provide multicomponent data for the scientific community. The models will focus more on the a-priori based predictions which gives higher emphasis on hydrogen-bonded systems. Particle Swarm Optimization (PSO) technique will also eventually help the readers to apply optimization technique to an extraction process. The overriding goal of this work is to provide pathways for leading engineers and researchers toward a clear understanding and firm grasp of the phase equilibria of Ionic Liquid systems.