Experimental Analysis and NRTL Parameters Estimation Using PSO Method for Dibenzothiophene Extraction from Fuel with Deep Eutectic Solvent

Mohebbi, Vahid; Kazemi Golbaghi, Hamed

doi:10.22034/ijche.2025.501285.1492

Experimental Analysis and NRTL Parameters Estimation Using PSO Method for Dibenzothiophene Extraction from Fuel with Deep Eutectic Solvent

Articles in Press

Document Type : Original Article

Authors

Vahid Mohebbi

Hamed Kazemi Golbaghi

Petroleum University of Technology

10.22034/ijche.2025.501285.1492

Abstract

Separation of sulfur-containing compounds from fuel remains one of the major challenges in crude oil refining processes. Extractive desulfurization using deep eutectic solvents (DES) has gained the attention of researchers as an effective method for removing these compounds from fuel. In this study, binary interaction parameters of the Non-Random Two-Liquid (NRTL) model were estimated using equilibrium solubility data of dibenzothiophene in the model fuel and the eutectic solvent (choline chloride and diethylene glycol), applying the Particle Swarm Optimization (PSO) algorithm. Subsequently, the developed thermodynamic model was employed to predict the extractive desulfurization performance. Modeling results indicate that the separation efficiency increases at lower temperatures and with a higher solvent-to-fuel ratio. Specifically, at 20 °C, increasing the solvent ratio from 0.1 to 3 led to an increase in DBT removal from 1.9% to 37%, while at 60 °C, the efficiency increased from 1.7% to 34%.

Keywords

Extractive Desulfurization

Deep Eutectic Solvent

Solid-liquid Equilibria

Thermodynamic Modeling

Particle Swarm Algorithm

Subjects