Process Simulation and Multiobjective Optimization for High-Purity Hexane Recovery Using Deep Eutectic Solvent

Deep eutectic solvents (DESs) are an experimentally proven and attractive solvent in the field of green chemistry for aromatic extraction from a mixture of aliphatic–aromatic mixtures. The current work reports a multiscale strategy using quantum chemical calculations, thermodynamic models, process simulation, and multiobjective optimization for the simultaneous production of high-purity hexane and aromatic removal using the DES methyl triphenyl phosphonium bromide/ethylene glycol (1:4). Initially the phase equilibrium data have been benchmarked through the continuum solvation-based COSMO-SAC model, which has a root-mean-square deviation of 5.81%. Thereafter, a conceptual multiloop extraction and solvent recovery process has been developed and simulated that incorporates sensitivity analysis to analyze the impact of different process parameters on the system. These parameters, namely, annualized capital cost, benzene content in the hexane product stream, and hexane recovery, have been further formulated as three separate objective functions to be optimized using a nondominated sorting genetic algorithm. After optimization, a series of solutions have been obtained from the Pareto front. The results provide 92% hexane recovery with a benzene concentration of less than 50 ppm. This shall enable the industrial production of high-purity hexane using efficient and sustainable green solvents.