Extractive Distillation with Ionic Liquids To Separate Benzene, Toluene, and Xylene from Pyrolysis Gasoline: Process Design and Techno-Economic Comparison with the Morphylane Process

Abstract

Aromatic/aliphatic separation stands as a challenge for both industry and academia. More and more efforts are being made to improve energy-demanding technologies based on liquid−liquid extraction or extractive distillation processes. Recently, ionic liquid-based technologies devoted to separating benzene, toluene, and xylene from pyrolysis gasoline have been evaluated, and extractive distillation showed more potential than liquid−liquid extraction in terms of separation performance and global energy requirements. In this work, extractive distillation with ionic liquids is completely evaluated from solvent selection to rate-based process design and compared with the Morphylane benchmark process. The ILUAM database is explored through a validated COSMO/Aspen methodology to understand the impact of the ionic liquid nature on the extractive distillation operation. A parametric study focused on the extractive distillation column (EDC) is conducted for preliminary set initial guesses to design task. The final issue is centered on rigorously designing the ionic liquid-based and Morphylane processes at commercial specifications. Two different ionic liquid-based process configurations are evaluated based on the opportunities that the use of ionic liquids enables. The new process configuration working with [emim][TCM] reduces the energy costs and capital expenditures associated with the Morphylane process by 67 and 63%, respectively, along with a reduction in the solvent costs, confirming it as a cleaner alternative. In addition, a parametrization of the Cubic Plus Association equation of state (CPA EoS) obtained from the regression of experimental vapor−liquid−liquid equilibrium data is also used to simulate the EDC in equilibrium and rate-based mode. Both models provide similar results, confirming the ability of the conductor-like screening model−segment activity coefficient model as an a priori tool and the reliability of the CPA EoS as a regressive alternative to describe these kinds of complex multicomponent systems.