(317g) SPICE_ED: A Framework for Simultaneous Materials Screening and Process Synthesis for Extractive Distillation

Distillation is the most widely used technology for separating mixtures into pure components in the chemical process industry [1]. However, conventional distillation is energy-intensive and often fails to meet the purity requirement for azeotropic mixtures. Extractive distillation (ED) is an intensified process that uses a low-volatile solvent as entrainer and can separate azeotropic mixtures into pure components [2]. ED has additional degrees of freedom (DOF) because of the choices for solvent selection and flow rates [3]. While many works (e.g., [3-5]) have addressed ED design, a systematic framework is still required for optimal synthesis, optimization, and further integration of ED configurations in an end-to-end processing network aka process flow diagram. Furthermore, recent emphasis on inherently sustainable, energy-efficient, and environmentally benign process design requires in-tandem selection of candidate solvents at the conceptual design stage.

Building block-based representation [6] of chemical process flowsheets was first used in developing the prototype design tool SPICE (Synthesis and Process Intensification of Chemical Enterprises) and was further modularized to specifically incorporate reactive distillation [7], membrane separation [8], and membrane reactors [9]. In this work, we introduce a new module SPICE_ED (SPICE involving Extractive Distillation). SPICE_ED specializes in systematic process synthesis, intensification, and optimization of ED columns and associated process configurations. SPICE_ED employs a mixed-integer nonlinear model (MINLP)-based equation-oriented design approach, where the conceptual decisions are represented using design building blocks. Based on user-defined specifications on feed (flow rates, composition, thermo-physical properties) and product purity and demand constraints, SPICE_ED performs automatic synthesis of optimal ED flowsheets. A key feature is the efficient prediction of fluid properties, phase equilibrium, and solvent-extraction phenomena using both rigorous and surrogate thermodynamic packages and detailed mathematical models e.g., equation-of-states (Peng Robinson or van der Waals) and Gamma-Phi method with NRTL model. Computational efficiencies are obtained by using reliable surrogate models (R²> 0.99) for thermodynamic and physical properties. This allows us to generate detailed configurations of ED columns considering appropriate feed inlet trays, boil-up, and reflux ratios, and side product stream trays. Furthermore, we can perform large-scale computational screening and selection of solvents, such as ionic liquids (ILs), for designing ED-based separation process involving azeotropic mixtures. In this context, SPICE_ED can be also used to generate structure-property-performance-process relationships mapping the entire range of solvent design space. We illustrate these capabilities by solving a simultaneous material selection and process design problem involving IL-based extractive distillation for hydrofluorocarbons (HFC) separation. Specifically, for the separation of R-410A, which is a refrigerant mixture of two HFCs (R-32 and R-125), SPICE_ED suggests an optimized process flowsheet that reduces the energy consumption by 65% from the base case flowsheet [11]. Additionally, the optimized process is environmentally sustainable as it emits 72% less indirect CO₂.

References:

[1] Humphrey, J.L., 1995. Separation processes: playing a critical role. Chemical Engineering Progress, 91(10).

[2] Lei, Z., Dai, C., Zhu, J. and Chen, B., 2014. Extractive distillation with ionic liquids: a review. AIChE Journal, 60(9), pp.3312-3329.

[3] Kossack, S., Kraemer, K., Gani, R. and Marquardt, W., 2008. A systematic synthesis framework for extractive distillation processes. Chemical Engineering Research and Design, 86(7), pp.781-792.

[4] Emhamed, A.M., Czuczai, B., Rev, E. and Lelkes, Z., 2008. Analysis of extractive distillation with mathematical programming. Industrial & engineering chemistry research, 47(24), pp.9983-9995.

[5] Valencia-Marquez, D., Flores-Tlacuahuac, A. and Vasquez-Medrano, R., 2012. Simultaneous optimal design of an extractive column and ionic liquid for the separation of bioethanol–water mixtures. Industrial & engineering chemistry research, 51(17), pp.5866-5880.

[6] Demirel, S.E., Li, J. and Hasan, M.M.F., 2017. Systematic process intensification using building blocks. Computers & Chemical Engineering, 105, pp.2-38.

[7] Demirel, S.E., Li, J., El-Halwagi, M.M. and Hasan, M.M.F., 2020. Sustainable Process Intensification Using Building Blocks. ACS Sustainable Chemistry & Engineering, 8(48), pp.17664-17679.

[8] Demirel, S.E., Li, J. and Hasan, M.M.F., 2021. Membrane Separation Process Design and Intensification. Industrial & Engineering Chemistry Research, DOI: 10.1021/acs.iecr.0c05072.

[9] Monjur, M.S., Demirel, S. E., Li, J. and Hasan, M.M.F., 2021. SPICE_MARS: A Process Synthesis Framework for Membrane-Assisted Reactive Separations. Industrial & Engineering Chemistry Research, Under Review.

[10] Shiflett, M.B. and Yokozeki, A., 2006. Separation of difluoromethane and pentafluoroethane by extractive distillation using ionic liquid. Chimica oggi, 24(2), pp.28-30.