(544a) Combining Solvent Screening with Process Synthesis for Separating Refrigerant Mixtures Using Ionic Liquids | AIChE

(544a) Combining Solvent Screening with Process Synthesis for Separating Refrigerant Mixtures Using Ionic Liquids


Monjur, M. S. - Presenter, Texas A&M University
Iftakher, A., Texas A&M University, 3122 TAMU
Hasan, F., Texas A&M University
Hydrofluorocarbons (HFCs) and their mixtures are 3rd generation refrigerants that have widespread usage in cooling systems. However, some HFCs have very high global warming potential (GWP). One of the most commonly used mixture of HFCs is R-410A, which is an azeotropic mixture of R-32 (low-GWP) and R-125 (very high-GWP). As there are millions of tons of R-410A being used worldwide, there is an incentive to separate and reuse R-410A constituents. However, due to the azeotropic nature of many such refrigerant blends, conventional distillation is highly energy-intensive or infeasible. This requires the need for intensified processes such as extractive distillation (ED) that can separate azeotropic mixtures by using a suitable solvent [1]. As a solvent, ionic liquid (IL) is rapidly gaining attention for separating refrigerant mixtures. Several works have been reported that show the selective solubility of refrigerants in different ILs [2]. However, very few works have been reported that focus on the optimal design of ED-based separation processes [3-5].

Designing an ED column is challenging, as the selection of appropriate IL and its flowrate plays an important role in deciding the separation purity and the energy consumption. Optimal process synthesis requires the consideration of all plausible design configurations. For that purpose, we employ building block-based process representation [6] which allows us to design a process from its fundamental physicochemical phenomena level. Based on such representation we have developed a software prototype called SPICE_ED (Synthesis and Process Intensification of Chemical Enterprises involving Extractive Distillation) for the design, optimization, and intensification of ED-based processes [7]. Establishing confidence in the derived designs requires an accurate and reliable prediction of the underlying physical and thermodynamic phenomena. However, most of these models are non-convex, highly non-linear, and computationally cumbersome. To circumvent this issue, we have also developed GEMS (Guaranteed Error-bounded Modeling of Surrogates) framework, which generates surrogate property models with guaranteed bounds on the maximum prediction error [8]. GEMS is embedded within the SPICE_ED framework to help decrease the computational burden significantly. With this updated process synthesis framework, we have improved process performance in terms of energy, sustainability, and economics [7] compared to the previously reported flowsheet [9] for R-410A separation. We also extend our efforts by screening all the existing ILs that have selective solubility towards either R-32 or R-125. We provide a rank-ordered list of all the feasible ILs and the corresponding design configurations. Our results show that the top-performing IL-based ED process can outperform the previous configuration [7] by up to 15%. We also investigate the limit on the process improvement by constructing realistic ILs and performing property to process performance mapping. We conclude that the experimental efforts should be directed toward synthesizing R-32 selective ILs. The discovery of such an IL with moderate selectivity can result in the reduction of energy consumption of the processes by up to 30% compared to the currently best IL-based ED process.

Keywords: Process Intensification, Material Screening, Hydrofluorocarbons, Ionic Liquids, Extractive Distillation.


[1] Tian, Y., Demirel, S.E., Hasan, M.M.F. and Pistikopoulos, E.N., 2018. An overview of process systems engineering approaches for process intensification: State of the art. Chemical Engineering and Processing-Process Intensification, 133, pp.160-210.

[2] Asensio-Delgado, S., Pardo, F., Zarca, G. and Urtiaga, A., 2021. Absorption separation of fluorinated refrigerant gases with ionic liquids: Equilibrium, mass transport, and process design. Separation and Purification Technology, 276, p.119363.

[3] Finberg, E.A. and Shiflett, M.B., 2021. Process Designs for Separating R-410A, R-404A, and R-407C Using Extractive Distillation and Ionic Liquid Entrainers. Industrial & Engineering Chemistry Research, 60(44), pp.16054-16067.

[4] Asensio-Delgado, S., Jovell, D., Zarca, G., Urtiaga, A. and Llovell, F., 2020. Thermodynamic and process modeling of the recovery of R410A compounds with ionic liquids. International Journal of Refrigeration, 118, pp.365-375.

[5] Garciadiego, A., Mazumder M., Befort B. J. and Dowling A. W., Techno-economic Analysis of Extractive Distillation of Ternary Hydrofluorocarbon Mixtures using Ionic Liquid Entertainers. Proceedings of the 14th International Symposium on Process Systems Engineering – PSE 2021+, Accepted.

[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] Monjur, M.S., Iftakher, A. and Hasan, M. M. F., 2022. Separation Process Synthesis for High-GWP Refrigerant Mixtures: Extractive Distillation using Ionic Liquids. Industrial & Engineering Chemistry Research, 61(12), pp.4390–4406.

[8] Iftakher, A., Aras, C. M., Monjur, M.S. and Hasan, M. M. F., A Framework for Guaranteed Error-bounded Surrogate Modeling. Proceedings of the 2022 American Control Conference (ACC), Accepted.

[9] 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.