The continuing development of a wide variety of novel adsorbents raises new possibilities for improving efficiencies in natural gas purification by pressure swing adsorption (PSA). However, designing an effective industrial scale PSA process requires expensive and time consuming pilot-scale testing. This highlights the need for effective in silico material screening tools. Currently, most performance metrics used for material screening focus on material properties such as adsorption capacity and product selectivity. However, restricting attentions solely onto the material properties effectively ignores critical features of the overall adsorption processes in PSA. On the other hand, studies that consider the overall process require the solution of complex design optimization problems for PSA given each adsorbent; This requires significant expertise from the practitioner. To address these limitations, a simplified dynamic model is presented along with heuristics based PSA process design rules that enable practitioners to easily evaluate relevant PSA process performance metrics through dynamic simulation, using only adsorbent material properties including isotherms and basic design specifications such as the feed composition and desired purity and recovery.
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