Abstract

Adsorbent performance evaluation metrics such as selectivity and regenerability that can be computed from the results of molecular simulations are widely used to identify the most promising metal organic frameworks (MOF) for separation of CO2/N2 mixture. Parasitic energy is recently offered to rank the MOFs for comparing the cost-effectiveness of an adsorption-based CO2/N2 separation process. In this work, we performed Grand Canonical Monte Carlo simulations for 1661 MOFs to compute CO2/N2 mixture adsorption data and then calculated selectivity, working capacity, adsorbent performance score (APS), regenerability (R%) of MOFs and parasitic energy. MOFs were ranked following two different approaches, one based on a combination of APS and R%, the other based on parasitic energy. Results showed that many MOFs are common in the top 100 adsorbents list of the two approaches, but the rankings of MOFs significantly differ since materials offering a low parasitic energy do not necessarily have a high R%. These results will provide important insights into the ranking of large number of MOFs based on different performance metrics for efficient identification of the most promising adsorbents for flue gas separation.

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