Kwon Ohmin, Gibaldi Marco, Pai Kasturi Nagesh, Rajendran Arvind, Woo Tom K
Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie Curie Private, Ottawa, Ontario K1N 6N5, Canada.
Department of Chemical and Materials Engineering, University of Alberta, 12th floor, Donadeo Innovation Centre for Engineering (ICE), 9211-116 Street, Edmonton, Alberta T6G1H9, Canada.
ACS Cent Sci. 2025 Jul 7;11(8):1438-1451. doi: 10.1021/acscentsci.5c00777. eCollection 2025 Aug 27.
Metal-organic framework (MOF) materials have attracted significant attention as solid sorbents for low energy CO capture with adsorption-based gas separation processes. In this work, an integrated screening workflow combining a series of atomistic and process simulations was applied to identify promising MOFs for a 4-step pressure-vacuum swing adsorption (P/VSA) process at three different CO flue gas compositions (6%, 15% and 35%). Starting from 55,818 unique experimentally characterized MOFs, ∼19k porous MOFs were investigated via atomistic grand canonical Monte Carlo (GCMC) simulations and machine learning model-based process optimizations to accelerate the screening of a large candidate database. Thousands of MOFs were identified for each of the CO compositions tested that could achieve within 4% of the practical energy limit of dry CO capture for the P/VSA process while still meeting the 95% CO purity and 90% recovery constraints. From this pool, 3D MOFs without open metal sites were subjected to the multicomponent (CO/N/HO) GCMC simulations at 40% relative humidity. Based on these simulations, hundreds of MOFs were identified at each CO composition that could retain 90% of their CO capture at this humidity while also adsorbing a minimal amount of water. A geometric analysis of these high performing materials revealed that narrow, straight 1D-channels were a common structural motif for low energy wet flue gas CO capture with P/VSA.
金属有机框架(MOF)材料作为基于吸附的气体分离过程中用于低能耗二氧化碳捕集的固体吸附剂,已引起了广泛关注。在这项工作中,采用了一系列原子模拟和过程模拟相结合的综合筛选流程,以确定在三种不同二氧化碳烟气组成(6%、15%和35%)下,适用于四步变压变真空吸附(P/VSA)过程的有前景的MOF材料。从55,818种具有独特实验表征的MOF材料开始,通过原子巨正则蒙特卡罗(GCMC)模拟和基于机器学习模型的过程优化,对约19k种多孔MOF材料进行了研究,以加速对大型候选数据库的筛选。对于所测试的每种二氧化碳组成,都鉴定出了数千种MOF材料,这些材料在P/VSA过程中实现的干二氧化碳捕集实际能量极限的4%以内,同时仍满足95%的二氧化碳纯度和90%的回收率约束。从这个库中,对没有开放金属位点的三维MOF材料在40%相对湿度下进行了多组分(CO/N₂/H₂O)GCMC模拟。基于这些模拟,在每种二氧化碳组成下都鉴定出了数百种MOF材料,这些材料在该湿度下可以保持其90%的二氧化碳捕集量,同时吸附的水量也最少。对这些高性能材料的几何分析表明,狭窄、笔直的一维通道是采用P/VSA进行低能耗湿烟气二氧化碳捕集的常见结构特征。