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Investigating the Increased CO2 Capture Performance of Amino Acid Functionalized Nanoporous Materials from First-Principles and Grand Canonical Monte Carlo Simulations
The Journal of Physical Chemistry Letters ( IF 4.8 ) Pub Date : 2023-05-25 , DOI: 10.1021/acs.jpclett.3c00998
Robert Stanton 1 , Dhara J Trivedi 1
Affiliation  

Nanoporous materials such as metal–organic frameworks (MOFs) and covalent–organic frameworks (COFs) have been identified as key candidates for environmental remediation through catalytic reduction and sequestration of pollutants. Given the prevalence of CO2 as a target molecule for capture, MOFs and COFs have seen a long history of application in the field. More recently, functionalized nanoporous materials have been demonstrated to improve performance metrics associated with the capture of CO2. We employ a multiscale computational approach including ab initio density functional theory (DFT) calculations and classical grand canonical Monte Carlo (GCMC) simulations, to investigate the impact of amino acid (AA) functionalization in three such nanoporous materials. Our results demonstrate a nearly universal improvement of CO2 uptake metrics such as adsorption capacity, accessible surface area, and CO2/N2 selectivity for six AAs. In this work, we elucidate the key geometric and electronic properties associated with improving the CO2 capture performance of functionalized nanoporous materials.

中文翻译:

从第一性原理和 Grand Canonical Monte Carlo 模拟研究氨基酸功能化纳米多孔材料提高的 CO2 捕获性能

金属有机框架 (MOF) 和共价有机框架 (COF) 等纳米多孔材料已被确定为通过催化还原和隔离污染物进行环境修复的主要候选材料。鉴于 CO 2作为捕获目标分子的普遍存在,MOF 和 COF 在该领域的应用历史悠久。最近,功能化的纳米多孔材料已被证明可以改善与 CO 2捕获相关的性能指标。我们采用多尺度计算方法,包括从头算起密度泛函理论 (DFT) 计算和经典大规范蒙特卡罗 (GCMC) 模拟,以研究氨基酸 (AA) 功能化对三种此类纳米多孔材料的影响。我们的结果表明,六种氨基酸的 CO 2吸收指标几乎普遍得到改善,例如吸附容量、可及表面积和 CO 2 /N 2选择性。在这项工作中,我们阐明了与提高功能化纳米多孔材料的 CO 2捕获性能相关的关键几何和电子特性。
更新日期:2023-05-25
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