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Molecular Building Block-Based Electronic Charges for High-Throughput Screening of Metal–Organic Frameworks for Adsorption Applications

纳米孔 吸附 块(置换群论) 从头算 静电学 分子 材料科学 吞吐量 金属有机骨架 计算机科学 化学 化学物理 纳米技术 物理化学 有机化学 电信 无线 数学 几何学
作者
Edwin Argueta,Jeena Shaji,Arun Gopalan,Peilin Liao,Randall Q. Snurr,Diego A. Gómez‐Gualdrón
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:14 (1): 365-376 被引量:18
标识
DOI:10.1021/acs.jctc.7b00841
摘要

Metal-organic frameworks (MOFs) are porous crystalline materials with attractive properties for gas separation and storage. Their remarkable tunability makes it possible to create millions of MOF variations but creates the need for fast material screening to identify promising structures. Computational high-throughput screening (HTS) is a possible solution, but its usefulness is tied to accurate predictions of MOF adsorption properties. Accurate adsorption simulations often require an accurate description of electrostatic interactions, which depend on the electronic charges of the MOF atoms. HTS-compatible methods to assign charges to MOF atoms need to accurately reproduce electrostatic potentials (ESPs) and be computationally affordable, but current methods present an unsatisfactory trade-off between computational cost and accuracy. We illustrate a method to assign charges to MOF atoms based on ab initio calculations on MOF molecular building blocks. A library of building blocks with built-in charges is thus created and used by an automated MOF construction code to create hundreds of MOFs with charges "inherited" from the constituent building blocks. The molecular building block-based (MBBB) charges are similar to REPEAT charges-which are charges that reproduce ESPs obtained from ab initio calculations on crystallographic unit cells of nanoporous crystals-and thus similar predictions of adsorption loadings, heats of adsorption, and Henry's constants are obtained with either method. The presented results indicate that the MBBB method to assign charges to MOF atoms is suitable for use in computational high-throughput screening of MOFs for applications that involve adsorption of molecules such as carbon dioxide.
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