Large-Scale Quantitative Structure–Property Relationship (QSPR) Analysis of Methane Storage in Metal–Organic Frameworks

Abstract

Metal–organic frameworks (MOFs) present a combinatorial design challenge. The structural building blocks of MOFs can be combined to synthesize a nearly infinite number of materials. This suggests that computational tools, rather than experimental trial and error, can be used for high-throughput screening. Here, in the context of methane storage, we report the first large-scale, quantitative structure–property relationship (QSPR) analysis of MOFs. We investigated the effect of geometrical features, such as pore size and void fraction, on the simulated methane storage capacities of ∼130 000 hypothetical MOFs at 1, 35, and 100 bar at 298 K. From these data we developed models that can predict methane storage with high accuracy, based only on knowledge of the geometric features. Several models were developed: multilinear regression (MLR) models, decision trees (DTs), and nonlinear support vector machines (SVMs). In each case, 10 000 MOF structures were used to “train” the QSPR regression models, and the accur...