Efficient and Accurate Charge Assignments via a Multilayer Connectivity-Based Atom Contribution (m-CBAC) Approach

Metal–organic frameworks (MOFs) have drawn considerable attention for their potential in a variety of energy applications such as gas separations and storage. With thousands of MOFs reported and more being discovered, molecular simulations can play a critical role in facilitating the material discovery. In those calculations, accurate charge assignments to the framework atoms are essential. In this study, we expand on the connectivity-based atom contribution (CBAC) method to develop an efficient, robust, and accurate approach for charge assignments. Distinct from the original CBAC method, which uses 1st layer connectivity of a target atom, our approach, denoted as multilayer CBAC (m-CBAC), incorporates multilayer connectivity up to 2nd layers. An extensive set of ∼2700 MOFs with the density-derived electrostatic and chemical (DDEC) charges is used to train the databases. The approach assigns charges in a systematic manner, where the highest-level connectivity database (i.e., 2nd-layer connectivity) is first searched, followed by lower-level connectivity patterns until the connectivity pattern is recognized. This approach makes the charge predictions feasible to almost all MOFs. Our results show that the charges assigned using m-CBAC resemble the DDEC charges very well (Pearson coefficient of 0.988). At the same time, the m-CBAC approach is computationally efficient, which is orders of magnitude faster than quantum mechanical approaches. Also, this study demonstrates that the accurate charge assignments from m-CBAC lead to reliable predictions on the Henry coefficient of CO2 in MOFs. Overall, the m-CBAC approach can enable fast charge assignments for MOFs with good accuracy, and a software for m-CBAC charge assignments together with charges assigned for ∼12 000 MOFs in a recently released MOF database is made available along with this work.