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.