Incorporation of ligand charge and metal oxidation state considerations into the computational solvent removal and activation of experimental crystal structures preceding molecular simulation

17 October 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Efficient computational screenings are integral to materials discovery in highly sought-after gas adsorption and storage applications, such as CO2 capture. Preprocessing techniques have been developed to render experimental crystal structures suitable for molecular simulations by mimicking experimental activation protocols, particularly residual solvent removal. Current accounts examining these preprocessed materials databases indicate the presence of assorted structural errors introduced by solvent removal and preprocessing, including improper elimination of charge-balancing ions and ligands. Here, we address the need for a reliable experimental crystal structure preprocessing protocol by introducing a novel solvent removal method, which we call SAMOSA, that is informed by systematic ligand charge and metal oxidation state calculations. A robust set of solvent removal criteria are outlined which identify solvent molecules and counterions without predefined molecule lists or significant reliance on experimental chemical information. Validation results against popular metal-organic framework (MOF) databases suggest that this method observes significant performance improvements regarding the retention of charged ligands and recognition of charged frameworks. SAMOSA enhances structure fidelity with respect to the original material as-synthesized, thereby representing a powerful tool in computational materials database curation and preprocessing for molecular simulation.

Keywords

Metal Organic Frameworks
Materials Databases
solvent removal
high throughput screening

Supplementary materials

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Additional figures and tables relating to the utilization and outputs of the SAMOSA solvent removal code, details relating to the core algorithms, and the manual validation and benchmarking of solvent removal performance.
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