On the Automation of High Throughput Modeling of Adsorption In Porous Zeolitic Imidazolate Frameworks

Abstract: The zeolitic imidazolate frameworks (ZIF) have emerged as a promising candidate for catalysis, carbon-dioxide (CO${2}$) capture and storage as well as flue gas separation due to their tunable porosity and chemical stability. ZIFs consists of transition metals in a tetrahedral coordination with imidazolate linkers, allowing for structural modifications that can enhance CO${2}$ adsorption and storage. To systematically design and optimize ZIFs for superior CO${2}$ capture performance, theoretical modelling provides an effective approach, though hindered by the sheer size of the search space, with hundred to thousands of possible sites per ZIF, and thousands of possible ZIF that can be synthesized. In this work, we employ a high-throughput techniques underpinned by first-principle Density Functional Theory (DFT) to develop a systematic automated method for characterizing adsorption energetics in ZIFs, guiding the rational design and selection of desirable ZIF structures. Using high-throughput computing tools, we perform pore and pore size analysis, and implement automated CO${2}$ molecule placement algorithm, accounting for positional symmetry, crystallographic orientation, and collision detection. The results obtained are in good agreement with previous studies, demonstrating the reliability of the approach in accelerating the discovery of next-generation ZIFs for CO$_{2}$ capture and storage.