Virtual high throughput screening has emerged as a powerful tool for the discovery of new materials. Nevertheless, screening of inorganic complexes is presently limited by the high cost of accurate property evaluation and the large, complex chemical space spanned by candidates. To address these challenges, we have recently developed molSimplify, an open-source toolkit for the automated generation of highly accurate inorganic molecular structures and automated property correlation analysis to accelerate high throughput screening of inorganic complexes. In conjunction with our structure generation toolkit, we have also developed and implemented a robust and automated workflow involving: (1) selection of a test set of ligands maximizing relative molecular diversity, (2) density functional theory calculations on the test set to elucidate design rules and (3) screening of multi-million molecule organic libraries to discover experimentally accessible ligand candidates. We demonstrate the broad utility of our integrated approach to inorganic complex discovery across a number of applications, including the design of bio-inspired single-site Fe(II) catalysts for oxygen activation. We also demonstrate the potential for molSimplify to accelerate catalytic property evaluation by automatically generating high-quality transition state guesses for common reactions in inorganic chemistry.

Accelerating the first-principles discovery of biomimetic catalysts

254th National Meeting (2017)

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