Automated structure generation for first-principles transition-metal catalysis

Abstract

Efficient discovery of new catalytic materials necessitates the rapid but selective generation of candidate structures from a very wide chemical space and the efficient estimation of their properties. We developed an efficient and reliable software utility for high-throughput screening of inorganic complexes that enables chemical discovery by automating molecular and intermolecular complex structure generation, job preparation as well as post-processing analysis to elucidate correlations of electronic or geometric descriptors with energetics. The developed software was then used to unveil different binding modes of small anions on organometallic complexes as well as functionalizations that allow for selective binding. We additionally employed our materials design framework to study the binding of carbon monoxide on functionalized metalloporphyrins providing tuning strategies and uncertainty estimation.

Computational approaches such as density functional theory (DFT) that directly simulate the electronic properties have been increasingly used as tools for materials design mainly due to recent developments in computational speed and accuracy. DFT recasts the many-body problem of interacting electrons into an equivalent problem of non-interacting electrons, greatly simplifying the solution procedure. This approach introduces certain approximations that are effectively modeled with an exchange and correlation functional that accounts for the many-body effects that are not included in the simplified problem. The functional choice is an important modeling decision and therefore computational predictions can be sensitive to user selection. This sensitivity is maximized for systems with highly localized electrons such as transition metals due to self-interaction error, where one electron interacts with its own mean field resulting in an unphysical delocalization of the electron density.

We studied extensively how the incorporation of the widely employed Hartree-Fock and meta-GGA-type exchange functionals affects DFT predictions on transition metal complexes.