Bond-Valence Parameterization for the Accurate Description of DFT Energetics

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Abstract

We report a bond-valence method (BVM) parameterization framework that captures density functional theory (DFT)-computed relative stabilities using the BVM global instability index (GII). We benchmarked our framework against a dataset of 188 experimentally observed ABO3 perovskite oxides, each of which was generated in 11 unique Glazer octahedral tilt systems and optimized using DFT. Our constrained minimization procedure minimizes the GIIs of the 188 perovskite ground state structures predicted by DFT while enforcing a linear correlation between the GIIs and DFT energies of all 2068 competing structures. GIIs based on BVM parameters determined using our framework correctly identified the DFT ground state perovskite structure in 135 of 188 compositions or one of the two lowest energy structures in 152 of 188 compositions. Using the most common approach to parameterize BVM, which minimizes the root-mean-square deviation of the BVM site discrepancy factors, GIIs correctly identified the DFT ground state perovskite structure in only 41 of 188 compositions. Our new parameterization framework is therefore a marked improvement over the existing procedure and an important first step toward BVM-based structure generation protocols that reproduce DFT.

Original languageEnglish
Pages (from-to)3257-3267
Number of pages11
JournalJournal of Chemical Theory and Computation
Volume18
Issue number5
DOIs
StatePublished - May 10 2022
Externally publishedYes

Funding

This work was supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO), and specifically the HydroGEN Advanced Water Splitting Materials Consortium, established as part of the Energy Materials Network under this same office (award DE-EE0008088). C.B.M., Z.J.L.B., and R.J.M. also acknowledge the support from the National Science Foundation (awards NSF CHEM-1800592 and CBET-2016225). R.J.M. acknowledges the support from a University of Colorado Boulder’s Materials for Energy Conversion and Sustainability Graduate Assistance in Areas of National Need (GAANN) fellowship, Department of Education (award no. P200A180012). The views expressed in this article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

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