Morelock RJ, Bare ZJL, Musgrave CB. Bond-Valence Parameterization for the Accurate Description of DFT Energetics.
J Chem Theory Comput 2022;
18:3257-3267. [PMID:
35442669 DOI:
10.1021/acs.jctc.1c01113]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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.
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