The Good, the Bad, and the Ugly: Pseudopotential Inconsistency Errors in Molecular Applications of Density Functional Theory

Elliot Rossomme; Leonardo A Cunha; Wanlu Li; Kaixuan Chen; Alexandra R McIsaac; Teresa Head-Gordon; Martin Head-Gordon

doi:10.1021/acs.jctc.3c00089

The Good, the Bad, and the Ugly: Pseudopotential Inconsistency Errors in Molecular Applications of Density Functional Theory

J Chem Theory Comput. 2023 May 23;19(10):2827-2841. doi: 10.1021/acs.jctc.3c00089. Epub 2023 May 8.

Authors

Elliot Rossomme^{1

2

3}, Leonardo A Cunha^{1

3}, Wanlu Li^{1

2

3}, Kaixuan Chen^{1

2

3}, Alexandra R McIsaac^{1

2

3}, Teresa Head-Gordon^{1

2

3

4

5}, Martin Head-Gordon^{1

2

3}

Affiliations

¹ Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States.
² Department of Chemistry, University of California, Berkeley, California 94720, United States.
³ Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
⁴ Department of Bioengineering, University of California, Berkeley, California 94720, United States.
⁵ Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States.

PMID: 37156013
DOI: 10.1021/acs.jctc.3c00089

Abstract

The pseudopotential (PP) approximation is one of the most common techniques in computational chemistry. Despite its long history, the development of custom PPs has not tracked with the explosion of different density functional approximations (DFAs). As a result, the use of PPs with exchange/correlation models for which they were not developed is widespread, although this practice is known to be theoretically unsound. The extent of PP inconsistency errors (PPIEs) associated with this practice has not been systematically explored across the types of energy differences commonly evaluated in chemical applications. We evaluate PPIEs for a number of PPs and DFAs across 196 chemically relevant systems of both transition-metal and main-group elements, as represented by the W4-11, TMC34, and S22 data sets. Near the complete basis set limit, these PPs are found to cleanly approach all-electron (AE) results for noncovalent interactions but introduce root-mean-squared errors (RMSEs) upwards of 15 kcal mol^-1 into predictions of covalent bond energies for a number of popular DFAs. We achieve significant improvements through the use of empirical atom- and DFA-specific PP corrections, indicating considerable systematicity of the PPIEs. The results of this work have implications for chemical modeling in both molecular contexts and for DFA design, which we discuss.