English

Data-driven and constrained optimization of semi-local exchange and non-local correlation functionals for materials and surface chemistry

Computational Physics 2022-06-01 v2 Materials Science

Abstract

Reliable predictions of surface chemical reaction energetics require an accurate description of both chemisorption and physisorption. Here, we present an empirical approach to simultaneously optimize semi-local exchange and non-local correlation of a density functional approximation to improve these energetics. A combination of reference data for solid bulk, surface, and gas-phase chemistry and physical exchange-correlation model constraints leads to the VCML-rVV10 exchange-correlation functional. Owing to the variety of training data, the applicability of VCML-rVV10 extends beyond surface chemistry simulations. It provides optimized gas phase reaction energetics and an accurate description of bulk lattice constants and elastic properties.

Keywords

Cite

@article{arxiv.2201.11106,
  title  = {Data-driven and constrained optimization of semi-local exchange and non-local correlation functionals for materials and surface chemistry},
  author = {Kai Trepte and Johannes Voss},
  journal= {arXiv preprint arXiv:2201.11106},
  year   = {2022}
}

Comments

12 pages, 7 figures

R2 v1 2026-06-24T09:04:12.162Z