Practical and accurate density functionals for computational heterogeneous catalysis

Abstract

Density functional theory underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in rational catalyst design. These applications require reliable density functionals, achieving errors below 13 kJ mol−1, sometimes called transition-metal chemical accuracy, which remains challenging. We introduce a non-self-consistent approach to lower the cost of higher-rung functionals by orders of magnitude, enabling application to larger and more complex metal surfaces than their self-consistent counterparts. Building on this, we develop a new hybrid and double-hybrid functional that achieves better accuracy than standard semilocal functionals, with the double-hybrid functional reaching transition-metal chemical accuracy on average across 39 experimental adsorption reactions. In addition, they both demonstrate balanced performance for 17 barrier heights and correct qualitative failures of standard functionals, including CO adsorption on Pt(111) and graphene on Ni(111). These functionals can be readily implemented in existing density functional theory codes, and we provide code for their integration into open-source high-throughput workflows to facilitate broad adoption. More broadly, this framework provides a systematic route towards improved functionals for heterogeneous catalysis and complex materials.