An accurate and efficient framework for modelling the surface chemistry of ionic materials
Benjamin X. Shi, Andrew S. Rosen, Tobias Sch\"afer, Andreas Gr\"uneis, Venkat Kapil, Andrea Zen, Angelos Michaelides

TL;DR
This paper introduces an automated, open-source multilevel embedding framework that enables accurate correlated wave-function theory calculations on ionic material surfaces at DFT-like computational costs, improving predictions of surface chemistry.
Contribution
The work presents a novel, efficient framework that makes high-accuracy cWFT methods practical for surface chemistry modeling of ionic materials, addressing computational and usability challenges.
Findings
Reproduced experimental adsorption enthalpies for 19 systems
Resolved adsorption configuration debates for several systems
Provided benchmarks for assessing DFT accuracy
Abstract
Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces. This understanding is crucial for the rational design of new solid catalysts as well as materials to store energy and mitigate greenhouse gases. However, achieving the accuracy needed for reliable predictions has proven challenging. Density functional theory (DFT), the workhorse quantum-mechanical method, can often lead to inconsistent predictions, necessitating accurate methods from correlated wave-function theory (cWFT). However, the high computational demands and significant user intervention associated with cWFT have traditionally made it impractical to carry out for surfaces. In this work, we address this challenge, presenting an automated framework which leverages multilevel embedding approaches, to apply accurate cWFT methods to the surfaces of ionic materials with computational…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
