Evidence map›Paper›PMID 40804537›Full record

ArticleNature chemistry2025

An accurate and efficient framework for modelling the surface chemistry of ionic materials.

Benjamin X Shi, Andrew S Rosen, Tobias Schäfer, Andreas Grüneis, Venkat Kapil, Andrea Zen, Angelos Michaelides

Abstract read
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Article in Nature chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Benjamin X ShiYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0003-3272-0996
Andrew S RosenDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA.ORCID http://orcid.org/0000-0002-0141-7006
Tobias SchäferInstitute for Theoretical Physics, TU Wien, Vienna, Austria.ORCID http://orcid.org/0000-0003-0716-6516
Andreas GrüneisInstitute for Theoretical Physics, TU Wien, Vienna, Austria.ORCID http://orcid.org/0000-0002-4984-7785
Venkat KapilYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0003-0324-2198
Andrea ZenDipartimento di Fisica Ettore Pancini, Università di Napoli Federico II, Napoli, Italy.ORCID http://orcid.org/0000-0002-7648-4078
Angelos MichaelidesYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom. am452@cam.ac.uk.ORCID http://orcid.org/0000-0002-9169-169X

Funding

Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung) 10.55776/ESP335EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 101071937
6 · The paper itself

Abstract

Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces that are crucial to advancing applications in heterogeneous catalysis, energy storage and greenhouse gas sequestration. Unfortunately, achieving the accuracy needed for reliable predictions has proven challenging. Density functional theory, widely used for its efficiency, can be inconsistent, necessitating accurate methods from correlated wavefunction theory. But high computational demands and substantial user intervention have traditionally made correlated wavefunction theory impractical to carry out for surfaces. Here we present an automated framework that leverages multilevel embedding approaches to apply correlated wavefunction theory to the surfaces of ionic materials with computational costs approaching those of density functional theory. With this framework, we reproduce experimental adsorption enthalpies for a diverse set of 19 adsorbate-surface systems. We further resolve debates on the adsorption configuration of several systems, while offering benchmarks to assess density functional theory. This framework is open source, facilitating the routine application of correlated wavefunction theory to complex problems involving the surfaces of ionic materials.

Identifiers

PMID40804537
PMCPMC12580338

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.