Unveiling the impact of ligand configurations and structural fluxionality on virtual screening of transition-metal complexes

Virtual screenings that ignore configurational diversity can misrepresent catalyst space. Using DFT, we show many transition metal complexes are fluxional, with multiple stable configurations and transferable global, but not local, descriptors.

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Publication Details

Journal
Digital Discovery
Published
2025-01-01
DOI
https://doi.org/10.1039/d5dd00093a
Citations
2
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
1.04

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article

Unveiling the impact of ligand configurations and structural fluxionality on virtual screening of transition-metal complexes

Cecile Valsecchi, Adarsh V. Kalikadien, Evgeny A. Pidko, Laurent Lefort et al.
2 citations
Digital Discovery
Machine Learning in Materials Science
1.04
article

Unveiling the impact of ligand configurations and structural fluxionality on virtual screening of transition-metal complexes

Cecile Valsecchi, Adarsh V. Kalikadien, Evgeny A. Pidko, Laurent Lefort, Niels J. van der Lem
article en
2 citations

Abstract

Virtual screenings that ignore configurational diversity can misrepresent catalyst space. Using DFT, we show many transition metal complexes are fluxional, with multiple stable configurations and transferable global, but not local, descriptors.

Digital DiscoveryVol. 4(8)
Janssen (Belgium) (BE), Janssen (Italy) (IT), Delft University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 24%
Machine Learning in Materials Science
1.04
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