Data underlying the chapter: Performance of Meta's Universal Model for Atoms Across the Conformational and Configurational Space of Diverse Transition-Metal Catalysts

DOI:10.4121/14bcdfc0-dd25-4945-9cb9-5d862b47a784.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/14bcdfc0-dd25-4945-9cb9-5d862b47a784

Datacite citation style

Kalikadien, Adarsh V.; Pidko, Evgeny (2025): Data underlying the chapter: Performance of Meta's Universal Model for Atoms Across the Conformational and Configurational Space of Diverse Transition-Metal Catalysts. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/14bcdfc0-dd25-4945-9cb9-5d862b47a784.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

We used Meta's Machine Learning Interatomic Potential (MLIP) UMA to evaluate how well it reproduces the energy rankings as calculated by DFT. The code to redo the calculations using UMA and to redo statistical analysis are present next to all used molecular structures.

History

  • 2025-09-16 first online, published, posted

Publisher

4TU.ResearchData

Format

Tabular data: .csv or .xlsx files, chemical structures: .xyz files, code: .py files

Organizations

TU Delft, Faculty of Applied Sciences, Department of Chemical Engineering

DATA

Files (4)