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MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules

Lookup NU author(s): Dr Ioan-Bogdan MagdăuORCiD, Dr Daniel ColeORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

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Author(s): Kovács DP, Moore JH, Browning NJ, Batatia I, Horton JT, Pu Y, Kapil V, Witt WC, Magdău IB, Cole DJ, Csányi G

Publication type: Article

Publication status: Published

Journal: Journal of the American Chemical Society

Year: 2025

Pages: epub ahead of print

Online publication date: 19/05/2025

Acceptance date: 02/05/2025

Date deposited: 19/05/2025

ISSN (print): 0002-7863

ISSN (electronic): 1520-5126

Publisher: American Chemical Society

URL: https://doi.org/10.1021/jacs.4c07099

DOI: 10.1021/jacs.4c07099

Data Access Statement: The data used to train the models are publicly available at: 10. 17863/CAM.107498. The torsion drive data set is also available at: https://zenodo.org/records/11385284. The MACE-OFF series of models is available at: https://github. com/ACEsuit/mace-off/tree/main.

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