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QCell: comprehensive quantum-mechanical dataset spanning diverse biomolecular fragments

Recent advances in machine learning force fields (MLFFs) are revolutionizing molecular simulations by bridging the gap between quantum-mechanical (QM) accuracy and the computational efficiency of mechanistic potentials. However, the development of reliable MLFFs for biomolecular systems remains cons...

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Principais autores: Adil Kabylda, Sergio Suárez-Dou, Nils Davoine, Florian N Brünig, Alexandre Tkatchenko
Format: Artigo
Sprog:Inglês
Udgivet: IOP Publishing 2026-01-01
Serier:AI for Science
Fag:
quantum-mechanical dataset
density functional theory
machine learning force fields
biomolecular simulations
Online adgang:https://doi.org/10.1088/3050-287X/ae5267
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