Work

UniFFBench: evaluating universal machine learning force fields against experimental measurements

Year: 2026

Type: article

Source: Nature Computational Science

DOI: 10.1038/s43588-026-01019-4

Authors: Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales, Kin Long Kelvin Lee, Nitya Nand Gosvami, Sayan Ranu, Santiago Miret, N. M. Anoop Krishnan

Institutions: Indian Institute of Technology Delhi, Intel (United States), Nvidia (United States)

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: Arthritis National Research Foundation, Alexander von Humboldt-Stiftung, National Research Foundation, Ministry of Education, India, Indian Institute of Technology Delhi

OpenAlex ID: W4415191223

FWCI: 17.85

Cites: 43

Cited by: 17

Related to: 10