Work

Machine Learning a Simple Interpretable Short-Range Potential for Silica

Year: 2024

Type: article

Source: Journal of Chemical Theory and Computation

DOI: 10.1021/acs.jctc.4c00639

Authors: Aditya Koneru, Henry Chan, Sukriti Manna, Suvo Banik, Valeria Molinero, Subramanian K. R. S. Sankaranarayanan

Institutions: Argonne National Laboratory, University of Illinois Chicago, Center for Nanoscale Materials, University of Utah

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: closed

Funder: Basic Energy Sciences

Awards: G21193025, G4067602926, G426311843

OpenAlex ID: W4402582290

FWCI: 0.568

Cites: 45

Cited by: 6

Related to: 10