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Performance-Based Selection of Machine Learning Interatomic Potentials for Studying Solid-State Electrolytes

Year: 2026

Type: article

Source: Chemistry of Materials

DOI: 10.1021/acs.chemmater.5c02352

Authors: Donghee Chang, Amir Taqieddin, Forrest Laskowski

Institution: Solid Power (United States)

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W7148447618

FWCI:

Cites: 58

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