Molecular insight into the GaP(110)–water interface using machine learning accelerated molecular dynamics

Subjects

Subjects :

Fuel Technology
Electrochemistry
Energy Engineering and Power Technology
Energy (miscellaneous)

Details

ISSN :

20954956

Volume :

82

Database :

OpenAIRE

Journal :

Journal of Energy Chemistry

Accession number :

edsair.doi...........e9f9b2c89e585e5755e687b283aa0956