Understanding anharmonic effects on hydrogen desorption characteristics of Mg n H 2 n nanoclusters by ab initio trained deep neural network
Year: 2022
Type: article
Source: Nanoscale
DOI: 10.1039/d1nr08359g
Institutions: University of Trento, Fondazione Bruno Kessler, European Centre for Theoretical Studies in Nuclear Physics and Related Areas, Università Campus Bio-Medico, Sapienza University of Rome, Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics And Applications, Queen Mary University of London
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: closed
Award: G6270501235
OpenAlex ID: W3215977537