QMLMaterial─A Quantum Machine Learning Software for Material Design and Discovery.
Journal
Journal of chemical theory and computation
ISSN: 1549-9626
Titre abrégé: J Chem Theory Comput
Pays: United States
ID NLM: 101232704
Informations de publication
Date de publication:
12 Sep 2023
12 Sep 2023
Historique:
medline:
15
8
2023
pubmed:
15
8
2023
entrez:
15
8
2023
Statut:
ppublish
Résumé
Structural elucidation of chemical compounds is challenging experimentally, and theoretical chemistry methods have added important insight into molecules, nanoparticles, alloys, and materials geometries and properties. However, finding the optimum structures is a bottleneck due to the huge search space, and global search algorithms have been used successfully for this purpose. In this work, we present the quantum machine learning software/agent for materials design and discovery (QMLMaterial), intended for automatic structural determination
Identifiants
pubmed: 37581570
doi: 10.1021/acs.jctc.3c00566
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM