Challenges for machine learning force fields in reproducing potential energy surfaces of flexible molecules

Reference : Challenges for machine learning force fields in reproducing potential energy surfaces...


	Document type :	Scientific journals : Article
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Physics
	To cite this reference:	http://hdl.handle.net/10993/49415

Title :	Challenges for machine learning force fields in reproducing potential energy surfaces of flexible molecules
Language :	English
Author, co-author :	Vassilev Galindo, Valentin [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
	Cordeiro Fonseca, Gregory [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
	Poltavskyi, Igor [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
	Tkatchenko, Alexandre [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
Publication date :	3-Mar-2021
Journal title :	Journal of Chemical Physics
Peer reviewed :	Yes
Permalink :	http://hdl.handle.net/10993/49415
DOI :	10.1063/5.0038516

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