Machine learned interatomic potentials for gas-metal interactions
M A Cusentino,
M A Wood,
A P Thompson
Abstract:Developing interatomic potentials for gas-metal systems is difficult due to the wide range of chemical compositions that the potential must be able to reproduce. There is a need for these types of potentials for studying plasma-material interactions in fusion reactors where gaseous plasma species will implant in metallic reactor components. The challenges presented by these material systems make them suitable candidates for treatment by a machine learning approach, such as that of the spectral neighbor analysi… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.