Open AccessPhysics-informed machine learning for inorganic scintillator discovery
Author(s) -
Ghanshyam Pilania,
Kenneth J. McClellan,
Christopher R. Stanek,
Blas P. Uberuaga
Publication year - 2018
Publication title -
journal of chemical physics online/the journal of chemical physics/journal of chemical physics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.071
H-Index - 357
eISSN - 1089-7690
pISSN - 0021-9606
DOI - 10.1063/1.5025819
Subject(s) - scintillator , lanthanide , excited state , valence (chemistry) , activator (genetics) , band gap , physics , scintillation , materials science , nanotechnology , ion , atomic physics , chemistry , optoelectronics , detector , quantum mechanics , optics , biochemistry , gene