Deep Learning-Based Predictions of Material Properties Using Chemical Compositions and Diffraction Patterns as Experimentally Accessible Inputs

Title
Deep Learning-Based Predictions of Material Properties Using Chemical Compositions and Diffraction Patterns as Experimentally Accessible Inputs
Authors
한상수김동훈김정래Leslie
Keywords
Deep learning; Material properties; Chemical composition; Diffraction pattern; Element vector
Issue Date
2021-09
Publisher
Journal of Physical Chemistry Letters
Citation
VOL 12-8383
URI
http://pubs.kist.re.kr/handle/201004/73747
ISSN
1948-7185
Appears in Collections:
KIST Publication > Article
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