Direct prediction of inelastic neutron scattering spectra from the crystal structure

Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty...

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書誌詳細

主要な著者:	Yongqiang Cheng, Geoffrey Wu, Daniel M Pajerowski, Matthew B Stone, Andrei T Savici, Mingda Li, Anibal J Ramirez-Cuesta
フォーマット:	Artigo
言語:	Inglês
出版事項:	IOP Publishing 2023-01-01
シリーズ:	Machine Learning: Science and Technology
主題:	inelastic neutron scattering autoencoder symmetry-aware neural network structure-property relationship
オンライン･アクセス:	https://doi.org/10.1088/2632-2153/acb315
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