Direct Prediction of Phonon Density of States With Euclidean Neural Networks

Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete properties, challenges remain for continuous property prediction. The challenge is aggravated in crystalline solids due to cr...

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Detalles Bibliográficos
Autores principales: Chen, Zhantao, Andrejevic, Nina, Smidt, Tess, Ding, Zhiwei, Xu, Qian, Chi, Yen‐Ting, Nguyen, Quynh T., Alatas, Ahmet, Kong, Jing, Li, Mingda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224435/
https://www.ncbi.nlm.nih.gov/pubmed/34165895
http://dx.doi.org/10.1002/advs.202004214

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224435/
https://www.ncbi.nlm.nih.gov/pubmed/34165895
http://dx.doi.org/10.1002/advs.202004214

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