Insightful classification of crystal structures using deep learning
Classifying crystal structures using their space group is important to understand material properties, but the process currently requires user input. Here, the authors use machine learning to automatically classify more than 100,000 simulated perfect and defective crystal structures.
Guardado en:
Autores principales: | Angelo Ziletti, Devinder Kumar, Matthias Scheffler, Luca M. Ghiringhelli |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
|
Materias: | |
Acceso en línea: | https://doaj.org/article/fdc2ae7369674905b86a4eaab4c29eff |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Identifying domains of applicability of machine learning models for materials science
por: Christopher Sutton, et al.
Publicado: (2020) -
Weakly-supervised learning for lung carcinoma classification using deep learning
por: Fahdi Kanavati, et al.
Publicado: (2020) -
Automatic classification of canine thoracic radiographs using deep learning
por: Tommaso Banzato, et al.
Publicado: (2021) -
Classification of caries in third molars on panoramic radiographs using deep learning
por: Shankeeth Vinayahalingam, et al.
Publicado: (2021) -
Deep learning classification of lung cancer histology using CT images
por: Tafadzwa L. Chaunzwa, et al.
Publicado: (2021)