Prediction and Classification of Formation Energies of Binary Compounds by Machine Learning: An Approach without Crystal Structure Information

[Image: see text] It is well believed that machine learning models could help to predict the formation energies of materials if all elemental and crystal structural details are known. In this paper, it is shown that even without detailed crystal structure information, the formation energies of binar...

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Detalles Bibliográficos
Autores principales: Mao, Yuanqing, Yang, Hongliang, Sheng, Ye, Wang, Jiping, Ouyang, Runhai, Ye, Caichao, Yang, Jiong, Zhang, Wenqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190927/
https://www.ncbi.nlm.nih.gov/pubmed/34124476
http://dx.doi.org/10.1021/acsomega.1c01517

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190927/
https://www.ncbi.nlm.nih.gov/pubmed/34124476
http://dx.doi.org/10.1021/acsomega.1c01517

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