Calibrating DFT Formation Enthalpy Calculations by Multifidelity Machine Learning

[Image: see text] The application of machine learning to predict materials properties measured by experiments are valuable yet difficult due to the limited amount of experimental data. In this work, we use a multifidelity random forest model to learn the experimental formation enthalpy of materials...

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Detalles Bibliográficos
Autores principales: Gong, Sheng, Wang, Shuo, Xie, Tian, Chae, Woo Hyun, Liu, Runze, Shao-Horn, Yang, Grossman, Jeffrey C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516701/
https://www.ncbi.nlm.nih.gov/pubmed/36186569
http://dx.doi.org/10.1021/jacsau.2c00235

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516701/
https://www.ncbi.nlm.nih.gov/pubmed/36186569
http://dx.doi.org/10.1021/jacsau.2c00235

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