Cargando…
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors
Establishing a data-driven pipeline for the discovery of novel materials requires the engineering of material features that can be feasibly calculated and can be applied to predict a material’s target properties. Here we propose a new class of descriptors for describing crystal structures, which we...
Autores principales: | Tawfik, Sherif Abdulkader, Russo, Salvy P. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644534/ https://www.ncbi.nlm.nih.gov/pubmed/36348412 http://dx.doi.org/10.1186/s13321-022-00658-9 |
Ejemplares similares
-
Robust control of linear descriptor systems
por: Feng, Yu, et al.
Publicado: (2017) -
Python descriptors: understanding and using the descriptor protocol
por: Zimmerman, Jacob
Publicado: (2018) -
Predicting the Skin Sensitization Potential of Small Molecules with Machine Learning Models Trained on Biologically Meaningful Descriptors
por: Wilm, Anke, et al.
Publicado: (2021) -
Python descriptors
por: Zimmerman, Jacob
Publicado: (2016) -
Module descriptor
por: Nicolaysen, O P
Publicado: (1973)