Graph neural networks for materials science and chemistry

Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growin...

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Detalles Bibliográficos
Autores principales: Reiser, Patrick, Neubert, Marlen, Eberhard, André, Torresi, Luca, Zhou, Chen, Shao, Chen, Metni, Houssam, van Hoesel, Clint, Schopmans, Henrik, Sommer, Timo, Friederich, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702700/
https://www.ncbi.nlm.nih.gov/pubmed/36468086
http://dx.doi.org/10.1038/s43246-022-00315-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702700/
https://www.ncbi.nlm.nih.gov/pubmed/36468086
http://dx.doi.org/10.1038/s43246-022-00315-6

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