MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning

Despite rapid progress in the field of metal–organic frameworks (MOFs), the potential of using machine learning (ML) methods to predict MOF synthesis parameters is still untapped. Here, we show how ML can be used for rationalization and acceleration of the MOF discovery process by directly predictin...

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Detalles Bibliográficos
Autores principales: Luo, Yi, Bag, Saientan, Zaremba, Orysia, Cierpka, Adrian, Andreo, Jacopo, Wuttke, Stefan, Friederich, Pascal, Tsotsalas, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310626/
https://www.ncbi.nlm.nih.gov/pubmed/35104033
http://dx.doi.org/10.1002/anie.202200242

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310626/
https://www.ncbi.nlm.nih.gov/pubmed/35104033
http://dx.doi.org/10.1002/anie.202200242

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