MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures...

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Detalles Bibliográficos
Autores principales: Nandy, Aditya, Terrones, Gianmarco, Arunachalam, Naveen, Duan, Chenru, Kastner, David W., Kulik, Heather J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917177/
https://www.ncbi.nlm.nih.gov/pubmed/35277533
http://dx.doi.org/10.1038/s41597-022-01181-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917177/
https://www.ncbi.nlm.nih.gov/pubmed/35277533
http://dx.doi.org/10.1038/s41597-022-01181-0

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