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

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

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<jats:title>Abstract</jats:title><jats:p>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 stabiliti...

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Bibliographic Details
Main Authors: Nandy, Aditya, Terrones, Gianmarco, Arunachalam, Naveen, Duan, Chenru, Kastner, David W, Kulik, Heather J
Other Authors: Massachusetts Institute of Technology. Department of Chemical Engineering
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2022
Online Access:https://hdl.handle.net/1721.1/141730.2

Internet

https://hdl.handle.net/1721.1/141730.2

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