Machine learning-assisted crystal engineering of a zeolite

It is shown that Machine Learning (ML) algorithms can usefully capture the effect of crystallization composition and conditions (inputs) on key microstructural characteristics (outputs) of faujasite type zeolites (structure types FAU, EMT, and their intergrowths), which are widely used zeolite catal...

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Detalles Bibliográficos
Autores principales: Li, Xinyu, Han, He, Evangelou, Nikolaos, Wichrowski, Noah J., Lu, Peng, Xu, Wenqian, Hwang, Son-Jong, Zhao, Wenyang, Song, Chunshan, Guo, Xinwen, Bhan, Aditya, Kevrekidis, Ioannis G., Tsapatsis, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232492/
https://www.ncbi.nlm.nih.gov/pubmed/37258522
http://dx.doi.org/10.1038/s41467-023-38738-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232492/
https://www.ncbi.nlm.nih.gov/pubmed/37258522
http://dx.doi.org/10.1038/s41467-023-38738-5

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