Gradient Boosted Machine Learning Model to Predict H(2), CH(4), and CO(2) Uptake in Metal–Organic Frameworks Using Experimental Data

[Image: see text] Predictive screening of metal–organic framework (MOF) materials for their gas uptake properties has been previously limited by using data from a range of simulated sources, meaning the final predictions are dependent on the performance of these original models. In this work, experi...

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Detalles Bibliográficos
Autores principales: Bailey, Tom, Jackson, Adam, Berbece, Razvan-Antonio, Wu, Kejun, Hondow, Nicole, Martin, Elaine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10428209/
https://www.ncbi.nlm.nih.gov/pubmed/37463276
http://dx.doi.org/10.1021/acs.jcim.3c00135

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10428209/
https://www.ncbi.nlm.nih.gov/pubmed/37463276
http://dx.doi.org/10.1021/acs.jcim.3c00135

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