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Explainable graph neural networks for organic cages

The development of accurate and explicable machine learning models to predict the properties of topologically complex systems is a challenge in materials science. Porous organic cages, a class of polycyclic molecular materials, have potential application in molecular separations, catalysis and encap...

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Detalles Bibliográficos
Autores principales: Yuan, Qi, Szczypiński, Filip T., Jelfs, Kim E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: RSC 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996732/
https://www.ncbi.nlm.nih.gov/pubmed/35515082
http://dx.doi.org/10.1039/d1dd00039j