Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language

Advances in machine learning (ML) and automated experimentation are poised to vastly accelerate research in polymer science. Data representation is a critical aspect for enabling ML integration in research workflows, yet many data models impose significant rigidity making it difficult to accommodate...

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Detalles Bibliográficos
Autores principales: Park, Nathaniel H., Manica, Matteo, Born, Jannis, Hedrick, James L., Erdmann, Tim, Zubarev, Dmitry Yu., Adell-Mill, Nil, Arrechea, Pedro L.
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/PMC10284867/
https://www.ncbi.nlm.nih.gov/pubmed/37344485
http://dx.doi.org/10.1038/s41467-023-39396-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284867/
https://www.ncbi.nlm.nih.gov/pubmed/37344485
http://dx.doi.org/10.1038/s41467-023-39396-3

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