Applying machine learning techniques to predict the properties of energetic materials

We present a proof of concept that machine learning techniques can be used to predict the properties of CNOHF energetic molecules from their molecular structures. We focus on a small but diverse dataset consisting of 109 molecular structures spread across ten compound classes. Up until now, candidat...

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Detalles Bibliográficos
Autores principales: Elton, Daniel C., Boukouvalas, Zois, Butrico, Mark S., Fuge, Mark D., Chung, Peter W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998124/
https://www.ncbi.nlm.nih.gov/pubmed/29899464
http://dx.doi.org/10.1038/s41598-018-27344-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998124/
https://www.ncbi.nlm.nih.gov/pubmed/29899464
http://dx.doi.org/10.1038/s41598-018-27344-x

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