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A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo- and Copolymers

The purpose of this study was to develop a data-driven machine learning model to predict the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced polyesters featuring excellent performance, to guide future design and synthesis experiments. A deep neural network (DNN) machine...

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Detalles Bibliográficos
Autores principales: Jiang, Zhuoying, Hu, Jiajie, Marrone, Babetta L., Pilania, Ghanshyam, Yu, Xiong (Bill)
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765086/
https://www.ncbi.nlm.nih.gov/pubmed/33327598
http://dx.doi.org/10.3390/ma13245701