Prediction and Interpretation of Polymer Properties Using the Graph Convolutional Network

[Image: see text] We present machine learning models for the prediction of thermal and mechanical properties of polymers based on the graph convolutional network (GCN). GCN-based models provide reliable prediction performances for the glass transition temperature (T(g)), melting temperature (T(m)),...

Descripción completa

Detalles Bibliográficos
Autores principales: Park, Jaehong, Shim, Youngseon, Lee, Franklin, Rammohan, Aravind, Goyal, Sushmit, Shim, Munbo, Jeong, Changwook, Kim, Dae Sin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954297/
https://www.ncbi.nlm.nih.gov/pubmed/36855563
http://dx.doi.org/10.1021/acspolymersau.1c00050

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954297/
https://www.ncbi.nlm.nih.gov/pubmed/36855563
http://dx.doi.org/10.1021/acspolymersau.1c00050

Ejemplares similares