Recursive neural networks prediction of glass transition temperature from monomer structure: An application to acrylic and methacrylic polymers
DOI10.1007/S10910-009-9547-ZzbMath1194.92083OpenAlexW2092991999MaRDI QIDQ1037472
Antonina Starita, Alessio Micheli, Roberto Solaro, Maria Rosaria Tiné, Celia Duce
Publication date: 16 November 2009
Published in: Journal of Mathematical Chemistry (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10910-009-9547-z
Chemistry (92E99) Neural networks for/in biological studies, artificial life and related topics (92B20) Statistical mechanics of polymers (82D60) Molecular structure (graph-theoretic methods, methods of differential topology, etc.) (92E10)
Cites Work
This page was built for publication: Recursive neural networks prediction of glass transition temperature from monomer structure: An application to acrylic and methacrylic polymers
