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A machine learning tool for future prediction of heat release capacity of in-situ flame retardant hybrid Mg(OH)2-Epoxy nanocomposites

In this work, the fire behavior of a sol-gel in-situ hybrid Mg(OH)2-epoxy nanocomposite was investigated and an artificial neural network-based system built on a fully connected feed-forward artificial neural network was developed to predict its heat release capacity. The nanocomposite containing on...

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Autori principali: Aurelio Bifulco, Angelo Casciello, Claudio Imparato, Stanislao Forte, Sabyasachi Gaan, Antonio Aronne, Giulio Malucelli
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2023-10-01
Serie:Polymer Testing
Soggetti:
Magnesium hydroxide
Sol-gel
Epoxy
Prediction of fire parameters
Artificial neural networks
Machine learning
Accesso online:http://www.sciencedirect.com/science/article/pii/S0142941823002556
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