2024
DOI: 10.1002/pc.28801
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XGBoost machine learning assisted prediction of the mechanical and fracture properties of unvulcanized and dynamically vulcanized PP/EPDM reinforced with clay and halloysite nanoparticles

Pouya Rajaee,
Amir Hossein Rabiee,
Faramarz Ashenai Ghasemi
et al.

Abstract: Polymer nanocomposites have found wide industrial applications, necessitating optimal mechanical and fracture properties evaluation, traditionally done through costly experimental methods. This study employs machine learning, particularly XGBoost, to predict properties like tensile and fracture properties swiftly, aiding material innovation across industries. The research investigates unvulcanized and vulcanized polypropylene (PP)/ethylene propylene diene monomer (EPDM) reinforced with clay and halloysite nano… Show more

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