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This study aims to experiment with the mechanical properties of polypropylene (PP)/thermoplastic elastomer/nano-silica/compatibilizer nanocomposite using the melt mixing method. The addition of polyolefin elastomers has proved to be an approachable solution for low impact strength of PP, while it would also reduce the Young's modulus and tensile strength. That is why reinforcement would be applied to this combination to enhance the elastic modulus. The mechanical properties of the prepared composites were devised to train an artificial neural network to predict these properties of the system in 6256 unknown points. Therefore, the sensitivity analysis was performed and the share of each input parameter on the respective output values was calculated. Additionally, a novel parameter called nanocomposite evaluation criterion (NEC) is introduced to analyze the suitability of the nanocomposites considering the mechanical properties. Accordingly, the formulation with optimal mechanical properties of toughness, elongation at break, tensile strength, Young's modulus, and impact strength was obtained.
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Jean-François Molinari, Son-Jonathan Pham-Ba