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Funct. Mater. 2019; 26 (3): 615-620.

doi:https://doi.org/10.15407/fm26.03.615

The preparation process of nanocomposite materials was optimized based on neural network and genetic algorithm

Q.Wang

Shandong Business Institute, ShanDong, China

Abstract: 

This paper presents two methods for optimizing the preparation technology of nanometer LLDPE/ZnO composite materials to get the best physical and chemical properties. To optimize the process parameters of the nano-composite, the best sample preparation technology conditions were chosen. FESEM and SEM methods were applied for further studying the decentralized state and fracture morphology, and the mechanical properties of the nano-composites were tested. The results show that the optimization method based on the orthogonal experiment, neural network and genetic algorithms is better than that based on the orthogonal experiment alone. Nano-ZnO particles can exert the nano-effect in the matrix of linear low-density polyethylene (LLDPE), promote the brittle-to-ductile transition process of composite materials, and play a role in strengthening and toughening. The tensile strength and elongation at break were improved. Through further analysis, it is concluded that the tensile strength can be maximized when the filling amount of nanometer ZnO particles is 3 %. The elongation at break can be maximized when the filling amount of nanometer ZnO is 5 %.

Keywords: 
nanometer ZnO particles, linear low-density polyethylene, preparation technology, mechanical properties.
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