Open Access

ARTICLE

Effect of Process Parameters on the Agglomeration Behavior and Tensile Response of Graphene Reinforced Magnesium Matrix Composites Based on Molecular Dynamics Model

by Chentong Zhao¹, Jiming Zhou^1,2,*, Xujiang Chao^1,3, Su Wang¹, Lehua Qi^1,2

1 School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072, China
2 Shanxi Key Laboratory of Fiber Reinforced Light Composite Materials, Northwestern Polytechnical University, Xi’an, 710072, China
3 Future Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, China

* Corresponding Author: Jiming Zhou. Email:

(This article belongs to the Special Issue: Theoretical and Computational Modeling of Advanced Materials and Structures-II)

Computer Modeling in Engineering & Sciences 2024, 141(3), 2453-2469. https://doi.org/10.32604/cmes.2024.052723

Received 12 April 2024; Accepted 10 July 2024; Issue published 31 October 2024

Abstract

The mechanical properties of graphene reinforced composites are often hampered by challenges related to the dispersion and aggregation of graphene within the matrix. This paper explores the mechanism of cooling rate, process temperature, and process pressure’s influence on the agglomeration behavior of graphene and the tensile response of composites from a computer simulation technology, namely molecular dynamics. Our findings reveal that the cooling rate exerts minimal influence on the tensile response of composites. Conversely, processing temperature significantly affects the degree of graphene aggregation, with higher temperatures leading to the formation of larger-sized graphene clusters. In contrast, processing pressure exhibits negligible impact on the degree of graphene aggregation, and increasing pressure effectively mitigates the formation of large-sized graphene clusters. Moreover, we elucidate the intrinsic factors governing the mechanical response to variations in processing parameters. Notably, we observe that the stretching process facilitates the decomposition of large-sized graphene clusters into smaller ones. This research contributes to the advancement of lightweight metal matrix composites by offering insights into optimizing processing parameters. Additionally, it provides crucial theoretical underpinnings for developing high-performance graphene-reinforced composites.

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Keywords

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