Review—Computational Studies of Graphene Reinforced Nanocomposites: Techniques, Parameters, and Future Perspectives

Abstract

In recent years, there has been notable exploration and investigation of graphene nanocomposites (GNCs) through experimental, numerical, and computational methods. GNCs have gained attention due to their remarkable mechanical and thermal properties, particularly when Gr has been utilized as the reinforcing material. Gr, a two-dimensional material, possesses exceptional properties, including greater elastic modulus, thermal conductivity, and electrical conductivity. As a result, GNCs have emerged as promising materials for various applications in aerospace and automobiles. Computational techniques, including finite element method (FEM), molecular dynamics, and Monte Carlo analysis have been utilized to analyse different aspects of GNC. Among these, FEM stands out for designing and evaluating the mechanical properties of GNC, enabling researchers to simulate and analyse the characteristics of GNC structures under diverse loading conditions, optimizing their design and predicting mechanical performance. This review emphasizes the significance of Gr in various matrices, discusses the present cutting-edge status of FEM methodologies for Gr reinforcement, and highlights its advantages and purposes. Furthermore, it explores the governing parameters affecting the mechanical properties of GNC and briefly presents the different mechanical properties of NC. We also outline future research directions and potential applications of GNC for advancing future generations of materials.