Machine learning assisted prediction of mechanical properties of graphene/aluminium nanocomposite based on molecular dynamics simulation

•Molecular dynamics simulations are conducted to investigate the Young’s modulus and ultimate tensile strength of graphene reinforced aluminium nanocomposites.•Machine learning (ML) techniques are used to predict the mechanical properties based on MD datasets.•Halpin-Tsai model is modified in explicit form based on MD and ML results.•Modified Halpin-Tsai model has significantly improved accuracy for the prediction of Young’s modulus.