Statistical analysis of slip transfer in Al alloy based on in-situ tensile test and high-throughput computing method

Abstract

Slip transfer mechanism is studied based on in-situ tensile tests performed on an Al-Mg alloy and high-throughput computing. A statistical analysis of slip transfer is performed for over 1180 grain boundaries and 155,250 slip pairs while considering the local lattice rotation, grain boundaries, and slip system geometries. Two new slip transfer parameters, N and B, representing the alignment of the slip planes and the activation of slip systems in adjacent grains, are proposed. A decision tree model is built to evaluate the prediction accuracy of the slip transfer parameters. The optimized results of the decision tree classifiers show that the two new parameters are more effective than the Luster–Morris parameter, m′. The improvement in the classification accuracy is attributable to the information regarding the slip plane geometry and orientation evolution contained in N and B. The new slip transfer parameters improve our understanding of the slip transfer mechanism and can be integrated into plasticity models to predict the deformation and fracture behaviors of polycrystalline materials.