Data-Mining of In Situ TEM Experiments on CoCrFeMnNi Alloys—4D Reconstruction of Dislocation Dynamics and Sampling of the Energy Landscape

During <i>In Situ</i> transmission electron microscopy (TEM) straining experiments of high entropy alloys (HEA), pinning points frequently hinder the motion of dislocations. They lead to abrupt changes in the curvature of moving dislocations in the middle of in situ samples. Because their nature remains a key question in HEA, we propose a data-mining strategy for extracting quantitative information from the real-time dynamics of dislocation lines to retrieve the local strength of these obstacles.<br/><br/>An experiment on equimolar CoCrFeMnNi HEA (Cantor alloy) demonstrates the capabilities of our data-mining approach. We show how the 3D dislocation structure can be reconstructed and the force variation along the lines retrieved automatically. A novel coarse-graining method is employed to statistically extract quantitative information on the nature, dispersion and strength of pinning points, along with their evolution upon deformation. This subsequently provides new ideas for understanding deformation mechanisms in high-entropy alloys.