Dislocation plasticity in c$c$‐axis nanopillar compression of wurtzite ceramics: A study using neural network potentials

Abstract Ceramics typically exhibit brittle characteristics at room temperature. However, under high compressive stress conditions, such as during nanoindentation or compression tests on nanopillars, these materials can reach the necessary shear stress for dislocation nucleation and glide before fracture occurs. This allows for the observation of plastic deformation through dislocations even at room temperature. Yet, detailed insights into their atomic‐scale dislocation plasticity remain scarce. This study employs atomistic simulations to explore the dislocation plasticity in ‐oriented nanopillars of wurtzite ceramics (i.e., GaN and ZnO) under uniaxial [0001] compression, utilizing a specially developed first‐principles neural network interatomic potential. We observed activation of and dislocations, corroborating experimental findings from in‐situ compression tests. Moreover, a wurtzite‐to‐hexagonal phase transformation begins at facet edges and extends inward, forming wedge‐shaped regions. As compression progresses, dislocations nucleate at the wurtzite‐hexagonal phase boundary and spread throughout the nanopillar, contributing to a rougher surface texture. These quantitative results offer new insights into the plastic deformation behaviors of nanopillars under compressive loading, highlighting the potential of dislocation engineering in these ceramics.