Investigation of Peierls stress of screw dislocation in BCC iron using machine learning potential

Abstract

It is very important to determine the mobility of screw dislocation in body-centered cubic (BCC) iron. The size of dislocation core of screw dislocation is around 1 nm. Thus, atomic modeling is required to investigate the energetics of screw dislocation. Recently, using reference data based on density functional theory (DFT) calculations, we construct an artificial neural network (ANN) atomic potential to investigate the dislocation dynamics in BCC iron. The energetics of screw dislocation predicted by the constructed ANN potential are in good agreement with the reference DFT calculations. Using constructed ANN potential, in this study we investigate Peierls stress of the screw dislocation.