Neural network potential for Zr-Rh system by machine learning

Atomic structure of intermetallic compound Nb5Si3by new cluster transformation analysis method

The structure of Nb₅Si₃at the atomic level is fundamental for identifying its complicated structure in atomic simulations and for further understanding the phase selection behaviors during the solidification of Nb-Si alloys. In this study, the structure of Nb₅Si₃was investigated using deep-learning molecular dynamic simulations. The idealβNb₅Si₃is characterized by Nb-centered Voronoi polyhedrons (VPs) <0,0,12,3>, <0,0,12,2>, and Si-centered VPs <0,2,8,2>, <0,2,8,0>. Most initial VPs are distorted at high temperatures due to intense thermal perturbation. A new cluster transformation analysis (CTA) method was proposed to evaluate the stability of ideal VPs against perturbation and predict the possible transformations of the initial VPs in atomic simulations. Most transformations of the initial VPs inβNb₅Si₃originate from distortions at the edges of the Nb-centered VPs and the faces/vertices of the Si-centered VPs. The distorted VPs inβNb₅Si₃at high temperatures are dominated by <0,1,10,4>, <0,1,10,5>, <0,2,8,1> and <1,2,5,3> VPs, which are predicted as the primary transformations by the CTA.