Unusual magnetic interaction in CrTe: insights from machine-learning and empirical models

Abstract

Abstract Chromium telluride (CrTe) has received much attention due to its small magnetic anisotropy, which hosts the potential for complex magnetic structures. However, its magnetic properties have been relatively unexplored with numerical simulations, as the magnetic interactions inside are quite unusual. In this study, we employ both a machine-learning model and an empirical model to investigate the magnetic phase transitions of bulk and monolayer CrTe, revealing the existence of unusual magnetic interaction, which can be captured by the machine-learning model but not the simple empirical model. Furthermore, our results also demonstrate that magnetic moments further apart exhibit stronger interactions than those in closer proximity, deviating from typical behavior.