The Transition Mechanism and Its Heterogeneity in Metal-Insulator Transition Compounds, and Machine-Learning Assisted Discovery of Novel Materials

I will focus on three key recent topics in the field of metal-insulator transition (MIT) compounds. First, I will show how we’ve solved the question of the transition from a high-temperature metallic to a low-temperature insulating state is driven by the electronic or the lattice degrees of freedom by disentangling their roles and showing that the lattice plays a key role in bulk and layered structures of rare earth nickelates (RNiO₃ with R a rare earth atom) and Ca₂RuO₄ - bulk and epitaxially strained thin films [1]. The methodology presented here can be easily applied to study phase transitions in other electronically active compounds. Second, I will discuss how we’ve used layered structures of different materials to understand the heterogeneity of the MIT and its coupled order parameters, and how this theory can be extended to devices [2]. Third, I will discuss the machine learning tools we’ve developed and provided to the community to discover new MIT compounds, and gain new insight into the features that characterize them [3]. Time permitting, I will discuss possible new MIT compounds we’ve identified using these machine learning based tools.