Understanding Defect Driven Phase Transitions in Correlated Quantum Materials with Quantum Monte Carlo

One of the most promising routes for manipulating the properties of correlated solids for technological applications is through control of defects, doping, and stoichiometry. However, the mechanisms that drive the electronic and magnetic transitions in these materials and the specific role of defects not fully understood. For example, the perovskite SrCoO3 is a ferromagnetic metal, while the oxygen-deficient (n-doped) brownmillerite SrCoO2.5 is an antiferromagnetic insulator. The challenge in predicting and understanding these behaviors from the intricate couplings of charge, spin, orbital, and lattice degrees of freedom. These challenge standard modeling approaches, requiring either significant empiricism or adoption of new methodologies to make progress. Here we outline our use of the highly accurate ab initio quantum Monte Carlo (QMC) approach to address these challenges. To control computational costs, we have developed a protocol of using QMC results to validate more scalable approaches via magnetic moments, charge densities, and thermodynamic properties. We present results for bulk and heterostructures of VO2[1,2], our model for how doping controls the metal-insulator transition in the correlated-perovskites[3], and the role of defects in the MnBi₂Te₄ system following this protocol.<br/> <br/>This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials.<br/> <br/>1. P. Ganesh et al., Physical Review B 101 155129 (2020).<br/>2. Q. Lu et al., Scientific Reports 10 1 (2020).<br/>3. M. Bennett et al., Physical Review Research 4 L022005 (2022).