Colloquium- “Understanding Phase Transitions in Correlated Quantum Materials” with Dr. Panchapakesan Ganesh (Oak Ridge National Laboratory) [CANCELED]
Colloquium
February 19, 2025
3:00 PM - 4:00 PM
Location
238 2SES
Calendar
Download iCal File[CANCELED, WILL LIKELY BE RESCHEUDLED]
Abstract:
One of the most promising route for manipulating the properties of correlated solids for technological applications is through controlled perturbations via atomic-defects, doping, stoichiometry, strain as well as heterostructuring. However the mechanisms that drive the electronic, magnetic and/or topological transitions in these materials and the specific role of these perturbations is 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. Similarly, 2D materials such as MnBi2Te4 and WTe2 show different topological phases depending on how they are stacked or heterostructured, while layered CuInP2S6 show layer dependent ferroelectricity with multi-well character, with large anharmonicity [1,2]. Inducing local strain via ion-implantation or dimensional confinement can modify magnetic and related properties in correlated metals such as PdCoO2 and TbMn6Sn6. The challenge in predicting and understanding these behaviors from the intricate couplings of charge, spin, orbital, and lattice degrees of freedom. These at times challenge standard modeling approaches, requiring either significant empiricism or adoption of new methodologies to make progress. As such, in addition to using density functional theory, we also 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[3,4], our model for how doping controls the metal-insulator transition in the correlated-perovskites[5], the role of defects in inducing transitions in MnBi2Te4 [6] and PdCoO2 [7] systems, and effects of stacking and dimensional confinement in MnBi2Te4 and TbMn6Sn6 [8] following this protocol.
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.
1. Brehm etl al., Nature Materials, 19, 43 (2020)
2. N. Sivadas etl al., Physical Review Research 4, 013094 (2022)
3. P. Ganesh et al. . Physical Review B 101 155129 (2020).
4. Q. Lu et al. Scientific Reports 10 1 (2020).
5. M. Bennett et al. Physical Review Research 4 L022005 (2022).
6. J. Ahn et al, . Phys. Chem. Lett. 14, 40, 9052–9059 (2023)
7. M. Brahlak et al., Nano Lett. 23, 16, 7279–7287 (2023)
8. A. Annaberdiyev et. al., npj Quantum Materials, 8, article:50 (2023)
Brief Bio:
Ganesh received his Ph. D in Physics from the Physics Department at Carnegie Mellon University in 2007. Prior to joining ORNL in 2010, he was a postdoctoral fellow in the Geophysical Laboratory at the Carnegie Institution for Science. Before coming to the US, Ganesh earned his Bachelors in Physics with Honors from the prestigious Presidency University in Kolkata, India, and a MSc degree from the Department of Physics at Pune University, India, after gaining admissions via highly competitive national selection examinations.
Currently he leads the Nanomaterials Theory Institute at the Center for Nanophase Materials Sciences Division at Oak Ridge National Laboratory. The group focuses on developing new theoretical capabilities to enable fundamental understanding of nanoscale phenomena to enable breakthroughs in new materials discovery for next generation energy and computing technologies. Ganesh is also a thrust-lead in CPSFM, a DOE Computational Materials Science Center to develop Quantum Monte Carlo based highly accurate electronic-structure methods for predictive simulation of functional materials.
Date posted
Jan 8, 2025
Date updated
Feb 18, 2025