Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session S59: First Principles Modeling of Excited-State Phenomena in Materials: Excited State Methods
8:00 AM–11:00 AM,
Thursday, March 7, 2024
Room: 206AB
Sponsoring
Unit:
DCOMP
Chair: Aurelie Champagne, Lawrence Berkeley National Laboratory; Li Yang, Washington University, St. Louis
Abstract: S59.00010 : Enhancing Excited State Characterization in Transition Metal Oxides Through Advanced Wavefunction Methods*
10:12 AM–10:24 AM
Presenter:
Anouar Benali
(Argonne National Laboratory)
Authors:
Anouar Benali
(Argonne National Laboratory)
kevin gasperich
(Argonne National Laboratory)
Jaron T Krogel
(Oak Ridge National Lab)
Cody A Melton
(Sandia National Laboratories)
Raymond C Clay
(Sandia National Laboratories)
joshua P townsend
(Sandia National Laboratories)
Amanda E Dumi
(Sandia National Laboratories)
Luke N Shulenburger
(Sandia National Laboratories)
Conventional plane wave methods, even when enhanced with corrections like Hubbard U in Density Functional Theory (DFT), typically yield virtual orbitals that, while not necessarily incorrect, are often "correct for the wrong reasons." These methods lack in capturing the nuanced behavior of excited states, particularly in transition metal compounds. Our approach, utilizing advanced wavefunction methodologies, not only achieves a richer physical representation but also holds significant implications for computational material science. The optimized wavefunctions present a robust foundation for more accurate predictions in various complex behaviors, offering enhanced applicability in other advanced methods such as Diffusion Monte Carlo (DMC) and GW approximations. This synergy underscores the potential for these refined techniques to revolutionize predictive modeling and understanding of electronic excitations in complex materials.
*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.An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under contract DE-AC02-06CH11357.
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