Towards High-Precision Heterogeneous Catalysis By Quantum Monte Carlo
ORAL
Abstract
Our ongoing efforts to improve green energy transformation by catalysis mainly focuses on surface adsorption phenomena. Surfaces of transition metal oxides [see J. Phys. Chem. C 126, 7903 (2022)] are of particular interest where precision of DFT approximations becomes an issue. In related work, the Diffusion Monte Carlo method was shown to accurately capture the electron correlation in extended systems like CO*-Pt(111) with relatively smaller supercells, leading to cost-effective calculations [J. Phys. Chem. A 126, 4636 (2022)].
We deploy QMCPACK [J. Phys.: Condens. Matter 30, 195901 (2018)] on the NERSC Perlmutter machine and discuss the relative performance of the CPU and GPU implementation. We reproduced the CO*-Pt(111) puzzle and tested the size extrapolation scheme. Our main project is to assess the accuracy of the commonly utilized DFT methods for the (110) surface of RuO2, a well-known catalytic system for oxygen evolution reaction. Finally, we will discuss the challenges in the accurate prediction of catalytic properties such as reaction and formation energies, and general surface adsorption phenomena.
We deploy QMCPACK [J. Phys.: Condens. Matter 30, 195901 (2018)] on the NERSC Perlmutter machine and discuss the relative performance of the CPU and GPU implementation. We reproduced the CO*-Pt(111) puzzle and tested the size extrapolation scheme. Our main project is to assess the accuracy of the commonly utilized DFT methods for the (110) surface of RuO2, a well-known catalytic system for oxygen evolution reaction. Finally, we will discuss the challenges in the accurate prediction of catalytic properties such as reaction and formation energies, and general surface adsorption phenomena.
* We acknowledge the LDRD support by SLAC National Laboratory on High-Precision Heterogeneous Catalysis By Quantum Monte Carlo. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award ERCAP0024139.
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Presenters
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Roman Fanta
SLAC National Accelerator Laboratory
Authors
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Roman Fanta
SLAC National Accelerator Laboratory
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Michal Bajdich
SLAC National Accelerator Laboratory