Screening strongly correlated materials in solid oxide cells with quantum simulation
Abstract
We develop an end-to-end framework for assessing a quantum-computing application in industrial materials science: the screening of strongly correlated oxygen-electrode materials for SOFCs and SOECs. We formulate the materials problem in terms of interface observables including oxygen-vacancy formation energies, vacancy migration barriers, and electronic conductivity. We describe how these observables can be obtained using a diagrammatic GW-based embedding, either GW+DMFT or self-energy embedding theory (SEET), applied to a DFT-screened shortlist. The atomistic electrode/electrolyte interface defines the electronic structure problem from which the correlated impurity models are constructed. Quantum impurity solvers would provide the finite-temperature impurity Green's functions required by the embedding. The computational challenges that classical solvers may encounter as the interacting active space grows, together with the polynomial scaling of quantum Hamiltonian simulation for efficiently represented discretized models, open an opportunity for quantum advantage. We identify the benchmarks needed to assess this opportunity through convergence of vacancy and migration energetics and comparison with the best applicable classical solvers. We provide illustrative logical qubit counts and identify the thermal state preparation, simulation, measurement, and repeated-solve costs needed for a complete resource assessment. We connect microscopic observables to macroscopic engineering metrics using a continuum model for mixed ionic--electronic conducting oxygen electrodes that couples oxygen surface exchange, solid-state oxygen transport, electrode microstructure, and finite electrode thickness. Finally, we estimate the potential worldwide business value of improved electrode materials under SOFC and SOEC deployment scenarios informed by public technical targets and electrolyser deployment data.
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BibTeX
@misc{harzli2026screening,
title = {{Screening strongly correlated materials in solid oxide cells with quantum simulation}},
author = {Ouns El Harzli and Jelle Bor and Linde Wester and Leonid Zhukov and Hanl Park and Jean-François Bobier and Matt Langione and Antonino Marco Saitta and Jonathan Owens and Richard Hart and Yudong Cao and François Jamet},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.31591},
eprint = {2610.31591},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.31591},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Screening strongly correlated materials in solid oxide cells with quantum simulation
AU - Ouns El Harzli
AU - Jelle Bor
AU - Linde Wester
AU - Leonid Zhukov
AU - Hanl Park
AU - Jean-François Bobier
AU - Matt Langione
AU - Antonino Marco Saitta
AU - Jonathan Owens
AU - Richard Hart
AU - Yudong Cao
AU - François Jamet
PY - 2026
DA - 2026/10/22
PB - arXiv
DO - 10.48550/arxiv.2610.31591
UR - https://arxiv.org/abs/2610.31591
AB - We develop an end-to-end framework for assessing a quantum-computing application in industrial materials science: the screening of strongly correlated oxygen-electrode materials for SOFCs and SOECs. We formulate the materials problem in terms of interface observables including oxygen-vacancy formation energies, vacancy migration barriers, and electronic conductivity. We describe how these observables can be obtained using a diagrammatic GW-based embedding, either GW+DMFT or self-energy embedding theory (SEET), applied to a DFT-screened shortlist. The atomistic electrode/electrolyte interface defines the electronic structure problem from which the correlated impurity models are constructed. Quantum impurity solvers would provide the finite-temperature impurity Green's functions required by the embedding. The computational challenges that classical solvers may encounter as the interacting active space grows, together with the polynomial scaling of quantum Hamiltonian simulation for efficiently represented discretized models, open an opportunity for quantum advantage. We identify the benchmarks needed to assess this opportunity through convergence of vacancy and migration energetics and comparison with the best applicable classical solvers. We provide illustrative logical qubit counts and identify the thermal state preparation, simulation, measurement, and repeated-solve costs needed for a complete resource assessment. We connect microscopic observables to macroscopic engineering metrics using a continuum model for mixed ionic--electronic conducting oxygen electrodes that couples oxygen surface exchange, solid-state oxygen transport, electrode microstructure, and finite electrode thickness. Finally, we estimate the potential worldwide business value of improved electrode materials under SOFC and SOEC deployment scenarios informed by public technical targets and electrolyser deployment data.
ER -