The goal here is to develop energy-efficient memristors based on the unique metal-insulator transitions (MIT) in TMOs. We aim to map fundamental materials properties to device performance using DFT calculations and physics-based surrogate models. Currently we are looking into two systems:

1. Free-standing TMO membranes, MIT controlled by oxygen vacancies

2. MIT controlled by proton doping, to design TMOs for low switching energy and fast switching speed

Related publications:

• M. Feng, J. Li, S. Zhang, A. Pofelski, R.E. Hage, C. Klewe, A. N’diaye, P. Shafer, Y. Zhu, G. Galli, I. Schuller, Y. Takamura, “Hydrogen-induced topotactic phase transformations of cobaltite thin films”, J. Phys. Chem. C 128, 17124-17133 (2024). 

• S. Zhang and G. Galli, “Metallic interface between two insulating phases of La1-xSrxCoO3-d”, Chem. Mater. 36, 2096-2105 (2024).

• S. Zhang, I. Chiu, M. Lee, B. Gunn, M. Feng, T. Park, P. Shafer, A. N’Diaye, F. Rodolakis, S. Ramanathan, A. Frano, I. Schuller, Y. Takamura and G. Galli, “Determine the oxygen stoichiometry of cobaltite thin films”, Chem. Mater. 34, 2076-2084 (2022).

• I. Chiu, M. Lee, S. Cheng, S. Zhang, L. Heki, Z. Zhang, Y. Mohtashami, P. Lapa, M. Feng, P. Shafer, A. Mehta, J. Schuller, G. Galli, S. Ramanathan, Y. Zhu, I. Schuller, Y. Takamura, “Cation and anion topotactic transformations in cobaltite thin films leading to Ruddlesden-Popper phases”, Phys. Rev. Mater. 5, 064416 (2021).

• S. Zhang, H. Vo and G. Galli, “Predicting the onset of metal-insulator transitions in transition metal oxides—a first step in designing neuromorphic devices”, Chem. Mater. 33, 3187-3195 (2021).

• H. Vo†, S. Zhang†, W. Wang† and G. Galli, “Lessons learned from first-principles calculations of transition metal oxides”, J. Chem. Phys. 154, 174704 (2021). (†: equal contribution).

• S. Zhang, G. Galli, "Understanding the metal-to-insulator transition in LaxSr1-xCoO3-d and its applications for neuromorphic computing",  npj Comput. Mater. 6, 170 (2020). 

We apply/optimize/develop machine learning models to accelerate the screen and design of materials for various applications. Current focus is to identify appropriate machine learning models to search intermetallics as copper replacement for interconnects in CMOS chips. 

Related publications:

• S. Zhang, Y. Huang, G. Tetiker, S. Srirman, A. Paterson and R. Faller, “Computational modelling of atomic layer etching of chlorinated germanium surfaces by argon”, Phys. Chem. Chem. Phys. 21, 5898-5902 (2019).

Currently, this part of the research is in collaboration with LLNL and Prof. Nien-Hui Ge at UC Irvine. We focus on hydrogen production via 1) proton-conducting oxide electrolyzer cells; 2) solar water splitting technology based on BiVO4.  We calculate proton transport properties, electron-phonon renormalization and IR/Raman spectra to apply oxides for efficient hydrogen production.

Previous research also covers layered-TMO materials as cathode for Li-ion battery development based on DFT calculations,  as well as fission gas adsorption with porous materials and toughening of nanocrystalline oxides with doping at grain boundaries which are based on classical molecular simulations.

Related publications:

• S. Yuan, S. E. Weitzner, W. Jeong, S. Zhang, B. Wang, L. Feng, J. L. Kaufman, K. Kim, Y. Qi and L.F. Wan, "Modeling single-crystal battery materials: from fundamental understanding to performance evaluation", https://doi.org/10.1021/acs.chemrev.5c00360 (2026).

• S. Zhang, W. Sun, E.G. Lomeli, W. Jeong, S.E. Weitzner, L.F. Wan, “Benchmarking density functional theory methods for efficient calculations of a strongly correlated LiNiO2 system”, ACS Appl. Energy Mater., 8, 13, 9110-9120 (2025).

• S.E. Weitzner, B. Wang, N. Rampal, W. Jeong, S. Yuan, S. Zhang, G. Bucci, N. Adelstein, S. Yan, A.C. Marschilok, L.F. Wan, “Cross-scale modeling and experimental integration for advancing cathode electrolyte interphase studies in high energy density lithium-ion batteries”, Energy Storage Mater. 80, 104368 (2025).

• S. Zhang, A.E. Rowberg, T. Ogitsu, T.A. Pham, J.B. Varley, “Electron-phonon renormalization in the proton-conducting electrolyte BaZrO3 and its implications for high-temperature electrolysis”, PRX Energy 4, 013013 (2025).

• A. Hilbrands†, S. Zhang†, C. Zhou, G. Melani, D. H. Wi, D. Lee, Z. Xi, A. R. Head, M. Liu, G. Galli and K.S. Choi, “Impact of varying the photoanode/catalyst interfacial composition on solar water oxidation: the case of BiVO4(010)/FeOOH photoanodes”, J. Am. Chem. Soc. 145, 23639-23650 (2023).

•  Y. Yuan†, Y. Yang†, K. Meihaus, S. Zhang, X. Ge, W. Zhang, R. Faller, J. Long and G. Zhu, “Selective scandium ion capture via coordination templating in a covalent organic framework”, Nat. Chem. 15, 1599-1606 (2023).

• Y. Yang, D. Deng, S. Zhang, Q. Meng, Z. Li, Z. Wang, H. Sha, R. Faller, Z. Bian, X. Zou, G. Zhu and Y. Yuan et al., “Porous organic frameworks featured by distinct confining fields for the selective hydrogenation of biomass-derived ketones”, Adv. Mater. 32, 1908243 (2020).

• A. Bokov, S. Zhang, S. J. Dillon, L. Feng, R. Faller and R. Castro, “Energetic design of grain boundary networks for toughening of nanocrystalline oxides”, J. Eur. Ceram. Soc. 38, 4260-4267 (2018).

• H. Sha, S. Zhang and R. Faller, “Molecular investigation of gas adsorption, separation, and transport on carbon nanoscrolls: A combined grand canonical Monte Carlo and molecular dynamics study”, Carbon 132, 401-410 (2018).

• S. Zhang, H. Sha, R. Castro and R. Faller, “Atomistic modeling of La3+ doping segregation effect on nanocrystalline yttria-stabilized zirconia”, Phys. Chem. Chem. Phys. 20, 13215-13223 (2018). (selected as hot papers).

•  S. Zhang, E. Yu, S. Gates, W. Cassata, J. Makel, A. Thron, C. Bartel, A. Weimer, R. Faller, P. Stroeve and J. Tringe, “Helium interactions with alumina formed by atomic layer deposition show potential for mitigating problems with excess helium in spent nuclear fuel”, J. Nucl. Mater. 499, 301-311 (2017).

• S. Zhang, M. Pérez-Page, K. Guan, E. Yu, J. Tringe, R. Castro, R. Faller and P. Stroeve, “Response to extreme temperatures of mesoporous silica MCM-41: porous structure transformation simulation and modification of gas adsorption properties”, Langmuir 32, 11422-11431 (2016).

Defects in wide band gap semiconductors, such as diamond, has been demonstrated as promising platforms to realize qubits for quantum computing. This future research direction aims to investigate defects configurations similar to known NV-1 center.