First-principles calculations of the structural and electronic properties of cobaltites for neuromorphic applications

ORAL  · Invited

Abstract

Transition metal oxides (TMOs), particularly the cobaltites La1-xSrxCoO3-d (LSCO), are promising materials for neuromorphic computing. They display a metal-to-insulator transition (MIT) under the action of physical stimuli, which can be exploited to realize low power resistive switching devices. Here, using first principles calculations we investigate how to control the oxygen vacancy concentration in cobaltite to trigger a MIT. Experiments1 revealed a series of topotactic transitions in LSCO from perovskite to brownmillerite and to Ruddlesden-Popper phases, which displayed various magnetic states and a MIT. Our calculations2 based on DFT+U unraveled the complex interplay between crystal structures, magnetic and electronic properties that leads to the MIT. We found that cooperative structural distortions and concurrent magnetic state transitions during the topotactic transition are ultimately responsible for driving the MIT. To guide the design of resistive switching devices, we developed a first-principle model3 to predict the electrical bias needed to trigger the MIT, and provided strategies to minimize the threshold voltage. Further, to measure the oxygen vacancies concentration in thin film cobaltites, we combined experiments and theory to identify fingerprints of oxygen vacancies in the X-ray absorption spectra of LSCO and provided a robust protocol to determine oxygen stoichiometry4. Finally, we found that a metallic interface may arise in a heterostructure formed by two insulating phases in cobaltites5, and we identified the mechanism leading to the formation of such an interface. Our results point at the possibility of realizing energy-efficient resistive switching processes at a two-dimensional interface within a single material.

*This work was supported as part of the Quantum Materials for Energy Efficient Neuromorphic Computing Energy Frontier Research Center, funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences (# DE-SC0019273).

Publication: [1] Chiu, I.-T. et al., Phys. Rev. Mater. 5, 064416 (2021). [2] Zhang, S. & Galli, G., npj Comput. Mater. 6, 170 (2020). [3] Zhang, S., Vo, H. & Galli, G., Chem. Mater. 33, 3187–3195 (2021). [4] Zhang, S et al., Chem. Mater. 34, 2076-2084 (2022). [5] Zhang, S and Galli, G., (2023), in preparation.

Presenters

  • Shenli Zhang

    • University of Chicago

Authors

  • Shenli Zhang

    • University of Chicago
  • Giulia Galli

    • University of Chicago
  • I-Ting Chiu

    • University of California, Davis
  • Min-Han Lee

    • Applied Materials
  • Brandon Gunn

    • University of California, San Diego
  • Mingzhen Feng

    • University of California, Davis
    • University of California Davis
    • University of Calilfornia, Davis
  • Tae Joon Park

    • Purdue University
  • Padraic Shafer

    • Lawrence Berkeley National Lab
    • Lawrence Berkeley National Laboratory
    • Brookhaven National Laboratory
    • University of California, Davis
  • Alpha T N'Diaye

    • Lawrence Berkeley National Lab
    • Lawrence Berkeley National Laboratory
  • Fanny M Rodolakis

    • Argonne National Laboratory
  • Shriram Ramanathan

    • Rutgers University
  • Alex Frano

    • University of California, San Diego
  • IVAN K SCHULLER

    • University of California, San Diego
  • Yayoi Takamura

    • University of California, Davis