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Reduction Optimization for Superconducting Lanthanum Nickelates

ORAL

Abstract

Infinite-layer nickelates are promising candidates for studying unconventional superconductivity because of their electronic and structural similarities with the cuprates [1-2]. Despite their similarities, theoretical calculations of the infinite-layer nickelate band structure have revealed properties that differ from the cuprates, including the presence of electron pockets in the Fermi surface, which creates a “self-doping” effect to make the ground state of the parent compound metallic with no long-range magnetic order observed to date [3-4]. The study of nickelates is limited because the poor thermodynamic stability of the system constrains synthesis to nanometer-scale thin films, with challenges in maintaining high crystallinity [4-7]. Our ongoing efforts to optimize materials growth and subsequent topotactic reduction have substantially improved the synthesis of infinite-layer lanthanum nickelate (LaNiO2) and reduced the transport scattering effects of disorder. Investigation of topotactic reduction from the parent perovskite to infinite-layer phase allow us to construct a phase diagram in the space of reduction time and temperature that determine optimal parameters for transport measurements.

References

[1] A. S. Botana and M. R. Norman, Phys. Rev. X 10, 011024 (2020).

[2] K.-W. Lee and W. E. Pickett, Phys. Rev. B 70, 165109 (2004).

[3] K. Lee et al., 27 (2022)

[4] X. Zhou et al., Materials Today S1369702122000591 (2022) K.

[5] D. Li et al., Nature 572, 624 (2019).

[6] D. Preziosi et al., AIP Advances 7, 015210 (2017).

[7] Lee et al., APL Materials 12 (2020).

Presenters

  • Martin Gonzalez

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

Authors

  • Martin Gonzalez

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Kyuho Lee

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Jennifer Fowlie

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Yonghun Lee

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Yijun Yu

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Bai Yang Wang

    Stanford University, Stanford University, SLAC National Accelerator Laboratory

  • Harold Hwang

    Stanford Univ, Stanford University