Probing ultrafast charge density wave diffusion in a trilayer nickelate

ORAL

Abstract

Low valence nickelates are a close analog to cuprates, sharing structural and electronic motifs and hosting superconductivity and charge density wave (CDW) phases in close proximity. Whether these correlated phases have common origins in both systems is an open question. While static CDWs are thought to compete with superconductivity, CDW fluctuations could enhance or even contribute to superconducting pairing [1]. We use non-resonant ultrafast x-ray diffraction to observe the suppression and subsequent recovery of the CDW phase in the stripe-ordered trilayer nickelate La4Ni3O8 [2] in response to an 800 nm pump excitation. The intensity of the (-1/3, 1/3, 9) CDW peak was monitored with a 2D detector, simultaneously measuring the response along a 2D momentum cut through the CDW peak. Conventional analysis required large time and momentum binning, due to weak CDW intensity and high background and noise levels. However, using the machine learning algorithm Xray-TEmperature series Clustering (X-TEC) [3] to track and analyze the time-evolution of individual pixels, we were able to determine momentum-dependent recovery rates and compare them to similar observations in La1.75Ba0.25CuO4. We find that La4Ni3O8 exhibits diffusive dynamics, similar to the cuprate La1.75Ba0.25CuO4 [4], rather than inertial dynamics as in conventional Peierls CDW systems. This indicates that in both cuprates and nickelates charge order can fluctuate at any temperature and can contribute to the emergent electronic behavior in both classes of materials.

[1] E. Fradkin, et al. Rev. Mod. Phys. 87, 457 (2015).

[2] J. Zhang. et al. PNAS, 113, 8945-8950 (2016).

[3] J. Venderley, et al. PNAS 119(24) (2022).

[4] M. Mitrano, M. et al. Sci. Adv. 5, (2019).

* This work was primarily supported by as supported by the U.S. Department of Energy (DOE), Division of Materials Science, under Contract No. DE-SC0012704.KM & E-AK also acknowledge funding from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, and Gordon and Betty Moore Foundation’s EPiQS Initiative, Grant GBMF10436. KM is also supported by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship: a Schmidt Futures program

Presenters

  • Sophia F TenHuisen

    Harvard University

Authors

  • Sophia F TenHuisen

    Harvard University

  • Krishnanand M Mallayya

    Cornell University

  • Filippo Glerean

    Harvard University

  • Yao Shen

    Brookhaven National Laboratory

  • Jennifer Sears

    Brookhaven National Laboratory

  • Haining Pan

    Cornell University

  • Wei He

    Brookhaven National Laboratory

  • Junjie Zhang

    Shandong Univ

  • J. F Mitchell

    Argonne National Laboratory

  • Christie Nelson

    Brookhaven National Laboratory

  • Raul Acevedo-Esteves

    Brookhaven National Laboratory

  • Tadashi Togashi

    Japan Synchrotron Radiation Research Institute

  • Yoshikazu Tanaka

    RIKEN

  • Taito Osaka

    RIKEN SPring-8 Center

  • Yuya Kubota

    RIKEN SPring-8 Center

  • Mark P Dean

    Brookhaven National Laboratory

  • Eun-Ah Kim

    Cornell University

  • Matteo Mitrano

    Harvard University