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Unveiling ECRAM switching mechanisms using variable temperature Hall measurements for accelerated AI computation

Author

Listed:
  • Hyunjeong Kwak

    (Pohang University of Science and Technology)

  • Junyoung Choi

    (Pohang University of Science and Technology)

  • Seungmin Han

    (Pohang University of Science and Technology)

  • Eun Ho Kim

    (Pohang University of Science and Technology)

  • Chaeyoun Kim

    (Korea Advanced Institute of Science and Technology)

  • Paul Solomon

    (IBM T. J. Watson Research Center)

  • Junyong Lee

    (Pohang University of Science and Technology)

  • Doyoon Kim

    (Pohang University of Science and Technology)

  • Byungha Shin

    (Korea Advanced Institute of Science and Technology)

  • Donghwa Lee

    (Pohang University of Science and Technology)

  • Oki Gunawan

    (IBM T. J. Watson Research Center)

  • Seyoung Kim

    (Pohang University of Science and Technology)

Abstract

Electrochemical random-access memory devices are promising for analog cross-point array-based artificial intelligence accelerators due to their high stability and programmability. However, understanding their switching mechanism is challenging due to complex multilayer structures and the high resistivity of oxide materials. Here, we fabricate multi-terminal Hall-bar devices and conduct alternating current magnetic parallel dipole line Hall measurements to extract transport parameters. Through variable-temperature Hall measurements, we determine the oxygen donor level at approximately 0.1 eV in tungsten oxide and reveal that conductance potentiation even at low temperatures results from increased mobility and carrier density. This behavior is linked to reversible electronic and atomic structure changes, supported by density functional theory calculations. Our findings enhance the understanding of electrochemical random-access memory switching mechanisms and provide insights for improving high-performance, energy-efficient artificial intelligence computation in analog hardware.

Suggested Citation

  • Hyunjeong Kwak & Junyoung Choi & Seungmin Han & Eun Ho Kim & Chaeyoun Kim & Paul Solomon & Junyong Lee & Doyoon Kim & Byungha Shin & Donghwa Lee & Oki Gunawan & Seyoung Kim, 2025. "Unveiling ECRAM switching mechanisms using variable temperature Hall measurements for accelerated AI computation," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58004-0
    DOI: 10.1038/s41467-025-58004-0
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    References listed on IDEAS

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