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May 22, 2026SmallOpen Access

A Bilayer Rare‐Earth/High‐κ Oxide Memristor for Energy‐Efficient Neuromorphic Intelligence

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Authors

HGHammad GhazanfarSejong UniversityMRMuhammad RabeelSejong UniversityHKHonggyun KimSejong University

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Implication

Randomized trial demonstrates synaptic capabilities of a bilayer memristor, suggesting advancements in neuromorphic systems.

Key Points

  • This research aims to develop an energy-efficient memristor that mimics biological synapses for neuromorphic computing.
  • Developed a CMOS-compatible Ag/Gd2O3/HfO2/Pt bilayer memristor with engineered interfaces and optimized defects.
  • Measured performance metrics such as ON/OFF current ratio, retention time, and switching transition time.
  • Integrated synaptic plasticity measurements into convolutional neural network simulations for performance evaluation.
  • Achieved an ON/OFF current ratio exceeding 10^7 and retention beyond 10^4 seconds.
  • Demonstrated a switching transition time of 350 ns and low programming energy of 13.6 pJ.
  • Obtained 78% classification accuracy on the Fashion-MNIST dataset, showcasing effective synaptic behavior.

Cite This Study

Ghazanfar et al. (2026) studied this question.

synapsesocial.com/papers/6a0ff42fd674f7c03778d69ahttps://doi.org/10.1002/smll.73836
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