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Interface-engineered Gd₂O₃/ZrO₂ bilayer memristor for emulating synaptic plasticity in neuromorphic systems.

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Rare-earth oxide memristors show promise for brain-inspired computing. A novel bilayer device achieved high performance and accurately recognized patterns, paving the way for energy-efficient neurosynaptic systems.

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Area of Science:

  • Materials Science
  • Neurotechnology
  • Device Physics

Background:

  • Rare-earth materials are crucial for developing energy-efficient neuromorphic devices.
  • Memristive switching behavior is essential for brain-inspired computing.

Purpose of the Study:

  • To demonstrate a bilayer memristor with robust resistive switching and synaptic functionality.
  • To explore the potential of rare-earth oxides in neuromorphic applications.

Main Methods:

  • Fabrication of a bilayer Ag/Gd₂O₃/ZrO₂/Pt memristor.
  • Characterization of resistive switching behavior, endurance, and data retention.
  • Emulation of biological synaptic functions and pattern recognition using a multilayer perceptron network.

Main Results:

  • The memristor exhibited low operating voltage (<0.5 V), high ON/OFF ratio (∼10⁸), and excellent endurance (>5000 cycles).
  • The device successfully emulated synaptic plasticity and achieved 97.5% accuracy on the MNIST dataset.
  • Demonstrated long-term data retention (>5000 s).

Conclusions:

  • Bilayer oxide architectures offer a promising route for scalable, energy-efficient neurosynaptic systems.
  • Rare-earth based memristors are suitable for hardware-level implementation of artificial intelligence.
  • The developed memristor shows potential for advanced computing applications.