Breakthrough in Neuromorphic Computing: Researchers Develop Low-Power Memristor

Strategic Insights -

Researchers from Tianjin University of Technology have made a significant discovery in the field of neuromorphic computing, developing a low-power memristor that can be used for energy-efficient image information sensing, processing, and protection. The memristor, which is a type of device that can store and process information, is essential for neuromorphic computing, providing the massive parallelism and connectivity needed to emulate complex brain-like functions with low energy consumption.

The memristor, known as a lead-free perovskite-based self-rectifying memristor, was developed using a self-organizing heterostructure enabled by halide ion migration. The device achieves ultralow SET power, a high rectification ratio, and fast switching, arising from Ag/iodide vacancy conductive channels and a spontaneously formed pn junction-like heterojunction. Functionally, the device leverages its characteristics to enable versatile applications, including basic logic gates, image encryption and reconstruction using keys generated by voltage-driven stochastic switching, and neuromorphic computing capabilities in array configuration.

This breakthrough has significant implications for the development of next-generation AI-oriented information technologies, establishing a new device/material paradigm for low-power, multifunctional SRMs that unify storage, logic, encryption, and neuromorphic computing.

Key Takeaways:

  • The researchers developed a lead-free perovskite-based self-rectifying memristor, which is essential for neuromorphic computing.
  • The memristor achieves ultralow SET power (approximately 16.8 fJ), a high rectification ratio (approximately 6.2 x 10^4), and fast switching (30 ns).
  • The device enables versatile applications, including basic logic gates, image encryption and reconstruction, and neuromorphic computing capabilities.
  • The memristor was developed using a self-organizing heterostructure enabled by halide ion migration.
  • The device establishes a new device/material paradigm for low-power, multifunctional SRMs that unify storage, logic, encryption, and neuromorphic computing.
  • The research was supported by the National Natural Science Foundation of China (NSFC).

Statistics:

  • The memristor achieves a recognition accuracy of approximately 92.08% in neuromorphic computing capabilities.
  • The device exhibits fast switching time of 30 ns.
  • The memristor is approximately 16.8 fJ of SET power.
  • The rectification ratio is approximately 6.2 x 10^4.

Sources:

  • "Lead-free Perovskite Based Self-rectifying Memristor With Self-organizing Heterojunction for Energy-efficient Image Information Sensing, Processing, and Protection." Advanced Functional Materials, 2025.
  • National Natural Science Foundation of China (NSFC)
  • NewsRx. Investigators at Tianjin University of Technology Discuss Findings in Information and Data Encoding and Encryption (Lead-free Perovskite Based Self-rectifying Memristor With Self-organizing Heterojunction for Energy-efficient Image Information ...). Information Technology Newsweekly. November 4, 2025; p 289.