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Neotype kuramite optoelectronic memristor for bio-synaptic plasticity simulations
Xiaofei Dong1, Wenbin Wei1, Hao Sun1
1Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
The Journal of Chemical Physics
|May 8, 2023
Summary
New memristive devices using kuramite (Cu3SnS4) mimic brain synapses. These devices exhibit electrical and optical control, paving the way for advanced neuromorphic computing systems.
Area of Science:
- Materials Science
- Neuroscience
- Electrical Engineering
Background:
- Brain-inspired neuromorphic computing requires advanced memristive devices capable of mimicking synaptic behavior.
- Developing novel resistive materials and device architectures is crucial for achieving high-performance neuromorphic systems.
Purpose of the Study:
- To introduce kuramite (Cu3SnS4) as a switching medium for constructing memristive devices.
- To demonstrate the bio-mimicry of diverse optoelectronic synaptic plasticity in these novel memristors.
Main Methods:
- Constructed memristive devices using kuramite (Cu3SnS4) embedded in poly-methacrylate.
- Evaluated device performance including resistive switching characteristics, retention, and synaptic plasticity behaviors.
- Investigated both electrically and optically induced synaptic functionalities.
Main Results:
- Achieved stable bipolar resistive switching with a high On/Off ratio (∼486) and low switching voltages (∼-0.88/+0.96 V).
- Demonstrated excellent retention up to 10^4 s and multi-level controllable resistive-switching memory.
- Successfully mimicked various optoelectronic synaptic plasticity behaviors, including excitatory postsynaptic currents, short-/long-term memory, and learning-forgetting dynamics.
Conclusions:
- Kuramite-based memristive devices exhibit promising performance for artificial optoelectronic synaptic applications.
- These devices show potential for constructing advanced neuromorphic architectures that simulate human brain functions.
- The integration of electrical and optical control in memristors opens new avenues for brain-inspired computing.
