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Bipolar and Complementary Resistive Switching Characteristics and Neuromorphic System Simulation in a Pt/ZnO/TiN
Sobia Ali Khan1, Geun Ho Lee2, Chandreswar Mahata1
1School of Electronics Engineering, Chungbuk National University, Cheongju 28644, Korea.
Nanomaterials (Basel, Switzerland)
|January 30, 2021
Summary
This study characterizes ZnO-based resistive switching memory devices. Bipolar and complementary resistive switching modes were achieved, with bipolar mode showing better pattern recognition for neuromorphic computing applications.
Area of Science:
- Materials Science
- Electrical Engineering
- Nanotechnology
Background:
- Resistive switching (RS) memory devices are crucial for next-generation electronics.
- Understanding device physics is key to optimizing performance.
- ZnO-based materials offer promising properties for memory applications.
Purpose of the Study:
- To characterize ZnO-based resistive switching memory devices.
- To investigate both bipolar resistive switching (BRS) and complementary resistive switching (CRS) modes.
- To evaluate device performance for potential neuromorphic computing applications.
Main Methods:
- Device fabrication and characterization using simplified electrical conduction models.
- Material and chemical analysis via transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS).
- Evaluation of BRS and CRS modes under varying bias conditions and pulse inputs.
Main Results:
- Uniform gradual BRS with good endurance and self-compliance was observed.
- CRS was successfully achieved by manipulating bias and compliance current.
- Synaptic behaviors like long-term potentiation and depression were emulated.
- BRS demonstrated a superior pattern recognition rate compared to CRS.
Conclusions:
- ZnO-based devices can operate in both BRS and CRS modes.
- BRS mode is more suitable for pattern recognition tasks due to uniform conductance updates.
- The study provides insights into optimizing ZnO-based resistive switching memory for neuromorphic computing.
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