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Molecular Reconfiguration of Disordered Tellurium Oxide Transistors with Biomimetic Spectral Selectivity
Yuxuan Zhang1, Jingwen Wang2, Pengshan Xie1
1Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Advanced Materials (Deerfield Beach, Fla.)
|October 18, 2024
Summary
Researchers developed a novel disordered tellurium oxide device that acts as both a logic transistor and a neuromorphic device. This breakthrough enhances data processing and reduces power consumption in next-generation electronics.
Area of Science:
- Materials Science
- Semiconductor Devices
- Neuromorphic Computing
Background:
- Reconfigurable devices are crucial for next-generation semiconductor platforms, offering enhanced data processing and reduced power consumption.
- Existing 2D materials for such devices often require complex operating rules and additional components.
- There is a need for simpler, highly functional reconfigurable materials.
Purpose of the Study:
- To introduce a novel p-type disordered tellurium oxide material for dual-mode reconfigurable devices.
- To demonstrate its capability as both a logic transistor and a neuromorphic device.
- To explore its application in advanced vision systems.
Main Methods:
- Fabrication of a p-type disordered tellurium oxide film.
- Utilizing oxygen molecule adsorption and laser-induced desorption to modulate carrier concentration.
- Characterization of transistor performance and neuromorphic functionalities.
Main Results:
- The device achieved high-performance p-type characteristics with a field-effect hole mobility of 10.02 cm2 V-1 s-1 and an Ion/Ioff ratio > 106.
- Demonstrated biomimetic bee vision, responding specifically to blue-to-ultraviolet light.
- Achieved in-sensor denoising and invisible image recognition in static and dynamic scenarios.
Conclusions:
- Disordered tellurium oxide offers a promising pathway for dual-mode reconfigurable devices.
- The material enables high-performance logic and advanced neuromorphic functionalities.
- This technology has potential applications in efficient, intelligent vision systems.

