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Harnessing Defects in SnSe Film via Photo-Induced Doping for Fully Light-Controlled Artificial Synapse.
Zihui Liu1, Yao Wang1, Yumin Zhang1
1State Key Laboratory of Silicon and Advanced Semiconductor Materials, Cyrus Tang Center for Sensor Materials and Applications, School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310058, China.
Advanced Materials (Deerfield Beach, Fla.)
|December 9, 2024
Summary
Tin-selenium (SnSe) thin films exhibit both positive and negative persistent photoconductivity, enabling novel artificial synaptic devices. This breakthrough paves the way for advanced neuromorphic computing and bio-inspired simulations.
Area of Science:
- Materials Science
- Condensed Matter Physics
- Nanotechnology
Background:
- Silicon-based electronics face intrinsic physical limitations.
- Two-dimensional (2D) layered materials offer promising alternatives for next-generation devices.
- Persistent photoconductivity (PPC) is a key phenomenon for optoelectronic applications.
Purpose of the Study:
- To investigate the coexistence of positive (PPPC) and negative (NPPC) persistent photoconductivity in SnSe thin films.
- To engineer novel artificial synaptic devices utilizing the unique optoelectronic properties of SnSe.
- To demonstrate the potential of 2D materials in neuromorphic computing and biological behavior simulation.
Main Methods:
- Fabrication of SnSe thin films using pulsed laser deposition.
- Analysis of surface oxygen adsorption (physisorption and chemisorption) and its role in NPPC.
- Construction and testing of a light-modulated artificial synaptic device.
- Implementation of a three-layer artificial neural network for image recognition.
Main Results:
- SnSe thin films exhibit both PPPC and NPPC, with NPPC linked to photo-controllable oxygen desorption.
- A stable, light-modulated artificial synaptic device was successfully created using SnSe.
- The device demonstrated various synaptic plasticity functions and reversible conductance modulation.
- A neural network based on the SnSe device achieved 95.33% accuracy in handwritten digit recognition.
- Mimicry of human pressure cognition and anemonefish behaviors was achieved.
Conclusions:
- 2D SnSe thin films are highly suitable for developing neuromorphic computing devices and simulating biological behaviors.
- The observed PPPC and NPPC phenomena in SnSe offer a pathway for advanced device engineering.
- The one-step fabrication method is adaptable for large-area growth and integration of SnSe-based devices.
