Optically tunable synaptic transistors based on AlGaN/GaN heterostructure for neuromorphic vision processing
Optoelectronic synaptic devices are a promising technology for overcoming the von Neumann bottleneck, meeting the demand from rapidly advancing artificial intelligence for faster, more energy-efficient neuromorphic computing. This study fabricated an optically tunable synaptic transistor based on an AlGaN/GaN heterostructure, which enables the implementation of neuromorphic vision processing. The device exhibits a low dark current in the cutoff region and a high photo-to-dark current ratio of 1.47 × 108, highlighting its excellent photoresponsivity. Under UV illumination, the device demonstrates synaptic behaviors such as excitatory postsynaptic current and paired-pulse facilitation. By tuning the time, power, and number of optical pulses, dynamic transitions from short-term memory to long-term memory are achieved, effectively emulating visual persistent memory. Furthermore, an optically modulated convolutional neural network is implemented, achieving a classification accuracy of 93.86% on the Fashion-MNIST dataset. These results validate the potential of the proposed device for neuromorphic vision processing applications.
Authors
- Mei Ge (ORCID: https://orcid.org/0000-0002-9001-6406)
- Xuyang Ge (ORCID: https://orcid.org/0000-0002-1306-2994)
- Guofeng Yang (ORCID: https://orcid.org/0000-0002-4409-9685)
- Jun‐Ge Liang (ORCID: https://orcid.org/0000-0003-1289-6513)
- Weiying Qian
- Jian Guo (ORCID: https://orcid.org/0000-0001-8049-2567)
- Huazhen Sun
- Xiaoqi Li (ORCID: https://orcid.org/0009-0004-7980-7794)
- Xinyi Shan (ORCID: https://orcid.org/0000-0001-6193-0787)
- Liejia Qian (ORCID: https://orcid.org/0000-0003-4036-8208)
- Xiangyang Zhang (ORCID: https://orcid.org/0000-0001-7873-1127)
- Xuekun Hong (ORCID: https://orcid.org/0000-0003-1650-5225)
Institutions
- Jiangnan University (CN)
- Kwangwoon University (KR)
- Nantong University (CN)
- Suzhou University of Technology (CN)
- Jiangsu University of Technology (CN)
- Hanyang University Medical Center (KR)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1063/5.0307178
- Citations
- 6
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 4.38