Broadband All‐Optical Memtransistor Based on Organic Cocrystals for Noise‐Robust Motion Recognition
All-optical artificial synaptic devices offer promising potential for neuromorphic computing, yet their development is hindered by limited spectral tunability and poor plasticity linearity. Here, a broadband all-optical synaptic memtransistor based on organic charge transfer cocrystals (DTT-TCNQ) is reported, which enables fully light-driven and reversible modulation of synaptic weights across a wide wavelength range (395-808 nm). The device exhibits bidirectional excitatory and inhibitory photoresponses, and achieves highly linear long-term potentiation and depression (LTP/LTD) characteristics with ultralow nonlinearity (α<sub>p</sub> = 0.00191, α<sub>d</sub> = 0.00305) and asymmetry ratio (AR = 0.00114), attributed to a synergistic strategy combining frequency modulation and photoelectric coupling. When integrated into a convolutional neural long short-term memory network (CNN-LSTM) hybrid network, the device enables rapid convergence (98.77% accuracy in 6 training epochs) and robust recognition performance under spatiotemporal noise, outperforming conventional light-write/electric-erasing schemes. This work bridges material-level innovation and system-level functionality, offering a scalable approach toward energy-efficient, noise-resilient neuromorphic vision systems.
Authors
- Lixing Kang (ORCID: https://orcid.org/0000-0003-3837-7711)
- Jiahua Luo (ORCID: https://orcid.org/0000-0002-7911-5841)
- Ying‐Li Shi
- Chun Zhi Zhao (ORCID: https://orcid.org/0000-0002-4783-960X)
- Zhaohui Cai (ORCID: https://orcid.org/0000-0001-5935-3570)
- Rui Wu (ORCID: https://orcid.org/0000-0001-7133-185X)
- Zhengjun Liu (ORCID: https://orcid.org/0000-0002-0303-6290)
- Yuxiao Fang (ORCID: https://orcid.org/0000-0002-0845-1936)
- Wenjie Du (ORCID: https://orcid.org/0000-0001-5698-4617)
Institutions
- University of Science and Technology of China (CN)
- University of Liverpool (GB)
- Chinese Academy of Sciences (CN)
- Suzhou University of Science and Technology (CN)
- Suzhou Institute of Nano-tech and Nano-bionics (CN)
- Suzhou Research Institute (CN)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1002/advs.202515087
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Fourth Military Medical University