Self-Powered Photonic Synapses with Rapid Optical Erasing Ability for Neuromorphic Visual Perception
Mingchao Li,
Chen Li,
Kang Ye,
Yunzhe Xu,
Weichen Song,
Cihui Liu,
Fangjian Xing,
Guiyuan Cao,
Shibiao Wei,
Zhihui Chen,
Yunsong Di,
Zhixing Gan
Affiliations
Mingchao Li
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Chen Li
Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering,
Southeast University, Nanjing 210096, P. R. China.
Kang Ye
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Yunzhe Xu
Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering,
Southeast University, Nanjing 210096, P. R. China.
Weichen Song
Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering,
Southeast University, Nanjing 210096, P. R. China.
Cihui Liu
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Fangjian Xing
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Guiyuan Cao
Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology,
Shenzhen University, Shenzhen 518060, P. R. China.
Shibiao Wei
Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology,
Shenzhen University, Shenzhen 518060, P. R. China.
Zhihui Chen
Key Lab of Advanced Transducers and Intelligent Control System, Ministry of Education and Shanxi Province, College of Electronic Information and Optical Engineering,
Taiyuan University of Technology, Taiyuan 030024, P. R. China.
Yunsong Di
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Zhixing Gan
Center for Future Optoelectronic Functional Materials, School of Computer and Electronic Information/School of Artificial Intelligence,
Nanjing Normal University, Nanjing 210023, P. R. China.
Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information, making them crucial for the development of artificial vision systems. However, the development of high-performance photonic synapses with low power consumption and rapid optical erasing ability remains challenging. Here, we propose a photon-modulated charging/discharging mechanism for self-powered photonic synapses. The current hysteresis enables the devices based on CsPbBr3/solvent/carbon nitride multilayer architecture to emulate synaptic behaviors, such as excitatory postsynaptic currents, paired-pulse facilitation, and long/short-term memory. Intriguingly, the unique radiation direction-dependent photocurrent endows the photonic synapses with the capability of optical writing and rapid optical erasing. Moreover, the photonic synapses exhibit exceptional performance in contrast enhancement and noise reduction owing to the notable synaptic plasticity. In simulations based on artificial neural network (ANN) algorithms, the pre-processing by our photonic synapses improves the recognition rate of handwritten digit from 11.4% (200 training epochs) to 85% (~60 training epochs). Furthermore, due to the excellent feature extraction and memory capability, an array based on the photonic synapses can imitate facial recognition of human retina without the assistance of ANN.
