Bidirectional Phosphorescent Neuroplasticity for All-Optical Neurovision
Zifan Li, Zicheng Zhang, Yueyue Wu, Zhe Zhou, Zixi He, Bin Liu, Xingyue Ji, Fa Zhang, Chen Chen, Fei Xiu, Xuemei Dong, Yuhan Zhang, Qiye Wang, Xiujuan Li, Wei Huang, Juqing Liu · ACS Nano · 2025
All-optical neuromorphics that can capture, process, and output photonic signals are in prospect to advance optical computing and imaging. Bidirectional neuroplasticity is essential for executing training and inference in optical neural networks, but most of the all-optical hardware only exhibits unidirectional weight modulation. Here, we explore bidirectional neuroplasticity in carbon dot phosphorescence (CDP) with potentiation and depression synaptic behaviors capable of neuroregulation for photonic intensity. This function enables the CDP as a neuroconverter to convert pulse light into excitatory and inhibitory light output for neuromorphic vision owing to the delayed release and superimposition dynamics of excitons in persistent phosphorescence, which allows for image digitization or direct observation. By integration with an optical neural network, the real-time motion tracking of light spots, including trajectory, direction, and speed, can be recorded and recognized, with a high accuracy of 96%. Such phosphor-based neuromorphics can be extended to other phosphorescent architectures for all-optical imaging and computing.