@article{Sun2025, 
author = {Tongrui Sun and Xu Liu and Yutong Xu and Xinglei Zhao and Pu Guo and Junyao Zhang and Ziyi Guo and Yue Wu and Shilei Dai and Jia Huang},
title = {Stretchable artificial vision sensor with retinomorphic transistor-reservoir computing},
year = {2025},
journal = {Nano Research},
volume = {18},
number = {3},
pages = {94907191},
keywords = {stretchable electronics, artificial vision sensors (AVSs), retinomorphic transistors, reservoir computing, neuromorphic computing},
url = {https://www.sciopen.com/article/10.26599/NR.2025.94907191},
doi = {10.26599/NR.2025.94907191},
abstract = {Artificial visual sensors (AVSs) with bio-inspired sensing and neuromorphic signal processing are essential for next-generation intelligent systems. Conventional optoelectronic devices employed in AVSs operate discretely in terms of sensing, processing, and memorization, and not ideal for applications necessitating shape deformation to achieve wide fields-of-view and deep depths-of-field. Here, we present stretchable artificial visual sensors (S-AVS) capable of concurrently sensing and processing optical signals while adapting to shape deformations. Specifically, these S-AVSs use a stretchable transistor structure with a meticulously engineered photosensitive semiconductor layer, comprising an organic semiconductor, thermoplastic elastomer, and cesium lead bromide quantum dots (CsPbBr3 QDs). They exhibit synaptic behaviors such as excitatory postsynaptic current (EPSC) and paired-pulse facilitation (PPF) under optical signals, maintaining functionality under 30% strain and repeated stretching. The nonlinear response and fading memory effect support in-sensor reservoir computing, achieving image recognition accuracies of 97.46% and 97.1% at 0% and 30% strain, respectively.}
}