Leng Kangmin, Guo Zhiqiang, Chen Junming, Fu Yao, Ma Ruihua, Yu Xuechao, Wang Li, Wang Qisheng
Department of Physics, School of Physics and Materials Science, Nanchang University, Nanchang 330031, China.
Department of Materials, School of Physics and Materials Science, Nanchang University, Nanchang 330031, China.
ACS Appl Mater Interfaces. 2024 Feb 14;16(6):7470-7479. doi: 10.1021/acsami.3c17935. Epub 2024 Feb 1.
Neuromorphic light sensors with analogue-domain image processing capability hold promise for overcoming the energy efficiency limitations and latency of von Neumann architecture-based vision chips. Recently, metal halide perovskites, with strong light-matter interaction, long carrier diffusion length, and exceptional photoelectric conversion efficiencies, exhibit reconfigurable photoresponsivity due to their intrinsic ion migration effect, which is expected to advance the development of visual sensors. However, suffering from a large bandgap, it is challenging to achieve highly tunable responsivity simultaneously with a wide-spectrum response in perovskites, which will significantly enhance the image recognition accuracy through the machine learning algorithm. Herein, we demonstrate a broadband neuromorphic visual sensor from visible (Vis) to near-infrared (NIR) by coupling all-inorganic metal halide perovskites (CsPbBr) with narrow-bandgap lead sulfide (PbS). The PbS/CsPbBr heterostructure is composed of high-quality single crystals of PbS and CsPbBr. Interestingly, the ion migration of CsPbBr with the implementation of an electric field induces the energy band dynamic bending at the interface of the PbS/CsPbBr heterojunction, leading to reversible, multilevel, and linearly tunable photoresponsivity. Furthermore, the reconfigurable and broadband photoresponse in the PbS/CsPbBr heterojunction allows convolutional neuronal network processing for pattern recognition and edge enhancements from the Vis to the NIR waveband, suggesting the great potential of the PbS/CsPbBr heterostructure in artificial intelligent vision sensing.
具有模拟域图像处理能力的神经形态光传感器有望克服基于冯·诺依曼架构的视觉芯片在能量效率和延迟方面的限制。最近，金属卤化物钙钛矿具有强光-物质相互作用、长载流子扩散长度和优异的光电转换效率，由于其固有的离子迁移效应而表现出可重构的光响应性，这有望推动视觉传感器的发展。然而，由于带隙较大，在钙钛矿中同时实现高可调光响应性和宽光谱响应具有挑战性，而这将通过机器学习算法显著提高图像识别精度。在此，我们通过将窄带隙硫化铅（PbS）与全无机金属卤化物钙钛矿（CsPbBr）耦合，展示了一种从可见光（Vis）到近红外（NIR）的宽带神经形态视觉传感器。PbS/CsPbBr异质结构由高质量的PbS和CsPbBr单晶组成。有趣的是，在电场作用下CsPbBr的离子迁移会在PbS/CsPbBr异质结界面处引起能带动态弯曲，从而导致可逆、多级和线性可调的光响应性。此外，PbS/CsPbBr异质结中可重构的宽带光响应允许进行卷积神经网络处理，以实现从可见光到近红外波段的模式识别和边缘增强，这表明PbS/CsPbBr异质结构在人工智能视觉传感方面具有巨大潜力。
