近日，清华大学的汪莱及其研究团队取得一项新进展。经过不懈努力，他们利用集成阻变随机存储器的光电二极管光电阵列，实现传感器内节能计算。相关研究成果已于2025年1月15日在国际知名学术期刊《光：科学与应用》上发表。

本文报道了一种通过集成光电二极管（PD）与阻变随机存储器（RRAM）实现传感器内计算的光电阵列。通过将RRAM编程至不同的电阻状态，PD-RRAM单元呈现出可重构的光电输出和光响应性。

此外，研究人员还制作了一个3×3的PD-RRAM阵列，用于演示光学图像识别，实现了具有超低延迟和低功耗的通用架构。本研究凸显了PD-RRAM光电阵列作为未来物联网应用中节能型传感器内计算基元的巨大潜力。

据悉，物联网（IoT）的迅猛发展迫切需要高效低功耗的边缘微型计算设备。传感器内计算技术应运而生，成为一种有前景的技术，能够在传感器阵列内部实现原位数据处理。

附：英文原文

Title: Optoelectronic array of photodiodes integrated with RRAMs for energy-efficient in-sensor computing

Author: Pan, Wen, Wang, Lai, Tang, Jianshi, Huang, Heyi, Hao, Zhibiao, Sun, Changzheng, Xiong, Bing, Wang, Jian, Han, Yanjun, Li, Hongtao, Gan, Lin, Luo, Yi

Issue&Volume: 2025-01-15

Abstract: The rapid development of internet of things (IoT) urgently needs edge miniaturized computing devices with high efficiency and low-power consumption. In-sensor computing has emerged as a promising technology to enable in-situ data processing within the sensor array. Here, we report an optoelectronic array for in-sensor computing by integrating photodiodes (PDs) with resistive random-access memories (RRAMs). The PD-RRAM unit cell exhibits reconfigurable optoelectronic output and photo-responsivity by programming RRAMs into different resistance states. Furthermore, a 3×3 PD-RRAM array is fabricated to demonstrate optical image recognition, achieving a universal architecture with ultralow latency and low power consumption. This study highlights the great potential of the PD-RRAM optoelectronic array as an energy-efficient in-sensor computing primitive for future IoT applications.

DOI: 10.1038/s41377-025-01743-y

Source: https://www.nature.com/articles/s41377-025-01743-y