Jiang Min, Zhao Yukun, Liu Tong, Chang Yanyan, Tang Yuan, Zhou Min, Shi Yiping, Zhang Jianya, Bian Lifeng, Lu Shulong
School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei, 230026, China.
Division of Nano-Devices Research, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), Suzhou, 215123, China.
Light Sci Appl. 2025 Aug 12;14(1):273. doi: 10.1038/s41377-025-01991-y.
Due to the extremely high manufacturing standards, the integration of quasi-omnidirectional photodetectors and synaptic devices within a single device remains a long-standing challenge. In this work, we have designed a graphene/(Al,Ga)N nanowire heterojunction, demonstrating the monolithic integration of self-driven 360° photodetectors and artificial synapses in a dual-mode transparent device successfully. By manipulating the carrier transport dynamics through controlling the bias voltage, the degree of oxygen vacancy ionization can be precisely regulated, ultimately realizing the monolithic dual-mode device. At 0 V bias, the device functions as a fast-response self-driven photodetector with stable optical communication capabilities, achieving 360° quasi-omnidirectional photodetection. Upon applying a bias voltage, the operating mode switches to a synaptic device, which successfully simulates brain-like paired-pulse facilitation, short-/long-term plasticity processes, and learning/forgetting behaviors. The device demonstrates an exceptionally high UV/visible rejection ratio of 1.29 × 10, coupled with an ultra-low dark current of less than 1 pA. Furthermore, this device has a low power consumption of 2.5 × 10 J per synaptic event, indicating an energy efficiency comparable to synaptic processes in the human brain. Moreover, nonlinear photoconductivity lets the device become a neuromorphic sensor for preprocessing images, enhancing recognition accuracy. Importantly, by leveraging the long-memory characteristic of the devices in open-circuit voltage mode, the devices have been successfully applied to guide humanoid robots in performing direction distinguishing and motion learning. This work provides new insights into the integrated manufacturing of multifunctional monolithic devices and foresees their immense potential in upcoming advanced, low-power neuromorphic computing systems.
由于极高的制造标准，在单个器件中集成准全向光电探测器和突触器件仍然是一个长期存在的挑战。在这项工作中，我们设计了一种石墨烯/（铝，镓）氮纳米线异质结，成功地在双模式透明器件中实现了自驱动360°光电探测器和人工突触的单片集成。通过控制偏置电压来操纵载流子传输动力学，可以精确调节氧空位电离程度，最终实现单片双模式器件。在0 V偏置下，该器件用作具有稳定光通信能力的快速响应自驱动光电探测器，实现360°准全向光电探测。施加偏置电压后，工作模式切换为突触器件，成功模拟了类脑的双脉冲易化、短期/长期可塑性过程以及学习/遗忘行为。该器件表现出高达1.29×1 的紫外/可见光抑制比，以及小于1 pA的超低暗电流。此外，该器件每个突触事件的功耗低至2.5×1 J，表明其能量效率与人脑突触过程相当。此外，非线性光电导使该器件成为用于预处理图像的神经形态传感器，提高了识别精度。重要的是，通过利用器件在开路电压模式下的长记忆特性，这些器件已成功应用于引导类人机器人进行方向辨别和运动学习。这项工作为多功能单片器件的集成制造提供了新的见解，并预见了它们在即将到来的先进低功耗神经形态计算系统中的巨大潜力。
