Wang Jiejun, Pan Xinqiang, Zhao Zebin, Xie Yiduo, Luo Wenbo, Xie Qin, Zeng Huizhong, Shuai Yao, Song Zeqian, Wu Chuangui, Zhang Wanli
School of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
National Key Laboratory of Electronic Thin Film and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Adv Sci (Weinh). 2024 Feb;11(6):e2307359. doi: 10.1002/advs.202307359. Epub 2023 Dec 25.
To efficiently process the massive amount of sensor data, it is demanding to develop a new paradigm. Inspired by neurobiological systems, an infrared near-senor reservoir computing (RC) system, consisting of infrared sensors and memristors based on single-crystalline LiTaO and LiNbO (LN) thin film respectively, is demonstrated. The analog memristor is used as a reservoir in the RC system to process sensor signals with spatiotemporal characteristics. LN crystal structure stacked with oxygen octahedra provides favorable conditions for reliable Mott variable-range hopping conduction, which provides the memristor with tens of thousands of reservoir states within a large dynamic range. With the characteristics, the analog sensor signals with high data fidelity can be directly fed to the memristive reservoir, and the spatiotemporal features can be separated and mapped. The system demonstrated a dynamic gesture perception task, achieving an accuracy of 99.6%, which highlights the great application potential of the memristor in signal sensor processing and will advance the application of artificial intelligence in sensor systems. Crystal ion slicing techniques are used to fabricate a single-crystalline thin film for both the memristor and sensor, which opens up the possibility of realizing monolithic integration of a memristor-based near-sensor computing system.
为了高效处理海量传感器数据,开发一种新范式很有必要。受神经生物学系统启发,展示了一种红外近传感器储层计算(RC)系统,该系统分别由基于单晶LiTaO和LiNbO(LN)薄膜的红外传感器和忆阻器组成。模拟忆阻器在RC系统中用作储层,以处理具有时空特征的传感器信号。由氧八面体堆叠而成的LN晶体结构为可靠的莫特变程跳跃传导提供了有利条件,这为忆阻器在大动态范围内提供了数万个储层状态。基于这些特性,具有高数据保真度的模拟传感器信号可直接输入到忆阻性储层中,并且时空特征可以被分离和映射。该系统展示了动态手势感知任务,准确率达到99.6%,这突出了忆阻器在信号传感器处理中的巨大应用潜力,并将推动人工智能在传感器系统中的应用。晶体离子切片技术用于制造用于忆阻器和传感器的单晶薄膜,这为实现基于忆阻器的近传感器计算系统的单片集成开辟了可能性。