神经形态工程学
材料科学
记忆电阻器
触觉传感器
可穿戴计算机
感觉系统
灵活性(工程)
纳米技术
电子皮肤
电子线路
电阻随机存取存储器
灵敏度(控制系统)
人工神经网络
电子工程
嵌入式系统
计算机科学
电气工程
人工智能
工程类
电压
心理学
机器人
统计
数学
认知心理学
作者
Junhua Huang,Jiyong Feng,Zhiwei Chen,Zhenxi Dai,Shaodian Yang,Zibo Chen,Hao‐Li Zhang,Zheng Zhou,Zhiping Zeng,Xinming Li,Xuchun Gui
出处
期刊:Nano Energy
[Elsevier BV]
日期:2024-05-02
卷期号:126: 109684-109684
被引量:43
标识
DOI:10.1016/j.nanoen.2024.109684
摘要
Multifunctional near-sensor computing sensory neurons based on the integration of flexible sensors and memristors hold promise to achieve unprecedented development in large-scale neuromorphic perception circuits and human-machine interaction systems. However, the traditional sensory-memory integrated systems are based on the integration of different device modules, which are subjected to redundant analog-to-digital conversion circuits and poor flexibility. Here, an all MXene-based flexible sensory neuron fabricated by a room temperature energy-efficient, and controllable oxidation preparation technique is reported. The near-sensor computing system is seamlessly integrated a MXene-based pressure sensor array for acquisition of tactile signals with a flexible MXene-based memristor array for simulating the implementation of perceived behavior. The tactile sensor array shows a wide range (0.1-100 kPa), high linear sensitivity (23.9 kPa-1), and the memristor array exhibits repeatable and stable bipolar resistive switching behavior (retention >100 cycles, endurance >103 s) and excellent flexibility (R=1.0 mm). As a conceptual demonstration, our devices realize high-precision recognition of handwritten digit recognition (93.21%) and human motion (97.96%), which demonstrate the feasibility for real-time health monitoring based on signals collected by sensors and artificial neural networks constructed by the memristors. The MXene-based sensor-memristor system offers a prominent contribution towards advanced application of intelligence in electronic skin and wearable electronic equipment.
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