受感觉神经系统启发的自分类、去耦合、多功能传感器,利用银纳米材料实现电阻电容式操作

IF 18.5 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY Advanced Functional Materials Pub Date : 2024-07-26 DOI:10.1002/adfm.202405687
Yoonji Yang, Byung Ku Jung, Taesung Park, Junhyuk Ahn, Young Kyun Choi, Seongkeun Oh, Yong Min Lee, Hyung Jin Choi, Hanseok Seo, Soong Ju Oh
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引用次数: 0

摘要

自我分类技术在无需任何电路或软件辅助的情况下自主辨别各种刺激物方面具有巨大潜力,可实现电子皮肤。传统的自我分类系统依赖于复杂的电路来运行,将传感和算法处理单元集成在一起不可避免地会导致设备的笨重和信号处理的瓶颈。在本研究中,受人体神经系统启发,新设计了一种新型双面结构的自分类传感器(SCS),无需额外电路。该传感器采用银纳米复合材料分层,通过界面工程和表面处理技术增强了机械性能。这种结构实现了电阻-电容混合操作,便于在单个设备中检测和区分应变、压力和温度的变化,从而模拟人类的感应识别过程。此外,还可通过分析检测到的信号确定施加刺激的强度,并通过传感器阵列实现刺激的精确定位。SCS 具有自我分类能力,为软机器人和先进多功能传感器平台的应用开辟了前景广阔的途径,提供了一种以简单高效为特点的传感系统。
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Sensory Nervous System‐Inspired Self‐Classifying, Decoupled, Multifunctional Sensor with Resistive‐Capacitive Operation Using Silver Nanomaterials
Self‐classification technology has remarkable potential for autonomously discerning various stimuli without any circuit or software assistance, enabling it to realize electronic skin. In conventional self‐classification systems that rely on complex circuitry for operation, integrating the sensing and algorithm processing units inevitably leads to bulkiness in devices and bottlenecks in signal processing. In this study, the novel double‐sided structure inspired by the human nervous system is newly designed for a self‐classifying sensor (SCS) without the need for additional circuits. The sensor is layered with Ag nanocomposites that have been mechanically enhanced via interface engineering and surface treatment techniques. This structure enables the resistance‐capacitance hybrid operation, facilitating the detection and distinguishment of changes in strain, pressure, and temperature within a single device, which mimics the human sensing recognition process. Moreover, the intensity of the applied stimuli is determined by analyzing the detected signal, and precise localization of the stimuli is achieved by arraying the sensors. With its self‐classification capabilities, SCS opens promising avenues for applications in soft robotics and advanced multifunctional sensor platforms, providing a sensing system characterized by simplicity and efficiency.
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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