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
{"title":"Sensory Nervous System‐Inspired Self‐Classifying, Decoupled, Multifunctional Sensor with Resistive‐Capacitive Operation Using Silver Nanomaterials","authors":"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","doi":"10.1002/adfm.202405687","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":112,"journal":{"name":"Advanced Functional Materials","volume":null,"pages":null},"PeriodicalIF":18.5000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Functional Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/adfm.202405687","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.