Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115586
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dc.contributorDepartment of Applied Biology and Chemical Technology-
dc.contributorResearch Institute for Smart Energy-
dc.creatorGong, G-
dc.creatorZhou, Y-
dc.creatorLi, Q-
dc.creatorZhao, W-
dc.creatorGeng, S-
dc.creatorLi, H-
dc.creatorLeng, Y-
dc.creatorZhu, S-
dc.creatorDing, G-
dc.creatorZhai, Y-
dc.creatorLv, Z-
dc.creatorZhou, Y-
dc.creatorHan, ST-
dc.date.accessioned2025-10-08T01:16:46Z-
dc.date.available2025-10-08T01:16:46Z-
dc.identifier.issn0935-9648-
dc.identifier.urihttp://hdl.handle.net/10397/115586-
dc.language.isoenen_US
dc.publisherWiley-VCH Verlag GmbH & Co. KGaAen_US
dc.rights© 2025 The Author(s). Advanced Materials published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.en_US
dc.rightsThe following publication G. Gong, Y. Zhou, Q. Li, W. Zhao, S. Geng, H. Li, Y.-B. Leng, S. Zhu, G. Ding, Y. Zhai, Z. Lv, Y. Zhou, S.-T. Han, Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application. Adv. Mater. 2025, 2505420 is available at https://doi.org/10.1002/adma.202505420.en_US
dc.subjectBioinspired electronicsen_US
dc.subjectMemristoren_US
dc.subjectNeuromorphic transistoren_US
dc.subjectPiezoelectric and triboelectric sensorsen_US
dc.subjectSensory adaptationen_US
dc.titleBioinspired adaptive sensors : a review on current developments in theory and applicationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1002/adma.202505420-
dcterms.abstractThe human perception system features many dynamic functional mechanisms that efficiently process the large amount of sensory information available in the surrounding environment. In this system, sensory adaptation operates as a core mechanism that seamlessly filters familiar and inconsequential external stimuli at sensory endpoints. Such adaptive filtering minimizes redundant data movement between sensory terminals and cortical processing units and contributes to a lower communication bandwidth requirement and lower energy consumption at the system level. Recreating the behavior of sensory adaptation using electronic devices has garnered significant research interest owing to its promising prospects in next-generation intelligent perception platforms. Herein, the recent progress in bioinspired adaptive device engineering is systematically examined, and its valuable applications in electronic skins, wearable electronics, and machine vision are highlighted. The rapid development of bioinspired adaptive sensors can be attributed not only to the recent advances in emerging neuromorphic electronic elements, including piezoelectric and triboelectric sensors, memristive devices, and neuromorphic transistors, but also to the improved understanding of biological sensory adaptation. Existing challenges hindering device performance optimization, multimodal adaptive sensor development, and system-level integration are also discussed, providing insights for the development of high-performance neuromorphic sensing systems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced materials, First published: 30 June 2025, Early View, 2505420, https://doi.org/10.1002/adma.202505420-
dcterms.isPartOfAdvanced materials-
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105009438881-
dc.identifier.eissn1521-4095-
dc.identifier.artn2505420-
dc.description.validate202510 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TAen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextG.G. and Y.Z. contributed equally to this study. S.-T.H. acknowledges financial support from the Hong Kong Research Grants Council, Young Collaborative Research Grant (C5001-24Y), Research Institute for Smart Energy, and Guangdong Provincial Department of Science and Technology (2024B1515040002). Y. Zhou acknowledges grants from RSC Sustainable Laboratories Grant (L24-8215098370), Guangdong Basic and Applied Basic Research Foundation (2023A1515012479), the Science and Technology Innovation Commission of Shenzhen (JCYJ20220818100206013), RSC Researcher Collaborations Grant (C23-2422436283), State Key Laboratory of Radio Frequency Heterogeneous Integration (Independent Scientific Research Program No. 2024010), and NTUT-SZU Joint Research Program. This work was also supported by the National Natural Science Foundation of China (52373248), Guangdong Provincial Department of Science and Technology (2024A1515010006 and 2024A1515011718), Guangdong Basic and Applied Basic Research Foundation (2023A1515012479 and 2025A1515011274), and Science and Technology Innovation Commission of Shenzhen (JCYJ20230808105900001, JCYJ20220531102214032, and 20231123155543001).en_US
dc.description.pubStatusEarly releaseen_US
dc.description.TAWiley (2025)en_US
dc.description.oaCategoryTAen_US
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