Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113038
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dc.contributorDepartment of Applied Biology and Chemical Technologyen_US
dc.creatorLi, Yen_US
dc.creatorDing, Gen_US
dc.creatorZhai, Yen_US
dc.creatorLv, Zen_US
dc.creatorYan, Yen_US
dc.creatorXue, Sen_US
dc.creatorZhou, Ken_US
dc.creatorZhang, Men_US
dc.creatorZhang, Yen_US
dc.creatorSun, QJen_US
dc.creatorLiu, Yen_US
dc.creatorRoy, VALen_US
dc.creatorZhou, Yen_US
dc.creatorHan, STen_US
dc.date.accessioned2025-05-19T00:52:00Z-
dc.date.available2025-05-19T00:52:00Z-
dc.identifier.issn1613-6810en_US
dc.identifier.urihttp://hdl.handle.net/10397/113038-
dc.language.isoenen_US
dc.publisherWiley-VCH Verlag GmbH & Co. KGaAen_US
dc.rights© 2025 The Author(s). Small published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.en_US
dc.rightsThe following publication Y. Li, G. Ding, Y. Zhai, Z. Lv, Y. Yan, S. Xue, K. Zhou, M. Zhang, Y. Zhang, Q.-J. Sun, Y. Liu, V. A. L. Roy, Y. Zhou, S.-T. Han, MXene-Based Flexible Memory and Neuromorphic Devices. Small 2025, 2410914 is available at https://doi.org/10.1002/smll.202410914.en_US
dc.subjectFlexible electronicsen_US
dc.subjectMemoryen_US
dc.subjectMXenesen_US
dc.subjectNeuromorphic computingen_US
dc.subjectSynaptic devicesen_US
dc.titleMXene-based flexible memory and neuromorphic devicesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1002/smll.202410914en_US
dcterms.abstractAs the age of the Internet of Things (IoTs) unfolds, along with the rapid advancement of artificial intelligence (AI), traditional von Neumann-based computing systems encounter significant challenges in handling vast amounts of data storage and processing. Bioinspired neuromorphic computing strategies offer a promising solution, characterized by features of in-memory computing, massively parallel processing, and event-driven operations. Compared to traditional rigid silicon-based devices, flexible neuromorphic devices are lightweight, thin, and highly stretchable, garnering considerable attention. Among the materials utilized in these devices, transition metal carbides/nitrides (MXenes) are particularly noteworthy materials with their excellent flexibility, exceptional conductivity, and hydrophilicity, which confer remarkable properties upon these devices. Herein, a comprehensive discussion is provided on the applications of MXenes in flexible memory and neuromorphic devices. This review covers the basic principles and device structures of memory and neuromorphic devices, common parameters and emerging materials of flexible devices, as well as the common synthesis, functionalization methods, and distinct properties of MXenes. The remaining challenges and future opportunities of MXenes in relevant devices are also presented. This review can serve as a valuable reference and lay a cornerstone for the practical and feasible implementation of MXenes in flexible memory and neuromorphic technologies.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSmall, First published: 31 January 2025, Early View, 2410914, https://doi.org/10.1002/smll.202410914en_US
dcterms.isPartOfSmallen_US
dcterms.issued2025-
dc.identifier.scopus2-s2.0-85216482108-
dc.identifier.eissn1613-6829en_US
dc.identifier.artn2410914en_US
dc.description.validate202505 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS, OA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe National Natural Science Foundation of China (Grant No. 62304137, 62122055, and 62074104); the Guangdong Basic and Applied Basic Research Foundation (Grant Nos. 2023A1515012479, 2024A1515011737, 2024A1515010006, and 2024B1515040002); the Science and Technology Innovation Commission of Shenzhen (Grant No. JCYJ20220818100206013); the RSC Researcher Collaborations Grant (Grant No. C23-2422436283); the State Key Laboratory of Radio Frequency Heterogeneous Integration (Independent Scientific Research Program No. 2024010); the NTUT-SZU Joint Research Programen_US
dc.description.pubStatusEarly releaseen_US
dc.description.TAWiley (2025)en_US
dc.description.oaCategoryTAen_US
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