Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161240
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dc.contributor.authorHe, Yonglien_US
dc.contributor.authorJiang, Shanshanen_US
dc.contributor.authorChen, Chunshengen_US
dc.contributor.authorWan, Changjinen_US
dc.contributor.authorShi, Yien_US
dc.contributor.authorWan, Qingen_US
dc.date.accessioned2022-08-22T05:28:58Z-
dc.date.available2022-08-22T05:28:58Z-
dc.date.issued2021-
dc.identifier.citationHe, Y., Jiang, S., Chen, C., Wan, C., Shi, Y. & Wan, Q. (2021). Electrolyte-gated neuromorphic transistors for brain-like dynamic computing. Journal of Applied Physics, 130(19), 190904-. https://dx.doi.org/10.1063/5.0069456en_US
dc.identifier.issn0021-8979en_US
dc.identifier.urihttps://hdl.handle.net/10356/161240-
dc.description.abstractIn recent years, the rapid increase in the data volume to be processed has led to urgent requirements for highly efficient computing paradigms. Brain-like computing that mimics the way the biological brain processes information has attracted growing interest due to extremely high energy efficiency. Particularly, dynamics play an essential role in neural spike information processing. Here, we offer a brief review and perspective in the field of electrolyte-gated neuromorphic transistors for brain-like dynamic computing. We first introduce the biological foundation of dynamic neural functions. Then dynamic synaptic plasticity, dynamic dendritic integration, dynamic neural functions, and bio-inspired somatosensory systems realized based on the electrolyte-gated neuromorphic transistors are presented. At last, conclusions and perspectives are given.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Applied Physicsen_US
dc.rights© 2021 Author(s). All rights reserved. This paper was published by AIP Publishing in Journal of Applied Physics and is made available with permission of Author(s).en_US
dc.subjectEngineering::Materialsen_US
dc.titleElectrolyte-gated neuromorphic transistors for brain-like dynamic computingen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Materials Science and Engineeringen_US
dc.identifier.doi10.1063/5.0069456-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85120382343-
dc.identifier.issue19en_US
dc.identifier.volume130en_US
dc.identifier.spage190904en_US
dc.subject.keywordsBiomimeticsen_US
dc.subject.keywordsComputing Paradigmen_US
dc.description.acknowledgementThe authors acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 61921005 and 61834001) and the National Key R&D Program of China (Grant No. 2019YFB2205400).en_US
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