Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108252
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dc.contributorDepartment of Applied Biology and Chemical Technologyen_US
dc.creatorLv, Zen_US
dc.creatorZhu, Sen_US
dc.creatorWang, Yen_US
dc.creatorRen, Yen_US
dc.creatorLuo, Men_US
dc.creatorWang, Hen_US
dc.creatorZhang, Gen_US
dc.creatorZhai, Yen_US
dc.creatorZhao, Sen_US
dc.creatorZhou, Yen_US
dc.creatorJiang, Men_US
dc.creatorLeng, YBen_US
dc.creatorHan, STen_US
dc.date.accessioned2024-07-30T03:13:11Z-
dc.date.available2024-07-30T03:13:11Z-
dc.identifier.issn0935-9648en_US
dc.identifier.urihttp://hdl.handle.net/10397/108252-
dc.language.isoenen_US
dc.publisherWiley-VCHen_US
dc.rights© 2024 The Author(s). Advanced Materials published by Wiley-VCHGmbH. This is an open access article under the terms of the Creative Commons Attribution-Non Commercial-NoDerivs License (https://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 Z. Lv, S. Zhu, Y. Wang, Y. Ren, M. Luo, H. Wang, G. Zhang, Y. Zhai, S. Zhao, Y. Zhou, M. Jiang, Y.-B. Leng, S.-T. Han, Development of Bio-Voltage Operated Humidity-Sensory Neurons Comprising Self-Assembled Peptide Memristors. Adv. Mater. 2024, 36, 2405145 is available at https://doi.org/10.1002/adma.202405145.en_US
dc.subjectArtificial neuronen_US
dc.subjectHumidity-dependent modulationen_US
dc.subjectNeuromorphic perceptionen_US
dc.subjectPeptide memristoren_US
dc.subjectSelf-assembled nanowireen_US
dc.titleDevelopment of bio-voltage operated humidity-sensory neurons comprising self-assembled peptide memristorsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume36en_US
dc.identifier.issue33en_US
dc.identifier.doi10.1002/adma.202405145en_US
dcterms.abstractBiomimetic humidity sensors offer a low-power approach for respiratory monitoring in early lung-disease diagnosis. However, balancing miniaturization and energy efficiency remains challenging. This study addresses this issue by introducing a bioinspired humidity-sensing neuron comprising a self-assembled peptide nanowire (NW) memristor with unique proton-coupled ion transport. The proposed neuron shows a low Ag+ activation energy owing to the NW and redox activity of the tyrosine (Tyr)-rich peptide in the system, facilitating ultralow electric-field–driven threshold switching and a high energy efficiency. Additionally, Ag+ migration in the system can be controlled by a proton source owing to the hydrophilic nature of the phenolic hydroxyl group in Tyr, enabling the humidity-based control of the conductance state of the memristor. Furthermore, a memristor-based neuromorphic perception neuron that can encode humidity signals into spikes is proposed. The spiking characteristics of this neuron can be modulated to emulate the strength-modulated spike-frequency characteristics of biological neurons. A three-layer spiking neural network with input neurons comprising these highly tunable humidity perception neurons shows an accuracy of 92.68% in lung-disease diagnosis. This study paves the way for developing bioinspired self-assembly strategies to construct neuromorphic perception systems, bridging the gap between artificial and biological sensing and processing paradigms.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced materials, 2024, 15 Aug. 2024, v. 36, no. 33, 2405145en_US
dcterms.isPartOfAdvanced materialsen_US
dcterms.issued2024-08-15-
dc.identifier.scopus2-s2.0-85197155709-
dc.identifier.eissn1521-4095en_US
dc.identifier.artn2405145en_US
dc.description.validate202407 bcwhen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextScience, Technology and Innovation Commission of Shenzhen Municipality; Guangdong Provincial Department of Science and Technology; NSFCen_US
dc.description.pubStatusPublisheden_US
dc.description.TAWiley (2024)en_US
dc.description.oaCategoryTAen_US
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