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dc.contributor.authorCaffrey, Daviden
dc.contributor.authorShvets, Igoren
dc.date.accessioned2021-01-15T17:06:46Z
dc.date.available2021-01-15T17:06:46Z
dc.date.issued2020en
dc.date.submitted2020en
dc.identifier.citationP. K. R. Boppidi, B. Suresh, A. Zhussupbekova, P. Biswas, D. Mullarkey, P. M. P. Raj, I. V. Shvets, S. Kundu, Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems, IEEE Transactions on Electron Devices, 67, 8, 2020, 3451 - 3458en
dc.identifier.issn1557-9646en
dc.identifier.otherYen
dc.descriptionPUBLISHEDen
dc.description.abstractIn this work, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO2 (150 nm) heterogeneously integrated onto FTO/glass for forming free memristor based neuromorphic applications. The fabricated Al/CuCrO2/FTO memristors demonstrate a reliable bipolar resistive switching with an ON/OFF ratio of 1000. The retention of the device was found to be steady even beyond 106 s, which demonstrates its non-volatility. The current-voltage (I-V) characteristics were fitted to evaluate its transport properties and a band-diagram was projected to have a better insight of the device operational principles. To validate the experimental observations, a new model has been developed, and the simulated I-V behavior was analogues to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and longterm depression (LTD) utilizing identical but opposite pulses to evaluate the device’s efficacy for synaptic applications. The synaptic behavior was well controlled by the pulse (pulse amplitude and width) variations. The conductance change was found to be symmetric and then saturated, which reflects the popular biological Hebbian rules. Finally, a long-term synaptic modulation has been implemented by establishing the spike rate dependent plasticity (SRDP) rule, which is a part of spiking neural networks and advantageous to mimic the brain’s capability at low power. All the obtained experimental results were systematically corroborated by neural network simulation. Overall, our approach provides a new road map towards the development of TCO based alternative memristors, which can be employed to mimic the synaptic plasticity for energy-efficient bioinspired neuromorphic systems and non-Von Neumann computer architectures.en
dc.description.sponsorshipBRNS, DAE, Govt. of India (project No. 34/14/11/2017-BRNS/34286) Science Foundation Ireland under grant no.12/IA/1264 Irish Research Council (IRCGOIPD/2017/1275)en
dc.format.extent3451en
dc.format.extent3458en
dc.language.isoenen
dc.relation.ispartofseriesIEEE Transactions on Electron Devicesen
dc.relation.ispartofseries67en
dc.relation.ispartofseries8en
dc.rightsYen
dc.subjectMaterials scienceen
dc.subjectCuCrOen
dc.subjectMemristoren
dc.titleEfficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systemsen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/caffredaen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/ivchvetsen
dc.identifier.rssinternalid222693en
dc.identifier.doihttp://dx.doi.org/10.1109/TED.2020.2999324en
dc.rights.ecaccessrightsopenAccess
dc.identifier.urihttps://ieeexplore.ieee.org/document/9118968
dc.identifier.urihttp://hdl.handle.net/2262/94691


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