Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems
In this article, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO 2 (150 nm) heterogeneously integrated onto fluorine doped tin oxide (FTO)/glass for forming-free memristor-based neuromorphic applications. The fabricated Al/CuCrO 2 /FTO memristors demonstrate a reliable bi...
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creator | Boppidi, Pavan Kumar Reddy Suresh, Bharathwaj Zhussupbekova, Ainur Biswas, Pranab Mullarkey, Daragh Raj, P. Michael Preetam Shvets, Igor V. Kundu, Souvik |
description | In this article, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO 2 (150 nm) heterogeneously integrated onto fluorine doped tin oxide (FTO)/glass for forming-free memristor-based neuromorphic applications. The fabricated Al/CuCrO 2 /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 10 6 s, which demonstrates its nonvolatility. The current-voltage ( {I} - {V} ) characteristics were fit 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 analogous to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and long-term 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 toward 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. |
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Michael Preetam ; Shvets, Igor V. ; Kundu, Souvik</creator><creatorcontrib>Boppidi, Pavan Kumar Reddy ; Suresh, Bharathwaj ; Zhussupbekova, Ainur ; Biswas, Pranab ; Mullarkey, Daragh ; Raj, P. Michael Preetam ; Shvets, Igor V. ; Kundu, Souvik</creatorcontrib><description><![CDATA[In this article, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO 2 (150 nm) heterogeneously integrated onto fluorine doped tin oxide (FTO)/glass for forming-free memristor-based neuromorphic applications. The fabricated Al/CuCrO 2 /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 10 6 s, which demonstrates its nonvolatility. The current-voltage (<inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula>) characteristics were fit 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 <inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula> behavior was analogous to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and long-term 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 toward 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.]]></description><identifier>ISSN: 0018-9383</identifier><identifier>EISSN: 1557-9646</identifier><identifier>DOI: 10.1109/TED.2020.2999324</identifier><identifier>CODEN: IETDAI</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Biological neural networks ; Biomimetics ; Computer simulation ; CuCrO ; Electrodes ; Fluorine ; Memristors ; Neural networks ; Neuromorphics ; Neurons ; Pulse amplitude ; Resistance ; resistive switching (RS) ; spike rate-dependent plasticity (SRDP) ; Spikes ; Switches ; Switching ; synapse ; Synapses ; Tin oxides ; Transport properties</subject><ispartof>IEEE transactions on electron devices, 2020-08, Vol.67 (8), p.3451-3458</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-2895-4944 ; 0000-0001-5815-8765 ; 0000-0001-5932-1739 ; 0000-0003-2724-8762</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9118968$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9118968$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Boppidi, Pavan Kumar Reddy</creatorcontrib><creatorcontrib>Suresh, Bharathwaj</creatorcontrib><creatorcontrib>Zhussupbekova, Ainur</creatorcontrib><creatorcontrib>Biswas, Pranab</creatorcontrib><creatorcontrib>Mullarkey, Daragh</creatorcontrib><creatorcontrib>Raj, P. Michael Preetam</creatorcontrib><creatorcontrib>Shvets, Igor V.</creatorcontrib><creatorcontrib>Kundu, Souvik</creatorcontrib><title>Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems</title><title>IEEE transactions on electron devices</title><addtitle>TED</addtitle><description><![CDATA[In this article, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO 2 (150 nm) heterogeneously integrated onto fluorine doped tin oxide (FTO)/glass for forming-free memristor-based neuromorphic applications. The fabricated Al/CuCrO 2 /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 10 6 s, which demonstrates its nonvolatility. The current-voltage (<inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula>) characteristics were fit 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 <inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula> behavior was analogous to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and long-term 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 toward 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.]]></description><subject>Biological neural networks</subject><subject>Biomimetics</subject><subject>Computer simulation</subject><subject>CuCrO</subject><subject>Electrodes</subject><subject>Fluorine</subject><subject>Memristors</subject><subject>Neural networks</subject><subject>Neuromorphics</subject><subject>Neurons</subject><subject>Pulse amplitude</subject><subject>Resistance</subject><subject>resistive switching (RS)</subject><subject>spike rate-dependent plasticity (SRDP)</subject><subject>Spikes</subject><subject>Switches</subject><subject>Switching</subject><subject>synapse</subject><subject>Synapses</subject><subject>Tin oxides</subject><subject>Transport properties</subject><issn>0018-9383</issn><issn>1557-9646</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNotz8tLw0AQBvBFFKzVu-BlwXPqvpLsHiWtD6hW2noOm2RitzYPdzeWXvzbXamH4WPgxzcMQteUTCgl6m49m04YYWTClFKciRM0onGcRioRySkaEUJlpLjk5-jCuW1YEyHYCP3M6tqUBlqPl-CM8-Yb8GpvfLkx7QfWbYVXvfkEvNQe8BR6aKs__LbTwZbGH7BpscavsMfZkNkFwy_Q2FDUWVyHCXBwpthBIIPtms72G1Pi1cF5aNwlOqv1zsHVf47R-8NsnT1F88Xjc3Y_jwxNYx8BlcCKKq4qqmsKIWQlSxA8PBseK4CIghIRyyqlguuESCK11jGIuE55WfAxuj329rb7GsD5fNsNtg0ncyZYmjAiRRrUzVEZAMh7axptD7miVKpE8l8mQGr2</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Boppidi, Pavan Kumar Reddy</creator><creator>Suresh, Bharathwaj</creator><creator>Zhussupbekova, Ainur</creator><creator>Biswas, Pranab</creator><creator>Mullarkey, Daragh</creator><creator>Raj, P. Michael Preetam</creator><creator>Shvets, Igor V.</creator><creator>Kundu, Souvik</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-2895-4944</orcidid><orcidid>https://orcid.org/0000-0001-5815-8765</orcidid><orcidid>https://orcid.org/0000-0001-5932-1739</orcidid><orcidid>https://orcid.org/0000-0003-2724-8762</orcidid></search><sort><creationdate>20200801</creationdate><title>Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems</title><author>Boppidi, Pavan Kumar Reddy ; Suresh, Bharathwaj ; Zhussupbekova, Ainur ; Biswas, Pranab ; Mullarkey, Daragh ; Raj, P. 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Michael Preetam</creatorcontrib><creatorcontrib>Shvets, Igor V.</creatorcontrib><creatorcontrib>Kundu, Souvik</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on electron devices</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Boppidi, Pavan Kumar Reddy</au><au>Suresh, Bharathwaj</au><au>Zhussupbekova, Ainur</au><au>Biswas, Pranab</au><au>Mullarkey, Daragh</au><au>Raj, P. Michael Preetam</au><au>Shvets, Igor V.</au><au>Kundu, Souvik</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems</atitle><jtitle>IEEE transactions on electron devices</jtitle><stitle>TED</stitle><date>2020-08-01</date><risdate>2020</risdate><volume>67</volume><issue>8</issue><spage>3451</spage><epage>3458</epage><pages>3451-3458</pages><issn>0018-9383</issn><eissn>1557-9646</eissn><coden>IETDAI</coden><abstract><![CDATA[In this article, we introduce a new class of p-type transparent conductive oxide (TCO) CuCrO 2 (150 nm) heterogeneously integrated onto fluorine doped tin oxide (FTO)/glass for forming-free memristor-based neuromorphic applications. The fabricated Al/CuCrO 2 /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 10 6 s, which demonstrates its nonvolatility. The current-voltage (<inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula>) characteristics were fit 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 <inline-formula> <tex-math notation="LaTeX">{I} </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula> behavior was analogous to the experimental one. Efforts were then devoted to observe long-term potentiation (LTP) and long-term 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 toward 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.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TED.2020.2999324</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-2895-4944</orcidid><orcidid>https://orcid.org/0000-0001-5815-8765</orcidid><orcidid>https://orcid.org/0000-0001-5932-1739</orcidid><orcidid>https://orcid.org/0000-0003-2724-8762</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Biological neural networks Biomimetics Computer simulation CuCrO Electrodes Fluorine Memristors Neural networks Neuromorphics Neurons Pulse amplitude Resistance resistive switching (RS) spike rate-dependent plasticity (SRDP) Spikes Switches Switching synapse Synapses Tin oxides Transport properties |
title | Efficient Resistive Switching and Spike Rate Dependent Plasticity in a New CuCrO2 Memristor for Plausible Neuromorphic Systems |
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