Designing carbon conductive filament memristor devices for memory and electronic synapse applications
Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices...
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Veröffentlicht in: | Materials horizons 2020-04, Vol.7 (4), p.116-1114 |
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description | Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices have increasingly attracted attention due to their excellent functional properties in plasticity and as memristors. However, the randomly dynamic process of nucleation during device fabrication results in nonuniform switching parameters. Here, we demonstrate the viability of a high-performance neuromorphic memristor device based on a carbon conductive filament mechanism, with the advantages of high switching stability and low power consumption. The memristor is also able to emulate faithfully different functions of artificial synapses, including paired-pulse facilitation (PPF) and spike-timing-dependent plasticity (STDP). According to detailed electron energy loss spectroscopy (EELS) and transmission electron microscopy (TEM) characterization, it is confirmed that carbon conductive filaments are formed in aluminum nitride (AlN) films comprising the middle layer of the memristor. First principles calculations provide insight into the energetics of defects involved in the diffusion of carbon atoms into the AlN film. This work probes the viability of a new physical conduction mechanism for use in neuromorphic memristor performance, with evidence of improved device performance.
Utilizing the instability of the edge atoms of graphene defects, carbon conductive filaments were formed under the regulation of the electric field and the synaptic function was achieved. |
doi_str_mv | 10.1039/c9mh01684h |
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Utilizing the instability of the edge atoms of graphene defects, carbon conductive filaments were formed under the regulation of the electric field and the synaptic function was achieved.</description><identifier>ISSN: 2051-6347</identifier><identifier>EISSN: 2051-6355</identifier><identifier>DOI: 10.1039/c9mh01684h</identifier><language>eng</language><publisher>Cambridge: Royal Society of Chemistry</publisher><subject>Aluminum nitride ; Carbon ; Computer simulation ; Conductivity ; Copper ; Diffusion ; Electron energy loss spectroscopy ; Electronic devices ; Energy dissipation ; Filaments ; First principles ; Mathematical analysis ; Memory devices ; Memristors ; Nucleation ; Plastic properties ; Power consumption ; Silver ; Switching ; Synapses ; Viability</subject><ispartof>Materials horizons, 2020-04, Vol.7 (4), p.116-1114</ispartof><rights>Copyright Royal Society of Chemistry 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c344t-be06b9047c6b4842888179cf7139a6f159d7fbfb1878599760856826967656273</citedby><cites>FETCH-LOGICAL-c344t-be06b9047c6b4842888179cf7139a6f159d7fbfb1878599760856826967656273</cites><orcidid>0000-0003-3188-2803 ; 0000-0002-3266-515X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Zhou, Zhenyu</creatorcontrib><creatorcontrib>Zhao, Jianhui</creatorcontrib><creatorcontrib>Chen, Andy Paul</creatorcontrib><creatorcontrib>Pei, Yifei</creatorcontrib><creatorcontrib>Xiao, Zuoao</creatorcontrib><creatorcontrib>Wang, Gong</creatorcontrib><creatorcontrib>Chen, Jingsheng</creatorcontrib><creatorcontrib>Fu, Guangsheng</creatorcontrib><creatorcontrib>Yan, Xiaobing</creatorcontrib><title>Designing carbon conductive filament memristor devices for memory and electronic synapse applications</title><title>Materials horizons</title><description>Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices have increasingly attracted attention due to their excellent functional properties in plasticity and as memristors. However, the randomly dynamic process of nucleation during device fabrication results in nonuniform switching parameters. Here, we demonstrate the viability of a high-performance neuromorphic memristor device based on a carbon conductive filament mechanism, with the advantages of high switching stability and low power consumption. The memristor is also able to emulate faithfully different functions of artificial synapses, including paired-pulse facilitation (PPF) and spike-timing-dependent plasticity (STDP). According to detailed electron energy loss spectroscopy (EELS) and transmission electron microscopy (TEM) characterization, it is confirmed that carbon conductive filaments are formed in aluminum nitride (AlN) films comprising the middle layer of the memristor. First principles calculations provide insight into the energetics of defects involved in the diffusion of carbon atoms into the AlN film. This work probes the viability of a new physical conduction mechanism for use in neuromorphic memristor performance, with evidence of improved device performance.
Utilizing the instability of the edge atoms of graphene defects, carbon conductive filaments were formed under the regulation of the electric field and the synaptic function was achieved.</description><subject>Aluminum nitride</subject><subject>Carbon</subject><subject>Computer simulation</subject><subject>Conductivity</subject><subject>Copper</subject><subject>Diffusion</subject><subject>Electron energy loss spectroscopy</subject><subject>Electronic devices</subject><subject>Energy dissipation</subject><subject>Filaments</subject><subject>First principles</subject><subject>Mathematical analysis</subject><subject>Memory devices</subject><subject>Memristors</subject><subject>Nucleation</subject><subject>Plastic properties</subject><subject>Power consumption</subject><subject>Silver</subject><subject>Switching</subject><subject>Synapses</subject><subject>Viability</subject><issn>2051-6347</issn><issn>2051-6355</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kM1LAzEQxYMoWGov3oWIN2E12XwfpX5UqHjR85LNJm3KbrImW6H_vauVevMy85j3Y4Z5AJxjdIMRUbdGdWuEuaTrIzApEcMFJ4wdHzQVp2CW8wYhhAllSKIJsPc2-1XwYQWNTnUM0MTQbM3gPy10vtWdDQPsbJd8HmKCjf30xmboRj1OY9pBHRpoW2uGFIM3MO-C7rOFuu9bb_TgY8hn4MTpNtvZb5-C98eHt_miWL4-Pc_vloUhlA5FbRGvFaLC8JpKWkopsVDGCUyU5g4z1QhXuxpLIZlSgiPJuCy54oIzXgoyBVf7vX2KH1ubh2oTtymMJ6uSSD5-TccyBdd7yqSYc7Ku6pPvdNpVGFXfSVZz9bL4SXIxwhd7OGVz4P6SHv3L__yqbxz5AhfAe2Y</recordid><startdate>20200406</startdate><enddate>20200406</enddate><creator>Zhou, Zhenyu</creator><creator>Zhao, Jianhui</creator><creator>Chen, Andy Paul</creator><creator>Pei, Yifei</creator><creator>Xiao, Zuoao</creator><creator>Wang, Gong</creator><creator>Chen, Jingsheng</creator><creator>Fu, Guangsheng</creator><creator>Yan, Xiaobing</creator><general>Royal Society of Chemistry</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JG9</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-3188-2803</orcidid><orcidid>https://orcid.org/0000-0002-3266-515X</orcidid></search><sort><creationdate>20200406</creationdate><title>Designing carbon conductive filament memristor devices for memory and electronic synapse applications</title><author>Zhou, Zhenyu ; Zhao, Jianhui ; Chen, Andy Paul ; Pei, Yifei ; Xiao, Zuoao ; Wang, Gong ; Chen, Jingsheng ; Fu, Guangsheng ; Yan, Xiaobing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c344t-be06b9047c6b4842888179cf7139a6f159d7fbfb1878599760856826967656273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aluminum nitride</topic><topic>Carbon</topic><topic>Computer simulation</topic><topic>Conductivity</topic><topic>Copper</topic><topic>Diffusion</topic><topic>Electron energy loss spectroscopy</topic><topic>Electronic devices</topic><topic>Energy dissipation</topic><topic>Filaments</topic><topic>First principles</topic><topic>Mathematical analysis</topic><topic>Memory devices</topic><topic>Memristors</topic><topic>Nucleation</topic><topic>Plastic properties</topic><topic>Power consumption</topic><topic>Silver</topic><topic>Switching</topic><topic>Synapses</topic><topic>Viability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Zhenyu</creatorcontrib><creatorcontrib>Zhao, Jianhui</creatorcontrib><creatorcontrib>Chen, Andy Paul</creatorcontrib><creatorcontrib>Pei, Yifei</creatorcontrib><creatorcontrib>Xiao, Zuoao</creatorcontrib><creatorcontrib>Wang, Gong</creatorcontrib><creatorcontrib>Chen, Jingsheng</creatorcontrib><creatorcontrib>Fu, Guangsheng</creatorcontrib><creatorcontrib>Yan, Xiaobing</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Materials horizons</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Zhenyu</au><au>Zhao, Jianhui</au><au>Chen, Andy Paul</au><au>Pei, Yifei</au><au>Xiao, Zuoao</au><au>Wang, Gong</au><au>Chen, Jingsheng</au><au>Fu, Guangsheng</au><au>Yan, Xiaobing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Designing carbon conductive filament memristor devices for memory and electronic synapse applications</atitle><jtitle>Materials horizons</jtitle><date>2020-04-06</date><risdate>2020</risdate><volume>7</volume><issue>4</issue><spage>116</spage><epage>1114</epage><pages>116-1114</pages><issn>2051-6347</issn><eissn>2051-6355</eissn><abstract>Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices have increasingly attracted attention due to their excellent functional properties in plasticity and as memristors. However, the randomly dynamic process of nucleation during device fabrication results in nonuniform switching parameters. Here, we demonstrate the viability of a high-performance neuromorphic memristor device based on a carbon conductive filament mechanism, with the advantages of high switching stability and low power consumption. The memristor is also able to emulate faithfully different functions of artificial synapses, including paired-pulse facilitation (PPF) and spike-timing-dependent plasticity (STDP). According to detailed electron energy loss spectroscopy (EELS) and transmission electron microscopy (TEM) characterization, it is confirmed that carbon conductive filaments are formed in aluminum nitride (AlN) films comprising the middle layer of the memristor. First principles calculations provide insight into the energetics of defects involved in the diffusion of carbon atoms into the AlN film. This work probes the viability of a new physical conduction mechanism for use in neuromorphic memristor performance, with evidence of improved device performance.
Utilizing the instability of the edge atoms of graphene defects, carbon conductive filaments were formed under the regulation of the electric field and the synaptic function was achieved.</abstract><cop>Cambridge</cop><pub>Royal Society of Chemistry</pub><doi>10.1039/c9mh01684h</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-3188-2803</orcidid><orcidid>https://orcid.org/0000-0002-3266-515X</orcidid></addata></record> |
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subjects | Aluminum nitride Carbon Computer simulation Conductivity Copper Diffusion Electron energy loss spectroscopy Electronic devices Energy dissipation Filaments First principles Mathematical analysis Memory devices Memristors Nucleation Plastic properties Power consumption Silver Switching Synapses Viability |
title | Designing carbon conductive filament memristor devices for memory and electronic synapse applications |
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