Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing

Future‐generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by colocating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high‐fidelity neuronal emulation, the pred...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Weinheim) 2023-09, Vol.35 (37), p.e2205294-e2205294
Hauptverfasser: Schofield, Parker, Bradicich, Adelaide, Gurrola, Rebeca M, Zhang, Yuwei, Brown, Timothy D, Pharr, Matt, Shamberger, Patrick J, Banerjee, Sarbajit
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page e2205294
container_issue 37
container_start_page e2205294
container_title Advanced materials (Weinheim)
container_volume 35
creator Schofield, Parker
Bradicich, Adelaide
Gurrola, Rebeca M
Zhang, Yuwei
Brown, Timothy D
Pharr, Matt
Shamberger, Patrick J
Banerjee, Sarbajit
description Future‐generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by colocating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high‐fidelity neuronal emulation, the predictive design of neuromorphic circuits starting from knowledge of material transformations remains challenging. VO2 is an attractive candidate since it manifests a near‐room‐temperature, discontinuous, and hysteretic metal–insulator transition. The transition provides a nonlinear dynamical response to input signals, as needed to construct neuronal circuit elements. Strategies for tuning the transformation characteristics of VO2 based on modification of material properties, interfacial structure, and field couplings, are discussed. Dynamical modulation of transformation characteristics through in situ processing is discussed as a means of imbuing synaptic function. Mechanistic understanding of site‐selective modification; external, epitaxial, and chemical strain; defect dynamics; and interfacial field coupling in modifying local atomistic structure, the implications therein for electronic structure, and ultimately, the tuning of transformation characteristics, is emphasized. Opportunities are highlighted for inverse design and for using design principles related to thermodynamics and kinetics of electronic transitions learned from VO2 to inform the design of new Mott materials, as well as to go beyond energy‐efficient computation to manifest intelligence.
doi_str_mv 10.1002/adma.202205294
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_miscellaneous_2707875164</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2707875164</sourcerecordid><originalsourceid>FETCH-LOGICAL-j322t-53b52c6891e6a9e4feef42240419e46ff2a7cbf012336de10ee07950f14714263</originalsourceid><addsrcrecordid>eNpdjr1OwzAUhS0EEqWwMltiYUm5vv5JPKIKaKVCl8Iauek1TZXYJU523oE35EmIBBNnOTrSp0-HsWsBMwGAd27XuhkCImi06oRNhEaRKbD6lE3ASp1Zo4pzdpHSAQCsATNhq4XrAqVUh3fe74k_U--a78-vZUhD4_rY8U3nQqr7OgYePX9bI68Df6Ghi23sjvu64vPYHod-NFyyM--aRFd_PWWvjw-b-SJbrZ-W8_tVdpCIfablVmNlCivIOEvKE3mFqECJcRnv0eXV1oNAKc2OBBBBbjV4oXKh0Mgpu_31Hrv4MVDqy7ZOFTWNCxSHVGIOeZFrYdSI3vxDD3HowviuxMKoMVIZ-QO0rV3m</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2864444346</pqid></control><display><type>article</type><title>Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Schofield, Parker ; Bradicich, Adelaide ; Gurrola, Rebeca M ; Zhang, Yuwei ; Brown, Timothy D ; Pharr, Matt ; Shamberger, Patrick J ; Banerjee, Sarbajit</creator><creatorcontrib>Schofield, Parker ; Bradicich, Adelaide ; Gurrola, Rebeca M ; Zhang, Yuwei ; Brown, Timothy D ; Pharr, Matt ; Shamberger, Patrick J ; Banerjee, Sarbajit</creatorcontrib><description>Future‐generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by colocating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high‐fidelity neuronal emulation, the predictive design of neuromorphic circuits starting from knowledge of material transformations remains challenging. VO2 is an attractive candidate since it manifests a near‐room‐temperature, discontinuous, and hysteretic metal–insulator transition. The transition provides a nonlinear dynamical response to input signals, as needed to construct neuronal circuit elements. Strategies for tuning the transformation characteristics of VO2 based on modification of material properties, interfacial structure, and field couplings, are discussed. Dynamical modulation of transformation characteristics through in situ processing is discussed as a means of imbuing synaptic function. Mechanistic understanding of site‐selective modification; external, epitaxial, and chemical strain; defect dynamics; and interfacial field coupling in modifying local atomistic structure, the implications therein for electronic structure, and ultimately, the tuning of transformation characteristics, is emphasized. Opportunities are highlighted for inverse design and for using design principles related to thermodynamics and kinetics of electronic transitions learned from VO2 to inform the design of new Mott materials, as well as to go beyond energy‐efficient computation to manifest intelligence.</description><identifier>ISSN: 0935-9648</identifier><identifier>EISSN: 1521-4095</identifier><identifier>DOI: 10.1002/adma.202205294</identifier><language>eng</language><publisher>Weinheim: Wiley Subscription Services, Inc</publisher><subject>Circuit design ; Couplings ; Electronic structure ; Inverse design ; Material properties ; Materials science ; Metal-insulator transition ; Neuromorphic computing ; Nonlinear response ; Synapses ; Transformations (mathematics) ; Tuning ; Vanadium oxides</subject><ispartof>Advanced materials (Weinheim), 2023-09, Vol.35 (37), p.e2205294-e2205294</ispartof><rights>2023 Wiley‐VCH GmbH</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></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>Schofield, Parker</creatorcontrib><creatorcontrib>Bradicich, Adelaide</creatorcontrib><creatorcontrib>Gurrola, Rebeca M</creatorcontrib><creatorcontrib>Zhang, Yuwei</creatorcontrib><creatorcontrib>Brown, Timothy D</creatorcontrib><creatorcontrib>Pharr, Matt</creatorcontrib><creatorcontrib>Shamberger, Patrick J</creatorcontrib><creatorcontrib>Banerjee, Sarbajit</creatorcontrib><title>Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing</title><title>Advanced materials (Weinheim)</title><description>Future‐generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by colocating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high‐fidelity neuronal emulation, the predictive design of neuromorphic circuits starting from knowledge of material transformations remains challenging. VO2 is an attractive candidate since it manifests a near‐room‐temperature, discontinuous, and hysteretic metal–insulator transition. The transition provides a nonlinear dynamical response to input signals, as needed to construct neuronal circuit elements. Strategies for tuning the transformation characteristics of VO2 based on modification of material properties, interfacial structure, and field couplings, are discussed. Dynamical modulation of transformation characteristics through in situ processing is discussed as a means of imbuing synaptic function. Mechanistic understanding of site‐selective modification; external, epitaxial, and chemical strain; defect dynamics; and interfacial field coupling in modifying local atomistic structure, the implications therein for electronic structure, and ultimately, the tuning of transformation characteristics, is emphasized. Opportunities are highlighted for inverse design and for using design principles related to thermodynamics and kinetics of electronic transitions learned from VO2 to inform the design of new Mott materials, as well as to go beyond energy‐efficient computation to manifest intelligence.</description><subject>Circuit design</subject><subject>Couplings</subject><subject>Electronic structure</subject><subject>Inverse design</subject><subject>Material properties</subject><subject>Materials science</subject><subject>Metal-insulator transition</subject><subject>Neuromorphic computing</subject><subject>Nonlinear response</subject><subject>Synapses</subject><subject>Transformations (mathematics)</subject><subject>Tuning</subject><subject>Vanadium oxides</subject><issn>0935-9648</issn><issn>1521-4095</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpdjr1OwzAUhS0EEqWwMltiYUm5vv5JPKIKaKVCl8Iauek1TZXYJU523oE35EmIBBNnOTrSp0-HsWsBMwGAd27XuhkCImi06oRNhEaRKbD6lE3ASp1Zo4pzdpHSAQCsATNhq4XrAqVUh3fe74k_U--a78-vZUhD4_rY8U3nQqr7OgYePX9bI68Df6Ghi23sjvu64vPYHod-NFyyM--aRFd_PWWvjw-b-SJbrZ-W8_tVdpCIfablVmNlCivIOEvKE3mFqECJcRnv0eXV1oNAKc2OBBBBbjV4oXKh0Mgpu_31Hrv4MVDqy7ZOFTWNCxSHVGIOeZFrYdSI3vxDD3HowviuxMKoMVIZ-QO0rV3m</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Schofield, Parker</creator><creator>Bradicich, Adelaide</creator><creator>Gurrola, Rebeca M</creator><creator>Zhang, Yuwei</creator><creator>Brown, Timothy D</creator><creator>Pharr, Matt</creator><creator>Shamberger, Patrick J</creator><creator>Banerjee, Sarbajit</creator><general>Wiley Subscription Services, Inc</general><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>7X8</scope></search><sort><creationdate>20230901</creationdate><title>Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing</title><author>Schofield, Parker ; Bradicich, Adelaide ; Gurrola, Rebeca M ; Zhang, Yuwei ; Brown, Timothy D ; Pharr, Matt ; Shamberger, Patrick J ; Banerjee, Sarbajit</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j322t-53b52c6891e6a9e4feef42240419e46ff2a7cbf012336de10ee07950f14714263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Circuit design</topic><topic>Couplings</topic><topic>Electronic structure</topic><topic>Inverse design</topic><topic>Material properties</topic><topic>Materials science</topic><topic>Metal-insulator transition</topic><topic>Neuromorphic computing</topic><topic>Nonlinear response</topic><topic>Synapses</topic><topic>Transformations (mathematics)</topic><topic>Tuning</topic><topic>Vanadium oxides</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schofield, Parker</creatorcontrib><creatorcontrib>Bradicich, Adelaide</creatorcontrib><creatorcontrib>Gurrola, Rebeca M</creatorcontrib><creatorcontrib>Zhang, Yuwei</creatorcontrib><creatorcontrib>Brown, Timothy D</creatorcontrib><creatorcontrib>Pharr, Matt</creatorcontrib><creatorcontrib>Shamberger, Patrick J</creatorcontrib><creatorcontrib>Banerjee, Sarbajit</creatorcontrib><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>MEDLINE - Academic</collection><jtitle>Advanced materials (Weinheim)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schofield, Parker</au><au>Bradicich, Adelaide</au><au>Gurrola, Rebeca M</au><au>Zhang, Yuwei</au><au>Brown, Timothy D</au><au>Pharr, Matt</au><au>Shamberger, Patrick J</au><au>Banerjee, Sarbajit</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing</atitle><jtitle>Advanced materials (Weinheim)</jtitle><date>2023-09-01</date><risdate>2023</risdate><volume>35</volume><issue>37</issue><spage>e2205294</spage><epage>e2205294</epage><pages>e2205294-e2205294</pages><issn>0935-9648</issn><eissn>1521-4095</eissn><abstract>Future‐generation neuromorphic computing seeks to overcome the limitations of von Neumann architectures by colocating logic and memory functions, thereby emulating the function of neurons and synapses in the human brain. Despite remarkable demonstrations of high‐fidelity neuronal emulation, the predictive design of neuromorphic circuits starting from knowledge of material transformations remains challenging. VO2 is an attractive candidate since it manifests a near‐room‐temperature, discontinuous, and hysteretic metal–insulator transition. The transition provides a nonlinear dynamical response to input signals, as needed to construct neuronal circuit elements. Strategies for tuning the transformation characteristics of VO2 based on modification of material properties, interfacial structure, and field couplings, are discussed. Dynamical modulation of transformation characteristics through in situ processing is discussed as a means of imbuing synaptic function. Mechanistic understanding of site‐selective modification; external, epitaxial, and chemical strain; defect dynamics; and interfacial field coupling in modifying local atomistic structure, the implications therein for electronic structure, and ultimately, the tuning of transformation characteristics, is emphasized. Opportunities are highlighted for inverse design and for using design principles related to thermodynamics and kinetics of electronic transitions learned from VO2 to inform the design of new Mott materials, as well as to go beyond energy‐efficient computation to manifest intelligence.</abstract><cop>Weinheim</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/adma.202205294</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0935-9648
ispartof Advanced materials (Weinheim), 2023-09, Vol.35 (37), p.e2205294-e2205294
issn 0935-9648
1521-4095
language eng
recordid cdi_proquest_miscellaneous_2707875164
source Wiley Online Library Journals Frontfile Complete
subjects Circuit design
Couplings
Electronic structure
Inverse design
Material properties
Materials science
Metal-insulator transition
Neuromorphic computing
Nonlinear response
Synapses
Transformations (mathematics)
Tuning
Vanadium oxides
title Harnessing the Metal–Insulator Transition of VO2 in Neuromorphic Computing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T16%3A56%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Harnessing%20the%20Metal%E2%80%93Insulator%20Transition%20of%20VO2%20in%20Neuromorphic%20Computing&rft.jtitle=Advanced%20materials%20(Weinheim)&rft.au=Schofield,%20Parker&rft.date=2023-09-01&rft.volume=35&rft.issue=37&rft.spage=e2205294&rft.epage=e2205294&rft.pages=e2205294-e2205294&rft.issn=0935-9648&rft.eissn=1521-4095&rft_id=info:doi/10.1002/adma.202205294&rft_dat=%3Cproquest%3E2707875164%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2864444346&rft_id=info:pmid/&rfr_iscdi=true