Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors

Memristive devices based on high-temperature superconducting cuprates offer promising routes for neuromorphic computing, yet the microscopic mechanisms governing their resistive switching remain unclear. Here we investigate YBa2Cu3O7−δ (YBCO) memristors across 80–300 K, revealing robust bipolar swit...

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Detalles Bibliográficos
Autores: Günkel, Thomas, Miranda, Enrique, Balcells, Lluís, Mestres, Narcís, Palau, Anna, Suñé, Jordi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2026
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/416213
Acceso en línea:http://hdl.handle.net/10261/416213
Access Level:acceso abierto
Palabra clave:Cryogenic memristor
Resistive switching
Conduction mechanisms
Trap-controlled space-charge-limited conduction
High-temperature superconductor
Metal−insulator transition
Neuromorphic computing
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dc.title.none.fl_str_mv Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
title Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
spellingShingle Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
Günkel, Thomas
Cryogenic memristor
Resistive switching
Conduction mechanisms
Trap-controlled space-charge-limited conduction
High-temperature superconductor
Metal−insulator transition
Neuromorphic computing
title_short Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
title_full Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
title_fullStr Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
title_full_unstemmed Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
title_sort Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
dc.creator.none.fl_str_mv Günkel, Thomas
Miranda, Enrique
Balcells, Lluís
Mestres, Narcís
Palau, Anna
Suñé, Jordi
author Günkel, Thomas
author_facet Günkel, Thomas
Miranda, Enrique
Balcells, Lluís
Mestres, Narcís
Palau, Anna
Suñé, Jordi
author_role author
author2 Miranda, Enrique
Balcells, Lluís
Mestres, Narcís
Palau, Anna
Suñé, Jordi
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
European Cooperation in Science and Technology
Generalitat de Catalunya
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Cryogenic memristor
Resistive switching
Conduction mechanisms
Trap-controlled space-charge-limited conduction
High-temperature superconductor
Metal−insulator transition
Neuromorphic computing
topic Cryogenic memristor
Resistive switching
Conduction mechanisms
Trap-controlled space-charge-limited conduction
High-temperature superconductor
Metal−insulator transition
Neuromorphic computing
description Memristive devices based on high-temperature superconducting cuprates offer promising routes for neuromorphic computing, yet the microscopic mechanisms governing their resistive switching remain unclear. Here we investigate YBa2Cu3O7−δ (YBCO) memristors across 80–300 K, revealing robust bipolar switching between high- and low-resistance states with temperature-independent SET and RESET voltages. Current–voltage analysis shows both states follow trap-controlled space-charge-limited conduction, modulated by shallow and deep trap states at an oxygen-deficient interfacial YBCO layer. A key enabler of this behavior is the formation of a deoxygenated layer beneath the top contact, which acts as a dynamic trap region and allows electrostatic control over a field-induced metal–insulator transition. We propose a dual-trap model where deep traps linked to CuO chain fragmentation stabilize a field-induced metal–insulator transition, enabling nonvolatile switching. These insights elucidate the role of trap dynamics in cuprate memristors and highlight their potential for cryogenic neuromorphic platforms compatible with superconducting computing architectures.
publishDate 2026
dc.date.none.fl_str_mv 2026
2026
2026
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dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/416213
url http://hdl.handle.net/10261/416213
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dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
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spelling Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate MemristorsGünkel, ThomasMiranda, EnriqueBalcells, LluísMestres, NarcísPalau, AnnaSuñé, JordiCryogenic memristorResistive switchingConduction mechanismsTrap-controlled space-charge-limited conductionHigh-temperature superconductorMetal−insulator transitionNeuromorphic computingMemristive devices based on high-temperature superconducting cuprates offer promising routes for neuromorphic computing, yet the microscopic mechanisms governing their resistive switching remain unclear. Here we investigate YBa2Cu3O7−δ (YBCO) memristors across 80–300 K, revealing robust bipolar switching between high- and low-resistance states with temperature-independent SET and RESET voltages. Current–voltage analysis shows both states follow trap-controlled space-charge-limited conduction, modulated by shallow and deep trap states at an oxygen-deficient interfacial YBCO layer. A key enabler of this behavior is the formation of a deoxygenated layer beneath the top contact, which acts as a dynamic trap region and allows electrostatic control over a field-induced metal–insulator transition. We propose a dual-trap model where deep traps linked to CuO chain fragmentation stabilize a field-induced metal–insulator transition, enabling nonvolatile switching. These insights elucidate the role of trap dynamics in cuprate memristors and highlight their potential for cryogenic neuromorphic platforms compatible with superconducting computing architectures.With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2023-001263-S).The authors acknowledge financial support from the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033/through CHIST-ERA PCI2021-122028-2A cofinanced by the European Union Next Generation EU/PRTR, the “Severo Ochoa” Programme for Centres of Excellence CEX2023-001263-S, HTSUPERFUN PID2021-124680OB-I00 and HTS-4ICT PID2024-156025OB-I00, cofinanced by ERDF A way of making Europe. The Spanish Nanolito networking project (RED2022-134096-T). The European COST Action SUPERQUMAP (CA 21144). E.M. and J.S. would like to thank the support the Spanish Ministerio de Ciencia e Innovación (MCIN)/Agencia Española de investigación (AEI) 10.13039/501100011 033 (Under project No. PID2022-139586NB-C41). T.G. acknowledge support from AGAUR Catalan Government Predoctoral Fellowship (2022 FISDU 00115). J.S. and E.M. acknowledge the support of EU through the HORIZON Chips-JU 101194172 NeAIxt Project and the Agencia Española de Investigación (AEI)/10.13039/501100011033 under Project PCI2025-163216. The authors acknowledge the Scientific Services at ICMAB and the UAB PhD program in Materials Science.Peer reviewedAmerican Chemical SocietyMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)European Cooperation in Science and TechnologyGeneralitat de CatalunyaEuropean CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262026info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/416213reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PCI2021-122028-2Ainfo:eu-repo/grantAgreement/AEI/Plan Estatal de investigación Científica y Técnica y de Innovación 2021-2023/CEX2023-001263-Sinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124680OB-I00PID2024-156025OB-I00RED2022-134096-Tinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-139586NB-C41info:eu-repo/grantAgreement/EC/HE/101194172info:eu-repo/grantAgreement/MICINN/Plan Estatal de investigación Científica y Técnica y de Innovación 2024-2027/PCI2025-163216http://doi.org/10.1021/acsaelm.5c02017Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4162132026-05-22T06:33:51Z
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