Resistive switching in graphene: A theoretical case study on the alumina-graphene interfaceShow others and affiliations
2023 (English)In: Physical Review Research, E-ISSN 2643-1564, Vol. 5, no 4, article id 043147Article in journal (Refereed) Published
Abstract [en]
Neuromorphic computing mimics the brain's architecture to create energy-efficient devices. Reconfigurable synapses are crucial for neuromorphic computing, which can be achieved through memory-resistive (memristive) switching. Graphene-based memristors have shown nonvolatile multibit resistive switching with desirable endurance. Through first-principles calculations, we study the structural and electronic properties of graphene in contact with an ultra-thin alumina overlayer and demonstrate how one can use charge doping to exert direct control over its interfacial covalency, reversibly switching between states of conductivity and resistivity in the graphene layer. We further show that this proposed mechanism can be stabilized through the p-type doping of graphene, e.g., by naturally occurring defects, the passivation of dangling bonds or defect engineering.
Place, publisher, year, edition, pages
American Physical Society, 2023. Vol. 5, no 4, article id 043147
National Category
Condensed Matter Physics
Identifiers
URN: urn:nbn:se:oru:diva-110212DOI: 10.1103/PhysRevResearch.5.043147ISI: 001110073500007Scopus ID: 2-s2.0-85178005622OAI: oai:DiVA.org:oru-110212DiVA, id: diva2:1819239
Funder
Swedish National Infrastructure for Computing (SNIC)Swedish Research Council, 2019-03569; 2019-03666r 1002772; 2019-03666Knut and Alice Wallenberg FoundationSwedish Energy AgencyStandUpeSSENCE - An eScience CollaborationGöran Gustafsson Foundation for Research in Natural Sciences and Medicine
Note
R.P.M. is grateful to Ivan P. Miranda for fruitful discussions. The computational resources for this work were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) , partially funded by the Swedish Research Council. The authors also acknowledge European Research Council (ERC) (synergy grant FASTCORR, project No. 854843 Consolidator Grant SPINNER, Project No. 101002772) , the Knut and Alice Wallenberg foundation (KAW) , the Swedish Energy Agency (Energimyndigheten) , StandUPP, and eSSENCE. Y.O.K. acknowledges the financial support from the Swedish Research Council (VR) under Project No. 2019-03569 and the Goran Gustafsson Foundation. D.T. acknowledges the financial support from the Swedish Research Council (VR) under Project No. 2019-03666r 1002772) , the Knut and Alice Wallenberg foundation (KAW) , the Swedish Energy Agency (Energimyndigheten) , StandUPP, and eSSENCE. Y.O.K. acknowledges the financial support from the Swedish Research Council (VR) under Project No. 2019-03569 and the Goran Gustafsson Foundation. D.T. acknowledges the financial support from the Swedish Research Council (VR) under Project No. 2019-03666.
2023-12-132023-12-132024-01-22Bibliographically approved