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Modeling and characterization of stochastic resistive switching in single Ag2S nanowires.
Frick, Nikolay; Hosseini, Mahshid; Guilbaud, Damien; Gao, Ming; LaBean, Thomas H.
Afiliación
  • Frick N; NC State University, Materials Science and Engineering, Raleigh, 27606, USA. nvfrik@ncsu.edu.
  • Hosseini M; NC State University, Materials Science and Engineering, Raleigh, 27606, USA.
  • Guilbaud D; NC State University, Physics, Raleigh, 27606, USA.
  • Gao M; NC State University, Biomedical Engineering, Raleigh, 27606, USA.
  • LaBean TH; NC State University, Materials Science and Engineering, Raleigh, 27606, USA.
Sci Rep ; 12(1): 6754, 2022 Apr 26.
Article en En | MEDLINE | ID: mdl-35474068
Chalcogenide resistive switches (RS), such as Ag2S, change resistance due to the growth of metallic filaments between electrodes along the electric field gradient. Therefore, they are candidates for neuromorphic and volatile memory applications. This work analyzed the RS of individual Ag2S nanowires (NWs) and extended the basic RS model to reproduce experimental observations. The work models resistivity of the device as a percolation of the conductive filaments. It also addressed continuous fluctuations of the resistivity with a stochastic change in volume fractions of the filaments in the device. As a result, these fluctuations cause unpredictable patterns in current-voltage characteristics and include a spontaneous change in resistance of the device during the linear sweep that conventional memristor models with constant resistivity cannot represent. The parameters of the presented stochastic model of a single Ag2S NW were fitted to the experimental data and reproduced key features of RS in the physical devices. Moreover, the model suggested a non-core shell structure of the Ag2S NWs. The outcome of this work is aimed to aid in simulating large self-assembled memristive networks and help to extend existing RS models.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido