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Details

Autor(en) / Beteiligte
Titel
Spatiotemporal characterization of the field-induced insulator-to-metal transition
Ist Teil von
  • Science (American Association for the Advancement of Science), 2021-08, Vol.373 (6557), p.907-911
Ort / Verlag
Washington: The American Association for the Advancement of Science
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Science magazine suite
Beschreibungen/Notizen
  • Watching a metal filament grow Resistive switching is a process in which the electrical resistance of a sample changes abruptly in response to a voltage pulse, often by orders of magnitude. This process is at the heart of many neuromorphic computing approaches but visualizing it in both space and time is tricky. del Valle et al . monitored the resistive switching in three different vanadium oxide compounds by measuring time- and space-resolved optical reflectivity (see the Perspective by Hilgenkamp and Gao). A characteristic conducting filament was quickly nucleated on the inhomogeneities in the sample and then propagated due to Joule heating. —JS Time- and space-resolved optical reflectivity is used to visualize resistive switching in vanadium oxide films. Many correlated systems feature an insulator-to-metal transition that can be triggered by an electric field. Although it is known that metallization takes place through filament formation, the details of how this process initiates and evolves remain elusive. We use in-operando optical reflectivity to capture the growth dynamics of the metallic phase with space and time resolution. We demonstrate that filament formation is triggered by nucleation at hotspots, with a subsequent expansion over several decades in time. By comparing three case studies (VO 2 , V 3 O 5 , and V 2 O 3 ), we identify the resistivity change across the transition as the crucial parameter governing this process. Our results provide a spatiotemporal characterization of volatile resistive switching in Mott insulators, which is important for emerging technologies, such as optoelectronics and neuromorphic computing.

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