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Investigation of the Impact of High Temperatures on the Switching Kinetics of Redox‐Based Resistive Switching Cells using a High‐Speed Nanoheater
Author(s) -
Witzleben Moritz,
Fleck Karsten,
Funck Carsten,
Baumkötter Brigitte,
Zuric Milena,
Idt Alexander,
Breuer Thomas,
Waser Rainer,
Böttger Ulrich,
Menzel Stephan
Publication year - 2017
Publication title -
advanced electronic materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.25
H-Index - 56
ISSN - 2199-160X
DOI - 10.1002/aelm.201700294
Subject(s) - joule heating , materials science , kinetics , thermal conduction , resistive touchscreen , ionic bonding , electrode , kinetic energy , electrical resistivity and conductivity , thermodynamics , analytical chemistry (journal) , ion , composite material , electrical engineering , chemistry , physics , organic chemistry , quantum mechanics , engineering , chromatography
Abstract Ionic transport greatly influences the switching kinetics of filamentary resistive switching memories and depends strongly on temperature and electric fields. To separate the impact of both parameters on the switching kinetics and to further deepen the understanding of the influence of local Joule heating, a nanometer‐sized heating structure is employed. It consists of a 100 nm wide Pt electrode which, due to Joule heating, serves as heating source upon an electrical stimulus. These self‐heating properties are underlined by a 3D finite elements simulation model, which confirms a temperature increase of almost 500 K. Experimental electrical pulse measurements indicate that for this temperature a steady state is achieved in less than 100 ns. By employing this heating structure, kinetic measurements of a Pt/Ta 2 O 5 /Ta cell are performed at different temperatures and reveal that significantly decreased SET times are obtained with increasing temperature. This effect is accompanied by an increasing slope of the current prior to the SET event. The experimental results are further confirmed by predictions of an analytical model based on ionic conduction.

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