• Media type: E-Article
  • Title: Memristor Kinetics and Diffusion Characteristics for Mixed Anionic‐Electronic SrTiO3‐δ Bits: The Memristor‐Based Cottrell Analysis Connecting Material to Device Performance
  • Contributor: Messerschmitt, Felix; Kubicek, Markus; Schweiger, Sebastian; Rupp, Jennifer L.M.
  • Published: Wiley, 2014
  • Published in: Advanced Functional Materials, 24 (2014) 47, Seite 7448-7460
  • Language: English
  • DOI: 10.1002/adfm.201402286
  • ISSN: 1616-301X; 1616-3028
  • Origination:
  • Footnote:
  • Description: Memristors based on mixed anionic‐electronic conducting oxides are promising devices for future data storage and information technology with applications such as non‐volatile memory or neuromorphic computing. Unlike transistors solely operating on electronic carriers, these memristors rely, in their switch characteristics, on defect kinetics of both oxygen vacancies and electronic carriers through a valence change mechanism. Here, Pt|SrTiO3‐δ|Pt structures are fabricated as a model material in terms of its mixed defects which show stable resistive switching. To date, experimental proof for memristance is characterized in hysteretic current–voltage profiles; however, the mixed anionic‐electronic defect kinetics that can describe the material characteristics in the dynamic resistive switching are still missing. It is shown that chronoamperometry and bias‐dependent resistive measurements are powerful methods to gain complimentary insights into material‐dependent diffusion characteristics of memristors. For example, capacitive, memristive and limiting currents towards the equilibrium state can successfully be separated. The memristor‐based Cottrell analysis is proposed to study diffusion kinetics for mixed conducting memristor materials. It is found that oxygen diffusion coefficients increase up to 3 × 10–15 m2s–1 for applied bias up to 3.8 V for SrTiO3‐δ memristors. These newly accessible diffusion characteristics allow for improving materials and implicate field strength requirements to optimize operation towards enhanced performance metrics for valence change memristors.