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Configurable Crack Wall Conduction in a Complex Oxide.

Youngki YeoSoo-Yoon HwangJinwook YeoJihun KimJinhyuk JangHeung-Sik ParkYong-Jin KimDuc Duy LeKyung SongMoonhong KimSeunghwa RyuSi-Young ChoiChan-Ho Yang
Published in: Nano letters (2023)
Mobile defects in solid-state materials play a significant role in memristive switching and energy-efficient neuromorphic computation. Techniques for confining and manipulating point defects may have great promise for low-dimensional memories. Here, we report the spontaneous gathering of oxygen vacancies at strain-relaxed crack walls in SrTiO 3 thin films grown on DyScO 3 substrates as a result of flexoelectricity. We found that electronic conductance at the crack walls was enhanced compared to the crack-free region, by a factor of 10 4 . A switchable asymmetric diode-like feature was also observed, and the mechanism is discussed, based on the electrical migration of oxygen vacancy donors in the background of Sr-deficient acceptors forming n + -n or n - n + junctions. By tracing the temporal relaxations of surface potential and lattice expansion of a formed region, we determine the diffusivity of mobile defects in crack walls to be 1.4 × 10 -16 cm 2 /s, which is consistent with oxygen vacancy kinetics.
Keyphrases
  • solid state
  • machine learning
  • risk assessment
  • deep learning
  • single molecule
  • human health
  • wild type