Soft Memristor at a Microbubble Interface

Yueke Niu, Yu Ma, Yanbo Xie

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Memristors show promising features for neuromorphic computing. Here we report a soft memristor based on the liquid-vapor surface of a microbubble. The thickness of the liquid film was modulated by electrostatic and interfacial forces, enabling resistance switches. We found a pinched current hysteresis at scanning periods between 1.6 and 51.2 s, while representing a resistor below 1.6 s and a diode-like behavior above 51.2 s. We approximate the thickening/thinning dynamics of liquid film by pressure-driven flow at the interface and derived the impacts of salt concentration and voltage amplitude on the memory effects. Our work opens a new approach to building nanofluidic memristors by a soft interface, which may be useful for new types of neuromorphic computing in the future.

Original languageEnglish
Pages (from-to)10475-10481
Number of pages7
JournalNano Letters
Volume24
Issue number34
DOIs
StatePublished - 28 Aug 2024

Keywords

  • Hebbian learning
  • Liquid computing
  • Liquid films
  • Memristor
  • Microbubble
  • Soft matter

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