PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 27, 2026Nanotechnology0 citationsOpen Access

Understanding the volatile memristor via direct observation of surface diffusion-regulated Cu-based conductive filaments

View Full Paper
BZBo ZhangGWGuangyu WenXZXu Zhao

Key Points

  • The aim is to understand the mechanisms governing the dynamics of conductive filaments in a bioinspired memristor.
  • Developed a bilayer memristor with W/SiO₂/Cux(SiO2)100-x/Cu structure.
  • Conducted cross-sectional transmission electron microscopy to observe filament morphology.
  • Utilized X-ray photoelectron spectroscopy to analyze copper diffusion and redox reactions.
  • Achieved a high accuracy of 93.11% for handwritten digit recognition tasks.
  • Found conductive filament rupture and recovery linked to surface energy minimization.
  • Identified the core role of copper diffusion and valence state transitions in filament dynamics.

Abstract

This study develops a bioinspired bilayer volatile memristor with a W/SiO₂/Cux(SiO2)100-x/Cu structure. The morphology and crystalline structure of the conductive filaments were directly observed via cross-sectional transmission electron microscopy. Discrete spherical copper-based grains construct conductive filaments with large internal surfaces, some of which are distorted due to stress interactions with the silicon dioxide matrix. According to the results of X-ray photoelectron spectroscopy, the diffusion of copper and redox reactions (involving the valence state transitions of copper to zero valence, positive monovalence, and positive divalence) are the core mechanisms governing the dynamic evolution of conductive filaments. When the stimulus is subsequently removed, the minimization of the thermodynamic surface energy drives the transformation of nonspherical grains into stable spherical grains, leading to conductive filament rupture and spontaneous recovery of the device to the initial state. By regulating the parameters of pulse signals to achieve precise control over conductive filament dynamics, the device successfully reproduces the behavior of nociceptors. A high accuracy of 93.11% for the handwritten digit recognition task in neurocomputing is achieved, showing the multipurpose function of the memristor.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69eefcf4fede9185760d3b34https://doi.org/10.1088/1361-6528/ae645a
Ask AI
Helpful
Bookmark
Share
View Full Paper