<p>This article proposes a new conceptual biomimetic liquid metal synapse (LMS), which operates on a principle that resembles electrochemical structural plasticity, distinct from conventional electronic state transitions. Its core architecture and biomimetic working mechanism have been clarified, which are governed by synergistic, persistent changes in the interfacial oxide layer and ion concentration at the liquid metal-electrolyte junction. These synergistic effects enable the precise modulation of synaptic strength through electrolyte engineering. The LMS demonstrates electrical behaviors analogous to fundamental neurobiological functions, such as signal transmission and persistent state changes reminiscent of long-term plasticity, which are rooted in permanent morphological and compositional reconstruction akin to biological systems. The inherent deformability, self-repair capacity, and high conductivity of liquid metal facilitate the design of neural networks that replicate the dynamic, adaptive signaling essential for flexible intelligent devices. The insights from the LMSs suggest a promising pathway for future research into next-generation neural functional architectures.</p>

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Biomimetic liquid metal synapse

  • Chunxue Wan,
  • Jianye Gao,
  • Xilong Zhang,
  • Lei Li,
  • Jing Liu

摘要

This article proposes a new conceptual biomimetic liquid metal synapse (LMS), which operates on a principle that resembles electrochemical structural plasticity, distinct from conventional electronic state transitions. Its core architecture and biomimetic working mechanism have been clarified, which are governed by synergistic, persistent changes in the interfacial oxide layer and ion concentration at the liquid metal-electrolyte junction. These synergistic effects enable the precise modulation of synaptic strength through electrolyte engineering. The LMS demonstrates electrical behaviors analogous to fundamental neurobiological functions, such as signal transmission and persistent state changes reminiscent of long-term plasticity, which are rooted in permanent morphological and compositional reconstruction akin to biological systems. The inherent deformability, self-repair capacity, and high conductivity of liquid metal facilitate the design of neural networks that replicate the dynamic, adaptive signaling essential for flexible intelligent devices. The insights from the LMSs suggest a promising pathway for future research into next-generation neural functional architectures.