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<p>Underwater machines critically depend on advanced sensing capabilities to operate in complex aquatic environments, yet conventional perceptual devices face limitations in energy efficiency and identical signal patterns. Inspired by biological synapses, this work introduces a sustainable underwater artificial synapse (UAS) using recyclable liquid metalgraphene electrodes (LGEs) for flow perception. The UAS mimics ion-mediated neuronal signal transmission and exhibits short-term plasticity, including pair-pulse facilitation (PPF) with an index up to 1.86 and a signal amplification rate of 3.84 after 10 stimuli. The self-assembled LGEs, with high conductivity (3.3 Ω sq<sup>−1</sup>) and recyclability (&gt;95% for LM), are an essential part of UAS. It is speculated that the synaptic behaviour stemmed from ion adsorption, desorption, and diffusion in the electric double layer (EDL) of LGEs. Beyond flow detection, the UAS could effectively perceive droplets, falling objects, and propeller turbulence. The demonstration of controlling a submarine model underscores the potential of UASs for next-generation underwater robotics, marine monitoring, and defensive systems, overcoming traditional sensing constraints through biomimetic intelligence and sustainability.</p>

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Liquid metal-based passive underwater artificial synapse towards submarine flow perception

  • 期刊论文

  • 发表日期：

    2026年4月9日

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  • Chennan Lu,
  • Yushu Wang,
  • Wei Rao

摘要

Underwater machines critically depend on advanced sensing capabilities to operate in complex aquatic environments, yet conventional perceptual devices face limitations in energy efficiency and identical signal patterns. Inspired by biological synapses, this work introduces a sustainable underwater artificial synapse (UAS) using recyclable liquid metalgraphene electrodes (LGEs) for flow perception. The UAS mimics ion-mediated neuronal signal transmission and exhibits short-term plasticity, including pair-pulse facilitation (PPF) with an index up to 1.86 and a signal amplification rate of 3.84 after 10 stimuli. The self-assembled LGEs, with high conductivity (3.3 Ω sq−1) and recyclability (>95% for LM), are an essential part of UAS. It is speculated that the synaptic behaviour stemmed from ion adsorption, desorption, and diffusion in the electric double layer (EDL) of LGEs. Beyond flow detection, the UAS could effectively perceive droplets, falling objects, and propeller turbulence. The demonstration of controlling a submarine model underscores the potential of UASs for next-generation underwater robotics, marine monitoring, and defensive systems, overcoming traditional sensing constraints through biomimetic intelligence and sustainability.