Bioinspired learning and memory in ionogels through fast response and slow relaxation dynamics of ions

Ning Zhou, Ting Cui, Zhouyue Lei () and Peiyi Wu ()
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Ning Zhou: Donghua University
Ting Cui: Donghua University
Zhouyue Lei: Donghua University
Peiyi Wu: Donghua University

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Mimicking biological systems’ sensing, learning, and memory capabilities in synthetic soft materials remains challenging. While significant progress has been made in sensory functions in ionogels, their learning and memory capabilities still lag behind biological systems. Here, we introduce cation-π interactions and a self-adaptable ionic-double-layer interface in bilayer ionogels to control ion transport. Fast ion response enables sensing and learning, while slow ion relaxation supports long-term memory. The ionogels achieve bioinspired functions, including sensitization, habituation, classical conditioning, and multimodal memory, with low energy consumption (0.06 pJ per spike). Additionally, the ionogels exhibit mechanical adaptability, such as stretchability, self-healing, and reconfigurability, making them ideal for soft robotics. Notably, the ionogels enable a robotic arm to mimic the selective capture behavior of a Venus flytrap. This work bridges the gap between biological intelligence and artificial systems, offering promising applications in bioinspired, energy-efficient sensing, learning, and memory.

Date: 2025
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DOI: 10.1038/s41467-025-59944-3

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