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Nanofluidic systems for ionic intelligence
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DOI：10.1039/D6NH00048G.png)
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Abstract
En 中文
Artificial intelligence is rapidly permeating modern technology; but its growth is increasingly constrained by the costs of delivering power and removing heat. Neural computation offers a striking counterpoint; for it achieves sophisticated information processing at exceptionally low energy by exploiting ionic flows and adaptive conductance. Inspired by the Hodgkin-Huxley view that function emerges from ion-transport dynamics; recent work has begun to implement memory and learning directly in fluids; where ions simultaneously carry signals and encode internal device state. This Review charts the emerging landscape of fluidic ionic memristors; from soft; bioinspired materials to manufacturable solid-state nanofluidic architectures. In lipid bilayers; droplet networks; tissues and ionic polymers; electrical activity is intrinsically coupled to chemistry and mechanics; enabling plasticity across multiple timescales. In rigid nanopores; nanochannels and angstrom-scale slits; the softness is transferred from the scaffold to the ionic degrees of freedom; where electric double-layer dynamics; concentration polarization and confinement-driven effects produce history-dependent transport in robust inorganic frameworks. Hybrid approaches integrate gels; brushes; particles; or biomolecules within microfabricated structures to combine stability with rich analogue dynamics. We conclude by outlining the key requirements for translation from reproducibility to scalable integration towards ionic intelligence technologies.
Keywords:
ionic intelligence
nanofluidic systems
memristors
ion-transport dynamics
adaptive conductance