4.8 Review

Bioinspired nanofluidic iontronics for brain-like computing

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NANO RESEARCH
卷 -, 期 -, 页码 -

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TSINGHUA UNIV PRESS
DOI: 10.1007/s12274-023-5900-y

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human brain; ion transport; nanofluidics; brain-like computing; memristive effect

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Inspired by the information processing mechanism of the human brain, bioinspired nanofluidic iontronics has been developed as a potential solution for efficient brain-like computing. The controllability of charge carriers and the ability to modify structures and chemistry enable the realization of brain-like functions. This review provides a comprehensive framework and design strategy for nanofluidic systems, as well as discusses recent advances and prospects in ion-based brain computing and artificial neuromorphic devices.
The human brain performs computations via a highly interconnected network of neurons. Taking inspiration from the information delivery and processing mechanism of the human brain in central nervous systems, bioinspired nanofluidic iontronics has been proposed and gradually engineered to overcome the limitations of the conventional electron-based von Neumann architecture, which shows the promising potential to enable efficient brain-like computing. Anomalous and tunable nanofluidic ion transport behaviors and spatial confinement show promising controllability of charge carriers, and a wide range of structural and chemical modification paves new ways for realizing brain-like functions. Herein, a comprehensive framework of mechanisms and design strategy is summarized to enable the rational design of nanofluidic systems and facilitate the further development of bioinspired nanofluidic iontronics. This review provides recent advances and prospects of the bioinspired nanofluidic iontronics, including ion-based brain computing, comprehension of intrinsic mechanisms, design of artificial nanochannels, and the latest artificial neuromorphic functions devices. Furthermore, the challenges and opportunities of bioinspired nanofluidic iontronics in the pioneering and interdisciplinary research fields are proposed, including brain-computer interfaces and artificial neurons.

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