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Bioinspired nanofluidic iontronics for brain-like computing

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Abstract

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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Acknowledgement

This work was supported by the National Natural Science Foundation of China (Nos. 21975209, 52273305, 22205185, 52025132, T2241022, 21621091, 22021001, and 22121001), the 111 Project (Nos. B17027 and B16029), the National Science Foundation of Fujian Province of China (No. 2022J02059), the Science and Technology Projects of Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (No. RD2022070601), and the Tencent Foundation (The XPLORER PRIZE). The authors thank Yeyun Chen and Xuelian Yang for beneficial discussion.

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Author notes

  1. Lejian Yu and Xipeng Li contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China

    Lejian Yu, Xipeng Li, Chunyi Luo, Yilan Wang & Xu Hou

  2. Institute of Artificial Intelligence, Xiamen University, Xiamen, 361005, China

    Zhenkang Lei & Xu Hou

  3. Department of Physics, Research Institute for Biomimetics and Soft Matter, Fujian Provincial Key Laboratory for Soft Functional Materials Research, Jiujiang Research Institute, College of Physical Science and Technology, Xiamen University, Xiamen, 361005, China

    Xu Hou

  4. The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Department of Biomaterials, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen, 361005, China

    Miao Wang

  5. The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen, 361005, China

    Yaqi Hou

  6. Binzhou Institute of Technology, Binzhou, 256600, China

    Xipeng Li

  7. Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen, 361102, China

    Xu Hou

  8. Engineering Research Center of Electrochemical Technologies of Ministry of Education, Xiamen University, Xiamen, 361005, China

    Xu Hou

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  2. Xipeng Li
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  3. Chunyi Luo
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  4. Zhenkang Lei
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  5. Yilan Wang
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  6. Yaqi Hou
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  7. Miao Wang
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  8. Xu Hou
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Corresponding authors

Correspondence to Yaqi Hou, Miao Wang or Xu Hou.

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Yu, L., Li, X., Luo, C. et al. Bioinspired nanofluidic iontronics for brain-like computing. Nano Res. 17, 503–514 (2024). https://doi.org/10.1007/s12274-023-5900-y

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  • DOI: https://doi.org/10.1007/s12274-023-5900-y

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