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Bioinspired nanofluidic iontronics for brain-like computing

Nano Research 2024年第2期17卷 503-514页

作者： Lejian Yu Xipeng Li Chunyi Luo Zhenkang Lei Yilan Wang Yaqi Hou Miao Wang Xu Hou State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China Institute of Artificial Intelligence Xiamen UniversityXiamen 361005China Department of Physics Research Institute for Biomimetics and Soft MatterFujian Provincial Key Laboratory for Soft Functional Materials ResearchJiujiang Research InstituteCollege of Physical Science and TechnologyXiamen UniversityXiamen 361005China The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province Department of BiomaterialsResearch Center of Biomedical Engineering of XiamenCollege of MaterialsXiamen UniversityXiamen 361005China The Institute of Flexible Electronics(IFE Future Technologies)Xiamen UniversityXiamen 361005China Binzhou Institute of Technology Binzhou 256600China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361102China Engineering Research Center of Electrochemical Technologies of Ministry of Education Xiamen UniversityXiamen 361005China

The human brain performs computations via a highly interconnected network of *** 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 *** 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 ***,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 *** 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 ***,the challenges and opportunities of bioinspired nanofluidic iontronics in the pioneering and interdisciplinary research fields are proposed,including brain–computer interfaces and artificial neurons.

关键词： human brain ion transport nanofluidics brain-like computing memristive effect

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memristive effects on an improved discrete Rulkov neuron model

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Science China(Technological Sciences) 2023年第11期66卷 3153-3163页

作者： BAO Han LI KeXin MA Jun HUA ZhongYun XU Quan BAO BoCheng School of Microelectronics and Control Engineering Changzhou UniversityChangzhou 213159China Department of Physics Lanzhou University of TechnologyLanzhou 730050China School of Computer Science and Technology Harbin Institute of TechnologyShenzhenShenzhen 518055China

A change in neuronal-action potential can generate a magnetically induced current during the release and propagation of intracellular *** better characterize the electromagnetic-induction effect,this paper presents an improved discrete Rulkov(ID-Rulkov)neuron model by coupling a discrete model of a memristor with sine memductance into a discrete Rulkov neuron *** ID-Rulkov neuron model possesses infinite invariant points,and its memristor-induced stability effect is evaluated by detecting the routes of period-doubling and Neimark-Sacker *** investigated the memristor-induced dynamic effects on the neuron model using bifurcation plots and firing ***,we theoretically expounded the memristor initial-boosting mechanism of infinite coexisting *** results show that the ID-Rulkov neuron model can realize diverse neuron firing patterns and produce hyperchaotic attractors that are nondestructively boosted by the initial value of the memristor,indicating that the introduced memristor greatly benefits the original neuron *** hyperchaotic attractors initially boosted by the memristor were verified by hardware experiments based on a hardware *** addition,pseudorandom number generators are designed using the ID-Rulkov neuron model,and their high randomness is demonstrated based onstrict test results.

关键词： neuron model invariant point memristive effect complex dynamics pseudorandom number generators

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