The research team of Prof. Zhang Haitian from Beijing University of Aeronautics and Astronautics (BUAA) has constructed a new type of artificial neural component characterized by adaptive hydrogen ion gradient sequencing. This concept overturns the traditional paradigm of device fabrication, no longer relying on inherent ideas such as material uniformity and symmetry, but breaking through previous technological constraints through the design of gradient ordering. This new artificial neural component enables an ultrafast and precise response to external signals by exploiting the ultrahigh sensitivity brought about by the tiny size of hydrogen ions. Characterization experiments are performed to illustrate the significance of constructing hydrogen ion gradient sequences from different perspectives and at multiple levels. Characterization experiments are performed to illustrate the importance of constructing hydrogen ion gradient sequences from different perspectives and at multiple levels. They used X-ray absorption near-edge structure spectroscopy (XANES) to characterize the valence change of the element nickel and found that hydrogen doping leads to a slight decrease in the valence state of Ni. By measuring the change in the valence state of Ni, it also suggests that there are different gradient distributions of hydrogen ions in neurons in different modes of operation. Relevant research was published in Matter under the title “Self-sensitizable neuromorphic device based on adaptive hydrogen gradient”.
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