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The 3D battery concept applied on silicon–graphite electrodes (Si/C) has revealed a significant improvement of battery performances, including high-rate capability, cycle stability, and cell lifetime. 3D architectures provide free spaces for volume expansion as well as additional lithium diffusion pathways into the electrodes. Therefore, the cell degradation induced by the volume change of silicon as active material can be significantly reduced, and the high-rate capability can be achieved. In order to better understand the impact of 3D electrode architectures on rate capability and degradation process of the thick film silicon–graphite electrodes, we applied laser-induced breakdown spectroscopy (LIBS). A calibration curve was established that enables the quantitative determination of the elemental concentrations in the electrodes. The structured silicon–graphite electrode, which was lithiated by 1C, revealed a homogeneous lithium distribution within the entire electrode. In contrast, a lithium concentration gradient was observed on the unstructured electrode. The lithium concentration was reduced gradually from the top to the button of the electrode, which indicated an inhibited diffusion kinetic at high C-rates. In addition, the LIBS applied on a model electrode with micropillars revealed that the lithium-ions principally diffused along the contour of laser-generated structures into the electrodes at elevated C-rates. The rate capability and electrochemical degradation observed in lithium-ion cells can be correlated to lithium concentration profiles in the electrodes measured by LIBS.

The application of facial recognition technology (FRT) can effectively reduce the red-light running behavior of e-bikers. However, the privacy issues involved in FRT have also attracted widespread attention from society. This research aims to explore the public and traffic police’s attitudes toward FRT to optimize the use and implementation of FRT. A structured questionnaire survey of 270 people and 94 traffic police in Fuzhou, China, was used. In the research, we use several methods to analyze the investigation data, including Mann–Whitney U test, Kruskal–Wallis test, and multiple correspondence analysis. The survey results indicate that the application of FRT has a significant effect on reducing red-light running behavior. The public’s educational level and driving license status are the most influential factors related to their attitudes to FRT (p < 0.001). Public members with these attributes show more supportive attitudes to FRT and more concerns about privacy invasion. There are significant differences between the public and traffic police in attitudes toward FRT (p < 0.001). Compared with the public, traffic police officers showed more supportive attitudes to FRT. This research contributes to promoting the application of FRT legitimately and alleviating people’s concerns about the technology.