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通过近距机械发光成像实现高灵敏度和高分辨率的动态力学作用可视化。

Visualizing Dynamic Mechanical Actions with High Sensitivity and High Resolution by Near-Distance Mechanoluminescence Imaging.

机构信息

State Key Laboratory of Physical Chemistry of Solid Surface, Fujian Provincial Key Laboratory of Materials Genome and College of Materials, Xiamen University, Simingnan-Road 422, Xiamen, 361005, China.

Baotou Research Institute of Rare Earths, Huanghe-Avenue 36, Baotou, 014060, China.

出版信息

Adv Mater. 2022 Sep;34(36):e2202864. doi: 10.1002/adma.202202864. Epub 2022 Aug 5.

Abstract

Proportionally converting the applied mechanical energy into photons by individual mechanoluminescent (ML) micrometer-sized particles opens a new way to develop intelligent electronic skins as it promises high-resolution stress distribution visualization and fast response. However, a big challenge for ML sensing technology is its low sensitivity in detecting stress. In this work, a novel stress distribution sensor with the detection sensitivity enhanced by two orders of magnitude is developed by combining a proposed near-distance ML imaging scheme with an improved mechano-to-photon convertor. The enhanced sensitivity is the main contributor to the realization of a maximum photon harvesting rate of ≈80% in the near-distance ML imaging scheme. The developed near-distance ML sensor shows a high sensitivity with a detection limit down to ≈kPa level, high spatial resolution of 254 dpi, and fast response with an interval of 3.3 ms, which allows for high-resolution and real-time visualization of complex mechanical actions such as irregular solid contacts or fluid impacts, and thus enables use in intelligent electronic skin, structural health monitoring, and human-computer interaction.

摘要

通过单个微机械发光(ML)微尺寸颗粒将施加的机械能按比例转换为光子,为开发智能电子皮肤开辟了一条新途径,因为它有望实现高分辨率的应力分布可视化和快速响应。然而,ML 传感技术的一个大挑战是其在检测压力方面的灵敏度低。在这项工作中,通过将提出的近距 ML 成像方案与改进的机械到光子转换器相结合,开发了一种新型的应力分布传感器,其检测灵敏度提高了两个数量级。增强的灵敏度是实现近距 ML 成像方案中≈80%的最大光子采集率的主要贡献者。所开发的近距 ML 传感器具有高灵敏度,检测限低至≈kPa 级,空间分辨率高达 254dpi,响应间隔为 3.3ms,可实现复杂机械动作(如不规则固体接触或流体冲击)的高分辨率和实时可视化,从而可用于智能电子皮肤、结构健康监测和人机交互。

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