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相关概念视频

Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

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The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
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相关实验视频

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Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
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自主扫描道显微镜通过深度学习成像

Zhiwen Zhu1, Shaoxuan Yuan2, Quan Yang2

  • 1Materials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai 200444, China.

Journal of the American Chemical Society
|October 9, 2024
PubMed
概括

这项研究引入了使用深度学习 (DL) 的自主扫描道显微镜 (STM) 框架. 该系统自动化复杂的操作,使高效,高分辨率的原子和分子表征.

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科学领域:

  • 材料科学
  • 表面科学
  • 纳米技术

背景情况:

  • 扫描道显微镜 (STM) 提供了原子精度,但涉及劳动密集,主观的过程.
  • 深度学习 (DL) 在自动化复杂,高维度任务方面表现出色.

研究的目的:

  • 开发一个基于深度学习的自主STM框架,用于无偏见的,自动化的原子和分子表征.
  • 通过人工智能提高扫描探针显微镜的效率和能力.

主要方法:

  • 一个卷积神经网络 (CNN) 实时评估了STM图像质量.
  • 一个U-net模型识别了裸体表面,一个深度Q学习网络 (DQN) 代理自主调节了探测器.
  • 一个对象识别模型自动识别分子吸附物.

主要成果:

  • 该框架在48小时内实现了STM自主操作,测量大约1.9μm2.
  • 在不影响高分辨率成像的情况下,生成了介面层中分子物种的自动化统计数据.
  • 该系统通过低温 (78K) 的测量证明了其强度.

结论:

  • 通过将DL与STM集成,可以实现自主,高通量原子和分子分析.
  • 这种方法加速了材料的发现,并提高了扫描探针显微镜的功能.