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相关概念视频

X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

3.8K
X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal...
3.8K
X-ray Crystallography02:18

X-ray Crystallography

23.8K
The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
23.8K

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相关实验视频

Updated: Jun 14, 2025

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
10:12

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

Published on: June 19, 2018

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人工智能增强的X射线衍射分析:朝着实时矿物阶段识别和量化.

Nikolaos I Prasianakis1

  • 1Laboratory for Waste Management, Paul Scherrer Institute, Forschungsstrasse 111, Villigen PSI, 5232 Switzerland.

IUCrJ
|August 30, 2024
PubMed
概括

卷积神经网络可以通过显著减少处理时间来彻底改变X射线衍射 (XRD) 分析. 本研究提供了使用合成和真实矿物质数据对这些方法准确性的初步评估.

科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学的计算化学
  • 地质地质地质地质地质地

背景情况:

  • X射线衍射 (XRD) 是矿物质识别和量化的一个关键技术.
  • 传统的XRD分析可能耗时,限制其在高通量场景中的应用.

研究的目的:

  • 研究卷积神经网络 (CNN) 加速XRD分析的潜力.
  • 与传统方法相比,评估基于CNN的XRD分析的准确性.

主要方法:

  • 开发和应用CNN模型用于XRD模式处理.
  • 在合成和现实世界矿物质混合物数据集上测试模型.

主要成果:

  • CNNs显著减少了XRD分析所需的处理时间.
  • 开发的方法在分析矿物混合物方面显示出有希望的准确度.

结论:

  • 卷积神经网络为XRD分析提供了一种革命性的方法,提高了速度和效率.
  • 需要进一步的研究,以充分确定CNN在定量XRD分析中的能力和局限性.
关键词:
计算建模计算建模卷积神经网络是一种卷积神经网络.矿物阶段识别矿物阶段识别粉末X射线衍射粉末的X射线.

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Analysis of Minerals Produced by hFOB 1.19 and Saos-2 Cells Using Transmission Electron Microscopy with Energy Dispersive X-ray Microanalysis
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Analysis of Minerals Produced by hFOB 1.19 and Saos-2 Cells Using Transmission Electron Microscopy with Energy Dispersive X-ray Microanalysis

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Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
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Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

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相关实验视频

Last Updated: Jun 14, 2025

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
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Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

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Analysis of Minerals Produced by hFOB 1.19 and Saos-2 Cells Using Transmission Electron Microscopy with Energy Dispersive X-ray Microanalysis
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Analysis of Minerals Produced by hFOB 1.19 and Saos-2 Cells Using Transmission Electron Microscopy with Energy Dispersive X-ray Microanalysis

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Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
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Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

Published on: May 10, 2021

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