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相关概念视频

X-ray Crystallography02:18

X-ray Crystallography

23.7K
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...
23.7K
X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

3.7K
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...
3.7K

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相关实验视频

Updated: May 9, 2025

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects
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X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

Published on: June 8, 2016

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通过扩散模型从纳米晶体粉末衍射数据的初始结构解决方案.

Gabe Guo1,2, Tristan Luca Saidi3, Maxwell W Terban4

  • 1Columbia University, Department of Computer Science, New York, NY, USA. gabeguo@stanford.edu.

Nature materials
|April 28, 2025
PubMed
概括
此摘要是机器生成的。

一个新的机器学习模型,PXRDnet,可以从粉末衍射模式确定纳米材料的原子结构. 这种数据驱动的方法成功地解决了10 Å小的结构,推进了材料科学发现.

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Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene
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Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

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Reliable Mechanochemistry: Protocols for Reproducible Outcomes of Neat and Liquid Assisted Ball-mill Grinding Experiments
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相关实验视频

Last Updated: May 9, 2025

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects
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Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene
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Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

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Reliable Mechanochemistry: Protocols for Reproducible Outcomes of Neat and Liquid Assisted Ball-mill Grinding Experiments
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Reliable Mechanochemistry: Protocols for Reproducible Outcomes of Neat and Liquid Assisted Ball-mill Grinding Experiments

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科学领域:

  • 材料科学 材料科学 材料科学
  • 晶体学 晶体学是指结晶学.
  • 机器学习 机器学习

背景情况:

  • 确定纳米材料的结构是材料科学中的一个重大挑战.
  • 现有的方法在纳米级对象结构确定方面存在困难.

研究的目的:

  • 开发一种机器学习方法来解决纳米尺寸物体的结构.
  • 利用在已知结构上训练的生成扩散模型进行精确的结构确定.

主要方法:

  • 一个基于扩散过程的生成机器学习模型PXRDnet被开发出来.
  • 该模型在45229个已知的材料结构上进行了训练.
  • PXRDnet因子测量了单元细胞结构上的衍射模式和统计先验.

主要成果:

  • 在200种材料中,PXRDnet成功地解决了模拟的纳米晶体,其尺寸只有10 Å.
  • 该模型实现了高精度,在五次中确定了四次结构候选,平均R因子误差为7%.
  • PXRDnet展示了从杂,现实世界的实验衍射模式中解决结构的能力.

结论:

  • 数据驱动的方法,加上理论模拟,为解决以前未确定的纳米材料结构提供了一个有希望的途径.
  • PXRDnet代表了纳米材料结构分析的重大进步.
  • 这种方法有可能加速新材料的发现.