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X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

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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...
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X-ray Crystallography02:18

X-ray Crystallography

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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...
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相关实验视频

Updated: Feb 17, 2026

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

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达拉:自动化多重假设相位识别和精细化从粉末X射线衍射.

Yuxing Fei1,2, Matthew J McDermott2, Christopher L Rom3

  • 1Department of Materials Science & Engineering, University of California, Berkeley, California 94720, United States.

Chemistry of materials : a publication of the American Chemical Society
|February 16, 2026
PubMed
概括
此摘要是机器生成的。

多相材料的粉末X射线衍射 (XRD) 分析由Dara自动化,这是一个新的框架. 这种数据驱动的方法提高了相位识别的准确性和可靠性,减少了手工工作.

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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.
  • 计算化学计算化学

背景情况:

  • 粉末X射线衍射 (XRD) 对于结晶材料的表征至关重要.
  • 在多相系统中解释XRD模式是复杂的,手动的,需要专业知识.
  • 由于可能存在多个相位解决方案,XRD数据的模糊性可能导致误解.

研究的目的:

  • 引入Dara (数据驱动的自动化瑞特维尔德分析),这是一个从XRD数据自动化多相识别的框架.
  • 为了提高复杂的XRD模式的相位识别和精细化的稳定性和准确性.
  • 为了减少XRD数据分析所需的手工工作和专业知识.

主要方法:

  • 达拉框架利用了对化学空间内的可信相组合的详尽树搜索.
  • 使用BGMN Rietveld精炼程序来验证每个假设的相组合.
  • 关键特征包括结构数据库过,同结构阶段集群和基于峰值匹配的评分.

主要成果:

  • 达拉自动化了从粉末XRD数据中识别和精制多个阶段.
  • 该框架提高了相位识别的可靠性和准确性,即使是复杂的模式.
  • 当出现模两可时,Dara生成多个假设,用于专家或进一步的基于工具的决策.

结论:

  • 达拉为分析复杂的XRD模式提供了可扩展的解决方案,减少了人为错误和努力.
  • 该框架有助于整合到多式联运特征化工作流程中.
  • 达拉代表了迈向自动化材料发现和表征的一步.