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Related Concept Videos

Determination of Crystal Structures01:29

Determination of Crystal Structures

In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...
X-ray Crystallography02:18

X-ray Crystallography

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

X-ray Diffraction of Biological Samples

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 crystal...
Unit Cells01:18

Unit Cells

A crystal's internal structure is an orderly array of atoms, ions, or molecules, and the details of this array significantly influence the solid's properties. In a crystal, periodically repeating 'structural motifs' - which could be atoms, molecules, or groups thereof - create a 'space lattice.' This is essentially a three-dimensional, infinite array of points, each surrounded by its neighbors in an identical way, forming the basic structure of the crystal.A 'unit cell' is a theoretical...
Crystal Density01:19

Crystal Density

The crystal lattice structure of a material allows us to determine how many molecules exist in its unit cell. With this information, alongside the unit-cell parameters - three distance parameters (a, b, c) and three angular parameters (α, β, γ).Density (ρ) = (Z × M) / (a × b × c × NA)where:Z is the number of formula units per unit cellM is the molar mass of the substancea, b, and c are the edge lengths of the unit cellNA is Avogadro’s numberFor a simple cubic lattice, atoms are located only at...

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Microcrystallography of Protein Crystals and In Cellulo Diffraction
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Microcrystallography of Protein Crystals and In Cellulo Diffraction

Published on: July 21, 2017

Application of clustering techniques to electron-diffraction data: determination of unit-cell parameters.

Sebastian Schlitt1, Tatiana E Gorelik, Andrew A Stewart

  • 1Institute for Mathematics, Johannes Gutenberg University Mainz, Staudingerweg 9, 55128, Mainz, Germany.

Acta Crystallographica. Section A, Foundations of Crystallography
|August 16, 2012
PubMed
Summary

A novel clustering analysis method using DBSCAN accurately determines unit-cell vectors from crystal diffraction data. This approach is optimal for noisy or limited datasets, particularly in automated diffraction tomography (ADT).

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Area of Science:

  • Crystallography
  • Materials Science
  • Data Analysis

Background:

  • Accurate unit-cell determination is crucial for materials characterization.
  • Traditional methods can struggle with limited or noisy diffraction data.
  • Automated Diffraction Tomography (ADT) generates extensive datasets requiring robust analysis.

Purpose of the Study:

  • To introduce a new clustering-based approach for unit-cell vector determination.
  • To demonstrate the efficacy of the DBSCAN algorithm for this task.
  • To validate the method on various materials using ADT and X-ray diffraction data.

Main Methods:

  • Utilizing the density-based spatial clustering of applications with noise (DBSCAN) algorithm.
  • Applying clustering analysis to single-crystal diffraction data.
  • Testing the method on both electron-diffraction ADT and single-crystal X-ray diffraction datasets.

Main Results:

  • Successful determination of unit-cell vectors using DBSCAN clustering.
  • The method shows particular utility for limited tilt sequences and noisy data.
  • Demonstrated effectiveness across diverse materials analyzed with ADT and X-ray diffraction.

Conclusions:

  • Clustering analysis, specifically DBSCAN, provides a robust method for unit-cell determination.
  • This approach enhances the analysis of challenging single-crystal diffraction datasets.
  • The method is broadly applicable to various materials and diffraction techniques.