Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Metallic Solids02:37

Metallic Solids

19.4K
Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
All metallic solids exhibit high thermal and electrical conductivity, metallic luster, and malleability....
19.4K
Structures of Solids02:22

Structures of Solids

15.7K
Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
15.7K
Lattice Centering and Coordination Number02:33

Lattice Centering and Coordination Number

10.2K
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
Imagine taking a large number of identical...
10.2K
Ionic Crystal Structures02:42

Ionic Crystal Structures

15.5K
Ionic crystals consist of two or more different kinds of ions that usually have different sizes. The packing of these ions into a crystal structure is more complex than the packing of metal atoms that are the same size.
Most monatomic ions behave as charged spheres, and their attraction for ions of opposite charge is the same in every direction. Consequently, stable structures for ionic compounds result (1) when ions of one charge are surrounded by as many ions as possible of the opposite...
15.5K
Crystal Field Theory - Tetrahedral and Square Planar Complexes02:46

Crystal Field Theory - Tetrahedral and Square Planar Complexes

45.1K
Tetrahedral Complexes
Crystal field theory (CFT) is applicable to molecules in geometries other than octahedral. In octahedral complexes, the lobes of the dx2−y2 and dz2 orbitals point directly at the ligands. For tetrahedral complexes, the d orbitals remain in place, but with only four ligands located between the axes. None of the orbitals points directly at the tetrahedral ligands. However, the dx2−y2 and dz2 orbitals (along the Cartesian axes) overlap with the ligands less than the dxy,...
45.1K
X-ray Crystallography02:18

X-ray Crystallography

24.4K
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...
24.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Large volume 'chunk' lift out for 3D tomographic analysis using analytical plasma focussed ion beam - scanning electron microscopy.

Micron (Oxford, England : 1993)·2026
Same author

Optimizing broad ion beam polishing of zircaloy-4 for electron backscatter diffraction analysis.

Micron (Oxford, England : 1993)·2022
Same author

Gazing at crystal balls: Electron backscatter diffraction pattern analysis and cross correlation on the sphere.

Ultramicroscopy·2019
See all related articles

Related Experiment Video

Updated: Oct 4, 2025

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
08:55

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses

Published on: June 7, 2018

8.6K

Effective structural unit analysis in hexagonal close-packed alloys - reconstruction of parent β microstructures and

Ruth Birch1, Thomas Benjamin Britton1,2

  • 1Materials, Imperial College London, London SW7 2AZ, United Kingdom.

Journal of Applied Crystallography
|February 11, 2022
PubMed
Summary

This study introduces a new computational tool called ParentBOR to analyze how zirconium alloys transform from a body-centred cubic to a hexagonal close-packed structure. The tool uses electron backscatter diffraction data to track how the final microstructure relates to the original structure. The algorithm was adapted from methods used in steel and is now open-source. It helps identify crystal orientation relationships and shared lattice directions within each grain. The study also compares this method with another tool called MTEX. The results show that the algorithm can accurately reconstruct the transformation history and help understand deformation properties. This work provides a new way to study microstructural evolution in zirconium alloys.

Keywords:
electron backscatter diffractionmicrostructureorientation relationshipsreconstructionhexagonal close-packed alloysmicrostructure analysiselectron backscatter diffractioncomputational materials science

Frequently Asked Questions

More Related Videos

Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
07:24

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

Published on: May 10, 2021

6.4K
Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography
11:48

Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography

Published on: April 24, 2018

14.9K

Related Experiment Videos

Last Updated: Oct 4, 2025

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
08:55

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses

Published on: June 7, 2018

8.6K
Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis
07:24

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

Published on: May 10, 2021

6.4K
Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography
11:48

Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography

Published on: April 24, 2018

14.9K

Area of Science:

  • Materials science and metallurgy
  • Crystallography and microstructural analysis
  • Computational materials modeling

Background:

Materials that undergo allotropic phase transformations often develop microstructures with orientation relationships based on transformation history. These relationships can impact mechanical properties. In zirconium alloys, a solid-state transformation from body-centred cubic (b.c.c.) to hexagonal close-packed (h.c.p.) occurs. This transformation follows the Burgers orientation relationship (BOR), linking the two phases. Prior research has shown that the crystallographic orientation of the h.c.p. α phase relates to the parent b.c.c. β phase. However, no prior work had resolved how to systematically reconstruct and analyze these relationships in zirconium alloys. This gap motivated the adaptation of existing reconstruction tools for use in this system. Existing methods, such as electron backscatter diffraction (EBSD), provide data but lack tools to fully interpret the transformation history. The lack of post-processing algorithms for h.c.p./b.c.c. systems limited the understanding of microstructure evolution. This paper introduces a new approach to address these limitations.

Purpose Of The Study:

This study aimed to adapt and apply a reconstruction algorithm originally developed for steels to zirconium alloys undergoing b.c.c. to h.c.p. transformation. The goal was to enable detailed analysis of crystal orientation relationships using EBSD data. The researchers sought to improve understanding of how the α phase forms from the β phase during transformation. They also aimed to release this algorithm as open-source software for broader use. The study focused on the Burgers orientation relationship (BOR) between the two phases. The researchers wanted to determine how variants of the h.c.p. α phase relate to the parent b.c.c. β grains. They also intended to compare their approach with existing tools like MTEX. The study's purpose was to provide a new computational method for analyzing transformation-related microstructures in zirconium alloys.

Main Methods:

The researchers adapted a reconstruction algorithm originally developed for steels to analyze EBSD data in zirconium alloys. This algorithm uses a Markov chain clustering approach to identify orientation relationships. The adapted code was released as open-source software called ParentBOR. The algorithm processes EBSD maps to reconstruct the parent β microstructure from the h.c.p. α phase. It identifies crystallographic variants of the α phase and their relationships to the β grains. The code also enables post-processing to determine shared crystal planes and lattice directions. The researchers compared their method with recently developed reconstruction tools in MTEX. The comparison focused on differences in how each method describes the microstructure and orientation relationships.

Main Results:

The adapted algorithm successfully reconstructed the parent β microstructure from the h.c.p. α phase in zirconium alloys. The code identified variants of the α phase and their crystallographic orientation relationships with the β grains. The algorithm enabled post-processing to determine shared crystal planes and lattice directions within each β grain. The results showed that the code could accurately track the transformation history of individual grains. The researchers demonstrated that the algorithm can be used to analyze deformation properties related to the transformation. The code was compared with MTEX tools, revealing similarities in microstructure description but differences in implementation. The comparison highlighted how each method captures orientation relationships differently. The open-source nature of ParentBOR allows for further development and application in similar materials.

Conclusions:

The study concludes that the adapted reconstruction algorithm can effectively analyze orientation relationships in zirconium alloys undergoing b.c.c. to h.c.p. transformation. The researchers propose that this method can improve understanding of transformation-related deformation properties. The open-source release of the code enables broader application in materials science. The comparison with MTEX tools revealed differences in how each method describes the microstructure. The study suggests that the algorithm can be used to analyze shared crystal planes and lattice directions. The results support the use of the algorithm for post-processing EBSD data in zirconium alloys. The researchers propose that the method can assist in understanding the microstructural evolution during phase transformations. The study highlights the importance of computational tools in analyzing complex microstructures.

The BOR links the crystal orientations of the h.c.p. α phase to the parent b.c.c. β phase in zirconium alloys. This relationship is used to track transformation history and microstructure evolution.

ParentBOR uses a Markov chain clustering algorithm adapted for zirconium alloys, while MTEX employs different computational approaches. The study compares how each tool describes orientation relationships.

Shared planes and directions help identify transformation patterns and deformation mechanisms in the final microstructure. This analysis is key to understanding mechanical behavior.

EBSD data provides crystallographic information about the α and β phases. The algorithm processes this data to reconstruct the parent β microstructure.

The open-source release allows researchers to apply and improve the algorithm for other materials. It promotes transparency and collaboration in microstructural analysis.

The study may assist in optimizing microstructure design for improved mechanical properties in zirconium alloys. It provides tools to better understand transformation-related deformation.