Determination of Crystal Structures
X-ray Crystallography
X-ray Diffraction of Biological Samples
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Updated: Jun 1, 2026

Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography
Published on: April 24, 2018
1The Australian Centre for Microscopy & Microanalysis, The University of Sydney, Sydney, NSW 2006, Australia.
This study explores ways to improve the accuracy and efficiency of measuring crystal orientation relationships in materials using electron microscopy. Current methods can struggle when specimen thickness or Kikuchi line quality is poor. The researchers revisited a technique called systematic tilting in transmission electron microscopy and introduced a new post-processing workflow. They tested different algorithms and found that least-squares fitting and singular value decomposition provided the best results. These methods were validated using known orientation relationships in TiAl intermetallics and dual-phase stainless steels. The study suggests that these algorithms can replace traditional methods in challenging cases and improve the reliability of orientation relationship measurements.
Area of Science:
Background:
Understanding grain boundary structures is central to materials science. Prior research has shown that electron diffraction methods can determine crystal orientation relationships. However, these methods often require manual intervention when specimen thickness or Kikuchi line quality is poor. No prior work had resolved how to systematically improve accuracy and efficiency in such cases. This gap motivated researchers to explore alternative post-processing strategies. Existing solutions lack adaptability in complex microstructures. That uncertainty drove the need for a more robust workflow. The challenge lies in balancing accuracy with practical usability in TEM. This study aims to address these limitations through algorithmic refinement.
Purpose Of The Study:
The goal of this research is to enhance the measurement of crystal orientation relationships using TEM. The specific problem involves improving angular accuracy and processing efficiency for grain boundary analysis. The motivation stems from limitations in current methods when specimen conditions are suboptimal. The study focuses on refining post-processing algorithms for electron diffraction data. It seeks to provide a reliable alternative when traditional methods fail. The approach centers on algorithmic comparison and validation. The study aims to streamline data processing in materials characterization. It also aims to reduce manual effort in OR determination.
Main Methods:
The study revisits the systematic tilting method in TEM for orientation relationship measurement. Researchers employed post-processing algorithms to refine data accuracy. They evaluated least-squares fitting and singular value decomposition approaches. Normalization was also tested for its practicality in on-site settings. The workflow was applied to known orientation relationships in intermetallics and steels. Data processing was validated using TiAl twin OR and Kurdjumov-Sachs relationships. The methods involved comparing algorithmic outputs against established benchmarks. The study focused on workflow efficiency and angular precision metrics.
Main Results:
Least-squares fitting and singular value decomposition algorithms showed superior angular accuracy. These methods outperformed normalization in precision and reliability. The normalization approach provided acceptable accuracy but with limited precision. Validation was conducted using TiAl intermetallics and dual-phase stainless steels. The TiAl twin OR was measured at [110]/69.5° with high accuracy. The Kurdjumov-Sachs OR between austenite and ferrite was also validated. The proposed workflow improved both accuracy and processing efficiency. The results suggest these algorithms can replace traditional methods in challenging cases.
Conclusions:
The authors propose that least-squares and singular value decomposition algorithms enhance OR measurements. These methods provide higher accuracy than normalization approaches. The workflow was successfully validated on known orientation relationships. The study suggests these algorithms can be used when traditional methods fail. The results support the use of post-processing to improve TEM data analysis. The authors emphasize the importance of algorithmic refinement in materials characterization. They suggest that these methods can streamline OR determination in complex specimens. The findings imply that these algorithms offer a practical alternative for routine use.
The study validated the [110]/69.5° twin OR in TiAl and the Kurdjumov-Sachs OR in dual-phase stainless steels.
Least-squares fitting and singular value decomposition algorithms demonstrated superior angular accuracy.
Normalization provided acceptable accuracy but lacked the precision of LS and SVD methods.
The workflow was tested using known orientation relationships in TiAl intermetallics and dual-phase stainless steels.
Systematic tilting improves angular accuracy in orientation relationship measurements.
The study suggests post-processing enhances both accuracy and efficiency in OR determination.