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Digital Image Correlation of 2D X-ray Powder Diffraction Data for Lattice Strain Evaluation

Overview of attention for article published in Materials, March 2018
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Article details
Title
Digital Image Correlation of 2D X-ray Powder Diffraction Data for Lattice Strain Evaluation
Published in
Materials, March 2018
DOI 10.3390/ma11030427
Pubmed ID
Authors
Abstract

High energy 2D X-ray powder diffraction experiments are widely used for lattice strain measurement. The 2D to 1D conversion of diffraction patterns is a necessary step used to prepare the data for full pattern refinement, but is inefficient when only peak centre position information is required for lattice strain evaluation. The multi-step conversion process is likely to lead to increased errors associated with the 'caking' (radial binning) or fitting procedures. A new method is proposed here that relies on direct Digital Image Correlation analysis of 2D X-ray powder diffraction patterns (XRD-DIC, for short). As an example of using XRD-DIC, residual strain values along the central line in a Mg AZ31B alloy bar after 3-point bending are calculated by using both XRD-DIC and the conventional 'caking' with fitting procedures. Comparison of the results for strain values in different azimuthal angles demonstrates excellent agreement between the two methods. The principal strains and directions are calculated using multiple direction strain data, leading to full in-plane strain evaluation. It is therefore concluded that XRD-DIC provides a reliable and robust method for strain evaluation from 2D powder diffraction data. The XRD-DIC approach simplifies the analysis process by skipping 2D to 1D conversion, and opens new possibilities for robust 2D powder diffraction data analysis for full in-plane strain evaluation.

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Mendeley demographics

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The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 9 19%
Researcher 9 19%
Student > Master 3 6%
Other 2 4%
Student > Bachelor 2 4%
Other 3 6%
Unknown 19 40%
Readers by discipline
Readers by discipline Count As %
Materials Science 9 19%
Engineering 5 11%
Chemistry 3 6%
Physics and Astronomy 2 4%
Unspecified 1 2%
Other 2 4%
Unknown 25 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 March 2018.
All research outputs
#20,722,728
of 23,322,258 outputs
Outputs from Materials
#6,333
of 8,011 outputs
Outputs of similar age
#295,811
of 334,585 outputs
Outputs of similar age from Materials
#114
of 143 outputs
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