The study of the peaks produced by X-ray diffraction and their shapes is a well- developed and valuable method for the study of the microstructure of crystalline materials. This technique, which I refer to as Diffraction Peak Profile Analysis (DPPA), is principally used to find the crystal or subgrain size, the dislocation density and the slip systems present in a metal (Kuzel 2007, Ungar 2003, Warren 1969). DPPA is a statistical method, because it uses information from a single diffraction pattern, which consists of information from many grains. From this pattern a DPPA method quantifies the microstructure of a sample.
To be able to do this it is necessary to make approximations as to how the peaks should broaden by different defect microstructures. The accuracy of these approximations is fundamental as to whether the technique works. However, there is a difficulty in verifying the results by other methods, which means there is an inherent ambiguity in the results. The only parameters that are adequately measured by both DPPA and other methods are the dislocation density and the crystal size. For the dislocation density the results show agreement (Gubicza et al. 2006). Whereas for the crystal size, the values agree for un-deformed samples (Ungar 2003), but for deformed samples the values from DPPA are most often less than found by other methods (Ungar 2003, van Berkum et al. 1994, Kuzel 2007). This discrepancy in crystal size results has led some to believe (van Berkum et al. 1994) that the methods produce systematic errors because of the assumption in their mathematical equations.
One of the main assumptions made is that deformation is homogenous, which means that any differences in the deformation of a grain are random. In order to describe the different broadening of different diffraction peaks (with different hkl indices), an equation called the contrast factor of dislocation has been introduced (Ungar and Tichy 1999, Dragomir and Ungar 2002). This equation can then be used to find information about the dislocations present such as the quantity of edge dislocations, or the amount of a dislocation type (e.g. the amount of <c+a> dislocations). However, there are often systematic differences in the deformation of individual grains in a metal based on its orientation (Taylor 1934, Zaefferer 2003, Bridier et al 2005, Dilamore et al. 1972). A method developed by Borbely and colleagues (Borbely et al. 2000) accounted for this heterogeneity by predicting the different slip systems active in different grains, and hence calculating the contrast factor. The approach has had no use to the author’s knowledge, other than by Borbely and colleagues. Hence, further investigation of the approach is needed since it would lead to different results than the contrast factor equation.
DPPA literaure review from my thesis
Thomas Simm: DPPA is potentially a nice technique, but it's also a black hole you may never escape from. It's also a good example of a technique that can be used to prove whatever you want it to. I'm always on the look out for collaborations- as this technique is my unwanted child that I both love and hate but can't get way from.
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