Hi folks,
I am trying to measure the dislocation density using XLPA. I am dealing with Ni superalloys. To calculate dislocation contrast factor, I need to calculate the value of q which describes the dislocation's character. The problem is I am getting values of q which are greater than the theoretical values. For screw and edge type dislocations, the theoretical values of q are 2.26 and 1.42, respectively. The experimentally obtained values of q are greater than 3 (3.11 to 3.33). I am stuck in the middle. I have carefully measured the FWHM of the diffraction peaks.
Any comment is highly appreciated.
Does XLPA refer to x-ray line profile analysis? That is not a single thing! That's like saying "my tool does not work for taking my car apart" - what analysis are you actually using? How are you calculating q? Please tell us HOW you "have carefully measured the FWHM of the diffraction peaks;" do expect us to just trust that you must have done that right since you were "careful." What equation are you use to fit your peaks? What are you using for your instrumental broadening standard? Does your instrumental broadening standard have peaks fit well to the same equation as your sample? Which method for correcting for instrumental broadening are you using?
Also, the term is "Ni base superalloy," not "based."
Yes, XLPA refers to X-ray Line profile analysis which is already mentioned in the subject line in bold fonts.
Sorry, if my question was less informative.
I believe the only available method for contrast factor determination is the one given by Prof T. Ungar (I don't know if there is any other method available).
I have used Origin 8.5 platform to fit the diffraction peaks using voight function.
Instrumental broadening was measured using standard Ni powder.
Yes, the peak profile fittings for the Ni standard were done using Voight function which showed best fit (If you believe me).
Thanks for correcting me (Also, the term is "Ni base superalloy," not "based."). In that way you are also pointing to Prof Bhadeshia, University of Cambridge.
Thank you very much for your time.
When you say Voight, do you really mean Voigt or pseudo-Voigt? Sure I believe you got a good fit, but what I'm doubting (becuase almost nobody pays any attention to it) is that you subtracted the instrumental broadening correctly. Here's why its an issue:
When both instrumental and sample peaks are Cauchy, the total breadth is:
B_observed = B_instrument + B_sample
When both instrumental and sample peaks are Gaussian, the breadths add as:
(B_observed)^2 = (B_instrument)^2 + (B_sample)^2
Or did you really do a deconvolution? The above differ because the observed peak is a convolution of the instrumental and sample functions.
Now if you're fitting to a Voigt or pseudo-Voigt, you should know that it is a combination of Cauchy and Gaussian functions (convolution or sum, respectively). So, when you fit to a Voigt or pseudo-Voigt, you are fiting to different functions each time. Unless your fit shows that you have pure Cauchy or pure Gaussian (or you are really doing a true deconvolution), it is not at all clear how you should subtract the instrumental broadening. So please tell us,
Do you really fit to Voight?
Do you really use deconvolution to remove instrumental broadening? If so, this is great, and you are very uncommonly careful, and please forgive my not assuming this is the case.
If you fit to pseudo-Voigt, is the mixing parameter equal to zero or one for both the standard and the sample? If so, you can use one of the above equations. Does the mixing parameter have the same value for both sample and standard? If not, your adjusted FWHM for the sample is an approximation that may be substantially in error. That will affect everthing else.
You have to scan the standard reference material (SRM) for the instrumental broadening. Fit the entire pattern with software, get the broadening function of ur instrument, fix it then fit your sample with the contribution of dislocation density as predicted. Avoid individual or manual fit as you can see in attached file (WPPM).
PM2K a program implemented Whole Powder Pattern Modelling is the software that could do the task. Contact Prof. Matteo Leoni ([email protected]) or Prof. Paolo Scardi ([email protected]) to get the software. The interface is easy and straight forward. Find attached files for more information.
The Lectures by Tamas Ungar himself on XRD line profile analyses at IIT-Kanpur!
https://www.linkedin.com/groups/2683600/2683600-6297853435559575554
https://www.youtube.com/watch?v=k15_P6JFQxw
https://www.youtube.com/watch?v=kGQb8EiSQAw&t=78s
https://www.youtube.com/watch?v=qtl9qAFPUrA
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