Hi Yang, There are many reasons why you would prefer your first-shell fit to have your fit include high-k data, when feasible. I’ll name one, just to give you the idea:
Suppose you have a substance where you have a good estimate of S02 (transferability from a similar substance measured under the same conditions), but you don’t know the first-shell coordination number or sigma^2. Coordination number and sigma^2 are correlated, since they both primarily affect the amplitude of chi(k), but they are not completely correlated, as the coordination number has the same effect across the entire k-range, wherease sigma^2 has a much greater effect at greater k (in the EXAFS equation, it’s weighted by k^2). So extending the fit up to higher k reduces the correlation between coordination number and sigma^2, which can be very important to understanding the structure of your material. Of course, there are other ways to reduce that correlation, such as by measuring a series of spectra at different temperatures. But it does provide a good example of why high-k information is useful when you can get it. Best, Scott Calvin Lehman College of the City University of New York > On Aug 30, 2021, at 4:32 PM, Hu, Yang (HIU) <yang...@kit.edu> wrote: > > 3) For fitting the 1st and 2nd shells, I still lack of clear understanding > how the high-k portion can influence. If I measure a set of samples, and one > of them has much noisy data so a shorter k-range is picked up for background > subtraction and FT. In this case, can I still consider the change or > evolution in the fitted parameters “systematic”? >
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