Hi Matt, thanks for the videos, Larch is pretty nice. I would like to understand more about the k-weight in the R-space, any suggestions about it? Best regards.
@eugenesys I am not sure that I understand the question. When doing a Fourier transform for EXAFS data, one typically multiplies chi(k) by k^n which typically called "k-weighting". It does alter the Fourier transform chi(R), but in a predictable way. Common values for n are 1, 2, or 3. When doing background subtraction, we do use a Fourier transform to separate low and high R-regions (with Rbkg being the cutoff). Since we are doing a Fourier transform, we can pick a k-weight, but for background subtraction using n=0 or 1 usually works best, and using n=2 is rarely better than n=1.
Hi Matt, thanks for the videos, Larch is pretty nice.
I would like to understand more about the k-weight in the R-space, any suggestions about it?
Best regards.
@eugenesys I am not sure that I understand the question. When doing a Fourier transform for EXAFS data, one typically multiplies chi(k) by k^n which typically called "k-weighting". It does alter the Fourier transform chi(R), but in a predictable way. Common values for n are 1, 2, or 3.
When doing background subtraction, we do use a Fourier transform to separate low and high R-regions (with Rbkg being the cutoff). Since we are doing a Fourier transform, we can pick a k-weight, but for background subtraction using n=0 or 1 usually works best, and using n=2 is rarely better than n=1.
@@MatthewNewvilleThanks! Ok got it.
I misunderstood there is a correlation between the atomic number of the atoms and the k-weight.