Re: Fwd: Re: Re: problem about negative
On 11/11/2014 10:19 AM, Bruce Ravel wrote:
> Rbkg>1.1 can avoid the first peak,but the remaining curve is somewhat
> not smooth.How to distinguish whether a long wavelength oscillation
> appear as a real peak or false one?I am confused about it.
> I find when I avoid the first scattering peak after white
> line(kmin=4.8 maybe too large),the first peak of R space
> disappeared.Because usually the first scatering peak is related to the
> first coordiantion shell,can I think the first peak in R space less 1A
> is a real peak instead of noiseï¼
As I said yesterday, I don't know anything about your sample, so it is
hard for me to know what the "right" answer is to your problem. But I
can make some observations and some suggestions.
* Your data range is really short. As you seem to have noticed
(judging from the very short k-range in your project file), your data
has serious systematic problems starting at 9 or 10 inverse Angstroms.
I cannot quite tell, but your data appear to be transmission data. Well
it is possible that you have some instability or nonlinearity at the
beamline, I would guess that your sample is not very homogeneous. It is
possible that more disciplined sample preparation might help extend that
range of the interpretable data.
* You are right that slightly increasing the Rbkg value seems to make
a positive difference in the extracted chi(k) data. Your data seem to
be an example of the sort of data I was alluding to yesterday. The
background subtraction is difficult because it is difficult to
distinguish the Fourier components of the background function from the
Fourier components of the data. I think that the background subtraction
with Rbkg=1.1 looks much better than with Rbkg=1.0, but given how
different they are, you have to be concerned about the correlations
between the background and the parameters of the data.
It is clear that your data are of the sort for which background
subtraction is difficult. So how do you know what is an acceptable
Well, using only Fourier methods, I think we have demonstrated that you
cannot know the right answer without some kind of prior knowledge.
So, how do you get that prior knowledge?
Well, my advice is to first solve some simpler problems. Measure your
Measure the common forms of moly oxide and moly sulfide. Measure moly
metal. Analyze all of them. The advantage of the standards is that you
know what the answer should be. Do the data processing and data
analysis. Make sure that, when you do the analysis, you get the right
Having done that exercise, you will then have a lot more knowledge about
what the various forms of moly oxide look like and what the challenges
are when doing the data processing and data analysis.
- Are there any forms of moly oxide for which the bond length is as
short as 1.6? If so, do the conditions of formation exist in your
system? Is your sample of a valence consistent with the valence of the
Mo when it has such a short bond?
- If you convince yourself that it is possible for moly to have an
oxygen atom at 1.6 or 1.7, what did you have to do with your standard to
get a sensible analysis of the EXAFS data? Hopefully, that will guide
you to doing a sensible analysis of your unknown sample.
- If none of your moly oxide standards have an O atom at 1.6 or 1.7,
why do you think it is chemically reasonable for your unknown sample to
have such a short bond? If, in fact, that short bond doesn't exist
elsewhere in nature, why would your sample magically have such a short bond?
- If you do not believe in such a short bond, then does your
experience with the standards give you the confidence to increase Rbkg
such that the low-R signal is removed by the background function?
I completely understand that you have a compelling reason to understand
your unknown sample and that I am suggesting that you spend a good chunk
of time measuring and analyzing a bunch of standards that are not your
actual research project. That might seem like time that takes you away
from your real goal, but you have already demonstrated that you are
stumped by your real goal. I am saying the only way to get over your
current hurdle is to take a step back and gain a deeper understanding of
the data, the physics of EXAFS, the methods of EXAFS analysis, and the
intricacies of your current problem.
Bruce Ravel ------------------------------------ bravel <at> bnl.gov
National Institute of Standards and Technology
Synchrotron Science Group at NSLS --- Beamlines U7A, X24A, X23A2
Upton NY, 11973
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