, and is not completely reversible. I see a factor of 1000
as a multiplicative factor in the Energy Text Control window when "keV" is
selected, but this appears to not be editable.
I also see that this only happens when using the Larch backend and not the
Ifeffit backend. And, I ca
similar to the one reported in March 2018 under the
> topic "Athena (Demeter 0.9.26) does not import all datapoints from ascci
> file". However, the issue I am seeing always results in 1.2eV steps in
> the imported data. If my original file hast 0.3eV steps, the number of
> po
of measurement you are
making (transmission, fluorescence). All of these factors can masquerade
a amplitude reduction factor.
What I do in practice is to measure a standard which has the same local
environment and fit the EXAFS with the known structure to extract an S02
which I then use
of measurement you are making
(transmission, fluorescence). All of these factors can masquerade
a amplitude reduction factor.
What I do in practice is to measure a standard which has the same
local environment and fit the EXAFS with the known structure to
extract
ability to
normalize properly, you're unlikely to account for a factor of 2 by
normalization if the data is relatively decent. And self-absorption tends to
suppress S02, not exaggerate it.
Why did you switch to fluorescence on just the handful of data sets? That might
provide us a clue.
--Scott
is only showing the fit results in
the top of the results window: Later where a summary is usually shown it
is left blank:
R-factor for this data set = 0.46013
pathdegen amp sigma^2e0reff delta_RR
work, I got it to the point that the fit looks pretty (R-factor<0.02), but I
have several reservations about it:
1) Generally, the ss values are all higher than I would like. 0.007 even
seems high to me for a metal-O bond. Am I right about this? Would this indicate
that this may have b
I was installing it only to
get the possibility to actually use the user-supplied value of epsilon_k
for fitting multiple dataset. If it is difficult to make the version
0.9.26 available soon, maybe in 0.9.25 there is a possibility to set
R-factor as a figure of merit for fitting rather than chi^2? That
error bar. Also, the R factor for fit "B,D,E" is barely different from
those above, which further suggests that those two are not actually in
your sample.
What happens if you exclude those two from the combinatorial fit? Do
you see the same error message?
What happens if y
distances from such an analysis is to assert that the difference between
the path is a fixed value and thus refine the two paths with the same delta R
(and probably the same debye wller factor) this in my experience works in some
cases
Best regards
Fred Mosselmans
-Original Message-
From
Hi Neil:
I took your data and fit it with the Co(OH)2 structure but only the first
two paths: Co-O and Co-Co. I used a k-range of 2-10 and dk=3 and the
r-range of 1-3.5 with dr=0.2. The fit results are as follows
R-factor= 0.024528565
Guess parameters
:
>
>> Hi Matt, thank you for your answer!. The references I have about
>> Malinowski´s work and some applications are:
>>
>> Malinowski, E.R., *Theory of error in factor analysis.* Analytical
>> Chemistry, 1977. *49*(4): p. 606-612.
>>
>> Malinowski, E
for the most recent fit but, for the previous fit it will have
been overwritten by the newer fit. Some of the other info, such as
R-factor by k-weight seems to get overwritten too.
I just pushed a fix for this to github and posted new windows installer
candidates at
http://bruceravel.github.io
that as the first
two S subshells are so close to each other, my data can't identify them
(delr and ss) independently. So I defined their delr and ss to be same and
the
results match pretty well with the cubic phase. The r-factor and reduced-chi
square with the two models are very similar.Thanks a lot !
On Sun
in an anticipation
Best
Pushkar
Independent points : 16.125
Number of variables : 4
Chi-square : 7324.9401796
Reduced chi-square : 604.118
R-factor: 0.0195782
Measurement uncertainty (k) : 0.0001264
Measurement uncertainty (R) : 0.0004142
Hi Matt,
Thank you for your answer and for taking time to explain me basic things again
and again.
I have completely different question as well, and hopefully the last one for a
while: I just started using Artemis, and have a question regarding the
amplitude reduction factor: I use
Good afternoon
I understand. In that case, would it be possible for you to perhaps guess
the greatest factor causing this problem? My apologies if I may be asking
for too much.
Yours sincerely
Deepak Varanasi
On Sun, Sep 13, 2020, 16:39 Deepak Varanasi wrote:
> Good afternoon
>
> T
f the Vogt–Mizaikoff F-test to determine the number of
principal factors responsible for a data matrix and comparison with other
popular methods. Journal of Chemometrics, 2004. 18(9): p. 387-392) is
stated that s is equal to r or c, wichever is smaller, in this case s=c,
the number of spectra as you said.
Y
Hi Scott,
That's a pretty amazing use case.
But I'm not sure I understand the issue exactly right. I would have
thought the volume (r**3) was the important physical parameter, and
that a 1000nm particle would dominate the spectra over 3nm particles.
Or is it that you are trying
oint is so
important that I want to yell it at you.
THE FOURIER TRANSFORM OF CHI(K) IS NOT A RADIAL DISTRIBUTION FUNCTION.
* chi(k) includes multiple scattering
* chi(k) includes a complex scattering factor
* For heavy elements, the magnitude of the complex scattering factor
has a lot of
t higher k than normal (perhaps 4 or 5 Ang^-1) or increasing the k-weight
used in the Fourier transform (perhaps to 3 or 4) would de-emphasize the
Se-Li scattering to a level that it was safe(r) to ignore.
FWIW, I would imagine that trying to fit coordination number or sigma^2 for
Se-Li at per
, without any restraint. While I restrain the DW to 0.005, my CN
jumps from 4.8 to 5.2.
When I make a cluster based on Yttria structure, I get DW factor of
0.008 +- 0.002, unrestrained. While I restrain the DW to 0.01, it
again jumps from 4.8 to 5.2.
First query...if you can pin down on the CN change
occupation
factors to be equal to 12 provided that you have a reasonable
understanding of what the amplitude reduction factor might be. You can
also start by constraining the delta R and sigma-squareds for the two
paths until you are sure that the fit makes sense and is stable.
If you have data
,
there will be a number of really nice options out there. For example,
ringtones for a really bad fit should be made very unpleasant, and even more
so, when Delta E0 is out of bounds, or r-factor is greater than 0.02..
Anatoly
-Original Message-
From: ifeffit-boun...@millenia.cars.aps.anl.gov
, 2011, at 7:58 PM, Jeff Terry wrote:
Did not try really hard to work with it.
Fitting Data as norm(E) from -20.000 to 30.000
Fit included 98 data points and 3 variables
R-factor = 0.000263
chi-square = 0.04347
reduced chi-square = 0.0004482
groupweight
Something is horribly wrong with the data here.
I overplotted your reference Au foil against mine, and yours has distorted
XANES and too high EXAFS intensity compared to my data. Your amplitude factor
is 1.54 which also confirms that something was wrong in the experiment. Perhaps
with the 4th parameter no fit at all
takes place. The errors in the GDS-window are exactly 0.0 with no fit
taking place (enot = 0, amp = 0 (guess amp = 1) delr = 0 and ss = 0.003)
and the R-factor of the fit is way over the top (10^20).
I've chosen a value of 0.5 for the 3rd and the 4th
only two variables in fitting
parameteres are needed 1) Radius 2) amplitude reduction factor (SO2)
I think I have understood the basic concept as to why the amplitude is
reduced and somehow we need to increase the number N of number of
paths/number of atoms in the cluster so that the amplittude
M, N, O, and P core levels with binding energies less
> than 1500 eV in approximately 25 elements. The results show that the
> framework provided by previously accepted theoretical estimates of
> lifetime broadening is sometimes misleading. Lifetimes derived from
> theory
ersion "Artemis 0.9.26" I have two
> problems. (1) The fitting Range was reported to be a error that the Rmin
> should be larger than the Rkbg value. It makes that the fitting range cannot
> be smaller than 0.9 (the Rkbg value is 0.9). (2) When Fitting the
> Debye–Waller fa
the Fourier transform (perhaps to 3 or 4) would de-emphasize the
> Se-Li scattering to a level that it was safe(r) to ignore.
>
> FWIW, I would imagine that trying to fit coordination number or sigma^2
> for
> Se-Li at percent-level concentrations would not work very well. If yo
^2 chi(k) vs. k is plotted. I don't
understand this context because there is no chi in the approximation for
the Debye-Waller factor. Where comes the chi here?
chi(k) is proportional to e^(-2 sigma^2 k^2), where sigma^2 is the
mean-square-displacement in the bond length R to the neighboring atom
, and for the K-B window i tried different dk's from 1-5.
The kmin and kmax were held constant at 2.5-11. I did notice the large
increase in ringing with the low dk values and the K-B window. The fit
quality, by R-factor, was substantially worse with the K-B window regardless
of the dk value. I will probably
a change in
epsilon.
In playing around with different windows and dk values my fit variables
generally stayed within the error bars, but the size of the error bars could
change more than a factor 2. Does this mean that it would make sense to
find a window/dk that seems to work for a given group
be dominated by the rapid decay
in |chi(k)|, rather than a change in epsilon.
I'm confused. We Fourier transform k-weighted data. Since Ifeffit uses the
high-R amplitude to estimate uncertainty, it seems to me that what matters
is signal-to-noise, not just noise in the original unweighted chi(k
list below, then, gives a result of 0.64, which indicates
such variation is quite likely to have taken place by chance.
You chose the worst case of your three, though; the pH 3 case. The pH 10 case
shows the most improvement in the R-factor with x = 0.007/0.012 = 0.58. The
probability of getting
e most improvement in the R-factor with x = 0.007/0.012 = 0.58. The
probability of getting that much improvement by chance drops to 0.30—less
likely, but still pretty close to a coin flip.
Even the fact that you got all three to show improvement doesn’t quite reach
the 95% confidence level, althoug
:
Bruce,
Perhaps you noticed the Fit color was red (large R-factor 0.074496,
poor fit, also seen in the attached figure in the last email) when you
loaded in the project file I sent you. When you hit Fit button again the
Fit color might turn to green indicating good fit as shown in your
result
hello
Two phase can be mixed in ZnS. You need to check r-factor and reduced-chi
squrare with two model.
If you want to fit only first shell,
I suggest.
first use cubic zinc-blende model in FEFF, and check goodness of fit.
second, fix the bond length of 3 bonding length and change the bond
. We would like to publish a qualitative XANES
paper and an EXAFS paper. Any suggestions on the type of information
(plots, tables, R-factor, etc.) that should be included in each paper
separately would be appreciated.
Was this the page you were looking for?
http://xafs.org
.
As you can see, the fit contains four paths. They are all single scattering paths,
and the paths with the four largest ranks according to feff. All paths share the
same SO2 and deltaE. Each path has its own delR and ss. After some work, I got it
to the point that the fit looks pretty (R-factor
Hi Carlo
Thank you for your answer. I have completely different question as well: I
just started using Artemis, and have a question regarding the amplitude
reduction factor: I use different So^2 for different elements, correct? If I
start fitting and have paths involving the same kind of atom
atom of Co, you can also calculate the volume fraction in a
cubic centimeter of material.
To do so, you need to firstly obtain the (short-ranged) lattice parameter (in
angstrom) of each phase from an EXAFS fitting with an R-factor less than 0.02.
Then the volume (in angstrom cube) of the unit ce
neighbors and the other -
4, and if you choose the site with 4 neighbors to construct FEFF to model
your EXAFS data; and if you set your degeneracy equal to 4 and make your
amplitude factor as S02*x of one site + S02*(1-x) of another site, then
your S02 will come out larger than it should be because
One possible scenario: If one site has 6 nearest neighbors and the other - 4,
and if you choose the site with 4 neighbors to construct FEFF to model your
EXAFS data; and if you set your degeneracy equal to 4 and make your amplitude
factor as S02*x of one site + S02*(1-x) of another site
.
In looking at the structures of Al2O3 and Y2O3, I noticed a couple of
interesting issues. The first shell in the Al2O3 structure is
# Atom R
3 O 1.8519
3 O 1.9717
The Y2O3, however seems to have two diffente Y sites, and the first shells
are
Site 1
large compared with the R from literature. But if I force sigma^2 to
be positive and e_2 to be below 10 ev, the R-factor will increase and the
fitting doesn't seem good.
As for the 2.59 Angstrom for equatorial U-O, it is even a little bit larger
than the bidentate U-O. I don't think it resonable
- and R-
dependence? Because S02 is not a simplistic parameter which may
include both theory and experimental effects, I feel that S02 is not
necessarily to be smaller than 1, although I admit S02 smaller than 1
is more defensible as it represents some limitations both in theory
model
Yanyun,
The so2 also has a correlation with the Debye factor as well. You should also
look at that parameter in the fits you've done.
Chris
Sent from my iPhone
On Mar 20, 2015, at 3:46 PM, huyan...@physics.utoronto.ca wrote:
Hi Scott,
Thank you so much for giving me your thought again
Hi Matt, thank you for your answer!. The references I have about
Malinowski´s work and some applications are:
Malinowski, E.R., *Theory of error in factor analysis.* Analytical
Chemistry, 1977. *49*(4): p. 606-612.
Malinowski, E.R., *Theory of the distribution of error eigenvalues
resulting
below, then, gives a result of 0.64, which indicates
such variation is quite likely to have taken place by chance.
You chose the worst case of your three, though; the pH 3 case. The pH 10 case
shows the most improvement in the R-factor with x = 0.007/0.012 = 0.58. The
probability of getting that muc
a more reasonable variation to me. But maybe I'm being
tricked by the fact that you have a split first shell and the MSRDs
are not supposed to be very similar...
I would also suggest opening the r-window to the right side a little
bit. (By the way, that bump in the FT at ~ 1 Angstrom seems
Dear Debora,
we have done some temperature-dependent EXAFS measurements on nanoparticles
(NPs) and analyzed the data through multiple dataset fits, as published in:
L.L. Araujo et al., Physical Review B 78, 094112, 2008.
R. Giulian et al., Journal of Physics: Condensed Matter 21, 155302, 2009.
P
@millenia.cars.aps.anl.gov
Subject: [Ifeffit] What you see is not what you get: help
Hi folks,
I´ve been working on Xanes peaks fitting with Athena (last version) and I
found a strange behaviour. I get a good fit looking to the Graphics
Window of Athena and to the minimized parameters (R
-Waller factor in XRD, because the first
is the variance in the interatomic distance, and the second is the
variance in the atomic position relative to a lattice point.
But what about the lattice parameter implied by the nearest-neighbor
distance in EXAFS as compared to the lattice parameter
the Debye-Waller factor in XRD, because the first
is the variance in the interatomic distance, and the second is the
variance in the atomic position relative to a lattice point.
But what about the lattice parameter implied by the nearest-neighbor
distance in EXAFS as compared to the lattice
published.
It's well known that the MSRD (sigma squared) for EXAFS differs
substantially from the Debye-Waller factor in XRD, because the first is
the variance in the interatomic distance, and the second is the variance in
the atomic position relative to a lattice point.
But what about the lattice
of the
covarience matrix. Those need not be scaled and aren't.
The formulas for chi-square, reduced chi-square, and the R-factor are
given on pages 16 and following of this postscript file
http://cars.uchicago.edu/~newville/feffit/feffit.ps
My own take, for what it's worth, on all
good reduced
chi square value, / good R Factor values) but shows the following, as an
example:
Standard Weight E0
X 0.267(0.056) 0
Y 0.249 (0.017) 0
M 0.220 (0.015) 0
N
EXAFS LCF. To choose from the combinations after fitting is diffcult
because the R factor of the first 5 combinations with diffrent reference
combinations is similar. And as I see from my fitting the alignement plays
really an important role on the LCF. You know when I made allign marked
groups
XANES and too high EXAFS intensity compared to my data. Your amplitude factor
is 1.54 which also confirms that something was wrong in the experiment. Perhaps
- a misalignment? The NP data also look strange...
I would not focus on the NP analysis until you figure out why your foil data is
so
standards
library
- using fit all combinations and I will get all the different fit results
from the best to the worst.
However, it appears that the result given by fit this group does not
correspond to the best fit given by fit all combinations (it often
corresponds to a higher R factor fit
Hello IFEFFIT users,
Sorry, I used the wrong values I should have set the delta r value,
Sorry again,
Ditty
On Wed, Apr 30, 2014 at 2:05 PM,
ifeffit-requ...@millenia.cars.aps.anl.govwrote:
Send Ifeffit mailing list submissions to
ifeffit@millenia.cars.aps.anl.gov
To subscribe
. The errors in the GDS-window are
exactly 0.0 with no fit taking place (enot = 0, amp = 0 (guess amp =
1) delr = 0 and ss = 0.003) and the R-factor of the fit is way over the
top (10^20).
I've chosen a value of 0.5 for the 3rd and the 4th parameter just to see
if they're working and I
Hi,
One thing that could be considered is transferring the SO2 factor from a
reliable source such as a standard and then use that value in the fit. Chemical
transferability of SO2 to similar systems is often acceptable. You could also
try constraining the value in the fit as well. SO2
is transferring the SO2 factor
from a reliable source such as a standard and then use that value in
the fit. Chemical transferability of SO2 to similar systems is often
acceptable. You could also try constraining the value in the fit as
well. SO2 and Debye are also correlated so this may
: [Ifeffit] phase problem copper
On 07/14/2015 10:18 AM, Neeb, Matthias wrote:
I have a standard exafs spectrum of copper K-shell and everything
looks as expected (Chi(E), Chi(k), Chi(R), Chi(q) ...) when using
Demeter 0.9.21 .
However the phase spectrum of (Chi(q)) appears quite different
lation.
Standard deviation missing in cell constants.
Structure calculated theoretically.
Structure type : Auricupride-AuCu3.
No R value given in the paper.
At least one temperature factor missing in the paper.
2-Thetad(Å) I(f) ( h k l) Theta 1/(2d) 2pi/d n^2
21.706 4.0910 95.4
dataset. If it is difficult to make the version
0.9.26 available soon, maybe in 0.9.25 there is a possibility to set
R-factor as a figure of merit for fitting rather than chi^2? That might
also help.
Thank you
All the best,
Kirill Lomachenko
--
Dr. Kirill A. Lomachenko
Scientist at BM23/ID24
have a certain impurity in the high doping range
> on my system, namely Li2Se. I try to include a scattering path from the
> respective Li2Se crystal model in my fits, since a Se (absorber) - Li
> (backscatterer) pair is present in the R-range of my fit in the Forward
> Fourier Transfor
I try to include a scattering path from the
respective Li2Se crystal model in my fits, since a Se (absorber) - Li
(backscatterer) pair is present in the R-range of my fit in the Forward
Fourier Transform. My question here is if this makes sense since Li is
much smaller scatterer compared
Julian:
I agree with Anatoly. The amplitude of the EXAFS is quite large. I have seen
a similar effect in metal foils and NP samples when you forget to take the
log of the I0 and IT. This also forces the S02 factor to be artificially
high (like it is for your samples) when fitting in Artemis. Maybe
that its
histogram is trivial -- one bin at one distance.
The histogram path, like its normal path counterpart, must have the
EXAFS equation evaluated. Thus the histogram path has an amplitude,
an E0 shift, a delta R, and a sigma^2 that must, somehow, be
evaluated.
The amplitude is pretty easy
Reduced chi-square : 604.118
R-factor: 0.0195782
Measurement uncertainty (k) : 0.0001264
Measurement uncertainty (R) : 0.0004142
Number of data sets : 1
guess parameters:
SO = 1.06525455# +/- 0.05504541 [1.0]
delE
: 7324.9401796
Reduced chi-square : 604.118
R-factor: 0.0195782
Measurement uncertainty (k) : 0.0001264
Measurement uncertainty (R) : 0.0004142
Number of data sets : 1
guess parameters:
SO = 1.06525455# +/- 0.05504541 [1.0
Number of variables : 4
Chi-square : 7324.9401796
Reduced chi-square : 604.118
R-factor: 0.0195782
Measurement uncertainty (k) : 0.0001264
Measurement uncertainty (R) : 0.0004142
Number of data sets : 1
guess parameters:
SO
interlibrary loan, at no cost to you or your institution.
In the mean time, a quote from the book that may be useful in thinking about
S02:
Alternatively, one can treat So2 as a phenomenological parameter that accounts
for any amplitude suppression independent of k and R, regardless of physical
cause
ell (configuration C2), respectively and got some
results. Please see the attached table. Smaller reduced chi2 and R-factor were
obtained by using configuration C2 as the initial model. Does this mean the
species of arsenate in barite is more likely to be HAsO42- instead of AsO43- ?
We also have other evid
: Re: [Ifeffit] Large Amplitude Values
Hi Gavin,
What are the uncertainties on the high S02 values?
Fluorescence is unlikely to be the culprit. While it can affect your
ability to normalize properly, you're unlikely to account for a
factor of 2 by normalization if the data is relatively decent
that.
In playing around with different windows and dk values my fit
variables generally stayed within the error bars, but the size of
the error bars could change more than a factor 2. Does this mean
that it would make sense to find a window/dk that seems to work
for a given group
coordination number to the bulk
coordination number via particle radius? (equation 4)
How can I do this in Artemis when there's other variables such as deltaE,
debye-waller factor and delr to worry about?
thanks,
georges
On Tue, Oct 29, 2013 at 7:31 PM, Scott Calvin scal...@sarahlawrence.eduwrote:
Hi
the amplitude reduction factor: I use
different So^2 for different elements, correct? If I start fitting and have
paths involving the same kind of atom but once at distance 2A, and once maybe
3A, is this then the same So^2 or am I supposed to model the behaviour of So^2
somehow?
Similar for \Delta R: If I
factors, i.e. on the order of 0.02-0.06 A^2. Including them and/or the
Pt-O-P MS paths lead to a small decrease of the R-factor, but an
increase or no change in the reduced chi-square! (HOW CAN THIS BE?)
Leaving them out has the advantage that the other fitting parameters
have smaller error bars. I
+/-0.14, R=0.0055, reduced
chi^2=17.86, Percentage=0.53+/-0.04
2) Set S02=0.7, R=0.044, reduced chi^2=120.6, percentage=0.81+/-0.2
3) set S02=0.8, R=0.030, reduced chi^2=86.10, percentage=0.77+/-0.07
3) set S02=0.9, R=0.021, reduced chi^2=60.16, percentage=0.72+/-0.06
4) set S02=1.0, R=0.017, reduced
that are known to be bad (e.g.
have a huge R-factor, unrealistic fitted parameters, etc.), but since those
fits aren't generally the published ones, that's OK.
Secondly, the high-R amplitude will not be essentially zero with
theoretically-generated data, even if you don't add noise, because the effect
and rescales
accordingly. This means that the estimated uncertainties really
aren't dependable for fits that are known to be bad (e.g. have a
huge R-factor, unrealistic fitted parameters, etc.), but since those
fits aren't generally the published ones, that's OK.
Secondly, the high-R amplitude
choose the site with 4 neighbors to construct FEFF to model
your EXAFS data; and if you set your degeneracy equal to 4 and make your
amplitude factor as S02*x of one site + S02*(1-x) of another site, then
your S02 will come out larger than it should be because it will compensate
for the fact that you
with 4 neighbors to construct FEFF to model
your EXAFS data; and if you set your degeneracy equal to 4 and make your
amplitude factor as S02*x of one site + S02*(1-x) of another site, then
your S02 will come out larger than it should be because it will compensate
for the fact that you
; charset=us-ascii
One possible scenario: If one site has 6 nearest neighbors and the other -
4, and if you choose the site with 4 neighbors to construct FEFF to model
your EXAFS data; and if you set your degeneracy equal to 4 and make your
amplitude factor as S02*x of one site + S02*(1-x) of another
think) noise added to simulate
a tube amp. Guess which won? Somebody once wrote a parody in which
mercury-filled speaker cables were
advertised for their liquid, shimmering sound, but I digress.
But for EXAFS, we know the limits of the signals in k and R (say, 50
Ang^-1 and 25 Ang for extrema
-factor: 0.0195782
Measurement uncertainty (k) : 0.0001264
Measurement uncertainty (R) : 0.0004142
Number of data sets : 1
guess parameters:
SO = 1.06525455# +/- 0.05504541 [1.0]
delE = -2.32587026
ples
Message-ID: <20151109132407.99127g2zy7ipe...@umail.oit.umass.edu
<mailto:20151109132407.99127g2zy7ipe...@umail.oit.umass.edu>>
Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes";
format="flowed"
Hi,
I have a ge
not know what is in my sample how can it help?
I try to answer it myself and someone can correct me:
Certainly not all of my, say 10 reference spektra, are that similar that
I can get several LCFs with the same say R-factor. So, I will get some
clue to narrow the components. But still there can
to 12 provided that you have a reasonable
understanding of what the amplitude reduction factor might be. You can
also start by constraining the delta R and sigma-squareds for the two
paths until you are sure that the fit makes sense and is stable.
If you have data from both W and Mo edges
that the MSRD (sigma squared) for EXAFS differs
substantially from the Debye-Waller factor in XRD, because the first is
the variance in the interatomic distance, and the second is the variance in
the atomic position relative to a lattice point.
But what about the lattice parameter implied by the nearest
of this equation
come in two flavors.
One flavor includes the terms 2R (the length of the path), sigma^2
(the mean square disorder about that path length), N (the number of
such paths), S_0^2 (the amplitude reduction factor that has to do with
the details of the behavior of the other electrons
reported
by Ifeffit are 1-sigma error bars.
The correlations are taken from the off-diagonal elements of the
covarience matrix. Those need not be scaled and aren't.
The formulas for chi-square, reduced chi-square, and the R-factor are
given on pages 16 and following of this postscript file
http
--
good and is the one that you want to publish, the error bars reported
by Ifeffit are 1-sigma error bars.
The correlations are taken from the off-diagonal elements of the
covarience matrix. Those need not be scaled and aren't.
The formulas for chi-square, reduced chi-square, and the R-factor
for the MS path and it
appears to increase the R factor slightly and tries to maximize the floating
degeneracy I set (with a restrain to be physically reasonable based on my
model). It does not look as good but at least it seems more plausible. I will
try out Shelly's suggestions to see if they work too
and too high EXAFS intensity compared to my data. Your amplitude factor
is 1.54 which also confirms that something was wrong in the experiment. Perhaps
- a misalignment? The NP data also look strange...
I would not focus on the NP analysis until you figure out why your foil data is
so strange
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