Dear all,
I have a question about the R factor: how can I decide if the difference
between the R factors of 2 fits is statistically significant, i.e, how can I
calculate the uncertainty which has to be associated to the R factor?
B.R.,
Lisa
Hello List,
I know that Horae is no longer supported but I had quick question about
the R-factor.
I search the mailing list and found this post from 2006 concerning
different R-factors in the fit log
I have a question about Artemis log file. I noticed that two r-factors are
reported
Thanks, Matt, I'll give it a try.
--Scott
On Jan 8, 2012, at 10:06 PM, Matt Newville wrote:
It should be possible to calculate an R-factor or chi-square
statistics with a fairly simple ifeffit macro, using the functions
vsum() (to sum an array) and npts
Dear list,
I am back with a new consultation on EXAFS fitting within Artemis.
I have made a fit and obtained a reduced Chi2 value of 391 and R-factor of
0.014 using 9 variables. Then I have added two more paths increasing the
number of variables up to 12 and then I obtained a reduced Chi2
On Friday 23 June 2006 05:01, you wrote:
I have a question about Artemis log file. I noticed that two r-factors are
reported in the log file. One is in the fifth line and it is called
'R-factor' and the other one is under the data set fitting conditions and
it is called 'r-factor
Good afternoon,
Could you please tell me what is the difference between the calculation
of the R-factor and the NSS ?
I found that R-factor is equal to : sum((data - fit)^2)/sum(data^2) and
NSS = sum((data - fit)^2)/sum(data^2)*100
But when I compare the R-factor obtained by Athena
Hello Marine,
On Tue, May 16, 2017 at 4:59 AM, Marine Albertelli <
marine.alberte...@univ-pau.fr> wrote:
> Good afternoon,
>
> Could you please tell me what is the difference between the calculation of
> the R-factor and the NSS ?
>
> I found that R-factor is equal to :
Hi Lisa,
At 07:23 AM 1/5/2007, you wrote:
I have a question about the R factor: how can I decide if the
difference between the R factors of 2 fits is statistically
significant, i.e, how can I calculate the uncertainty which has to
be associated to the R factor?
As I understand it, you
Hi Jon Petter,
On Tue, Jul 12, 2022 at 12:46 AM Jon-Petter Gustafsson <
jon-petter.gustafs...@slu.se> wrote:
> Hello all,
>
>
>
> I have been a frequent user of Athena for many years, mostly for
> interpreting P K-edge XANES spectra. Until last week I thought that
Hi Scott,
here I copy a part of the report:
Independent points = 6.222656250
Number of variables = 4.0
Chi-square = 247.145092496
Reduced Chi-square = 111.193574128
R-factor= 0.017422216
Guess
Jesus,
On Mon, May 23, 2016 at 7:08 AM, Jesús Eduardo Vega Castillo <
jeve...@gmail.com> wrote:
> Dear list,
>
> I am back with a new consultation on EXAFS fitting within Artemis.
>
> I have made a fit and obtained a reduced Chi2 value of 391 and R-factor of
> 0.014 u
a new consultation on EXAFS fitting within Artemis.
>>
>> I have made a fit and obtained a reduced Chi2 value of 391 and R-factor
>> of 0.014 using 9 variables. Then I have added two more paths increasing the
>> number of variables up to 12 and then I obtained a reduced Chi2
Hello all,
I have been a frequent user of Athena for many years, mostly for interpreting P
K-edge XANES spectra. Until last week I thought that the R factor in Athena was
always defined as:
sum( [data_i - fit_i]^2 )
---
sum( data_i^2 ]
This is also
Hi Scott,
On Sat, Jan 7, 2012 at 12:42 PM, Scott Calvin scal...@sarahlawrence.edu wrote:
Hi all,
Is there a way to get Athena (or Ifeffit) to report an R-factor for a linear
combination sum, as opposed to a fit? Artemis does that for FEFF fitting, and
Athena will do a linear combination
On Wednesday, March 13, 2013 08:24:41 PM davood dar wrote:
1. *1*.What is the ideal value of R- factor for any fit.
R-factor is a way of expressing percentage misfit. Smaller is
generally better, although smaller is not better if other aspects of
the fit are not defensible
Thank you for the discussion Matt and Jason,
My main objective was to decide between the two different reported
R-factors in some older Artemis fit file logs. I suspect that the
analysis was prematurely completed because the user found small R-factor
values printed out along with the other
Hi all,
Could any tell me in a simple language about the error bars
returned by the EXAFS fitting program?
what
do they exactly represent?How is
it determined?How is
the number of iterations decided.In
addition to R-factor what are the other parameters which
Dear iffefit user,
I found on a paper (E.A. Stern et al. /Physica B 208209 (1995) 117 120) the
definition of R quality factor as:
R_factor ≡ ∆chi(R space)) = √[ ∑ |chi_C(Ri) – chi_E(Ri)|2 / ∑( chi_E(Ri))2]
formula 3
Where Chi(Ri) is a complex function (imaginary and real part
Hi Sandra,
On Sat, Apr 6, 2013 at 12:37 PM, Sandra Luber s.lu...@pci.uzh.ch wrote:
Dear Matt Newville,
I do some fitting with ifeffit using EXAFS data generated by feff.
I wonder how the R-factor is calculated. Unfortunately,
I have not found any definition yet. Would it be possible
Hi Chris,
Might be helpful also to link to the archived thread you're talking about.
http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2006-June/007048.html
Bruce might have to correct me on this, but if I remember right there were
individual-data-set R-factor and chi-square calculations
artifacts as well as errors in
the Feff calculations.
For us, reduced chi-square is almost always 1, unless the data is very noisy.
R-factor scales the fit residual by the magnitude of the data itself,
for some estimate of fractional misfit. This gives a convenient
measure that is independent
are slightly different, I have appended the message
with these results. the very low value of R-factor produced with the 64bit
system is difficult to interpret. the questions are;
1- how to account for these differences?
2- if I to publish something, which measure of the quality should I present?
and how
OK, good answer Scott. My fits have lower values of R-factor but when I depict
them in k-space they do not fit quite well to the experimental data due to the
short range of R space chosen, of course if I increase range of R then I hope
fits in k space will look better. When I talked about
points = 6.222656250
Number of variables = 4.0
Chi-square = 247.145092496
Reduced Chi-square = 111.193574128
R-factor= 0.017422216
Guess parameters +/- uncertainties (initial guess):
amp
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.
Thanks,
Matthea Peck
___
Ifeffit mailing list
Ifeffit
Hi all,
Is there a way to get Athena (or Ifeffit) to report an R-factor for a linear
combination sum, as opposed to a fit? Artemis does that for FEFF fitting, and
Athena will do a linear combination sum (plot data + sum with weights entered
into the LCF standards boxes), but I don't see a way
On Saturday, January 07, 2012, 01:42:43 pm, Scott Calvin wrote:
Hi all,
Is there a way to get Athena (or Ifeffit) to report an R-factor for a
linear combination sum, as opposed to a fit? Artemis does that for FEFF
fitting, and Athena will do a linear combination sum (plot data + sum
fluorescence, it's reasonable to expect statistical
effects to inflate the R-factor a bit.)
R-factor 0.10: Serious problems with the fit. The underlying model
may be incorrect. It's best at this stage to look at the spectrum for
clues. Maybe the wiggles are qualitatively right, but shifted over
ts : 17.7666016
> Number of variables : 17
> Chi-square : 265.0947132
> Reduced chi-square : 345.8050781
>
> R-factor: 0.0026486
>
> Number of data sets : 1
> : k-range = 2.942 - 1
foil with the two
diffrent machines, a 32 bit and 64 bit ones, both running widows7, 32
ans 64 bit respectively.
The results obtained are slightly different, I have appended the
message with these results. the very low value of R-factor produced
with the 64bit system is difficult to interpret
: 345.8050781
R-factor: 0.0026486
Number of data sets : 1
: k-range = 2.942 - 11.043
: dk= 1
: k-window = hanning
: k-weight = 1,2,3
: R-range = 1.115 - 3.5
: dR= 0.0
: R-window
-square, and R factor express the sum of
squares of the residual (data-model) after a fit has finished. The
difference between these statistics is how they are scaled.
In particular, chi-square is scaled by the estimated error in the
data. If you look at a (naive?) introduction to statistics
Thanks, Bruce.
Does the math expression in IFEFFIT include the term -4k*sigma2*(1/labmda
+1/R) in the phase? If yes, the 1st cumulant is sigma1= R+dR. If no, sigma1=
R+dR+2*sigma2*(1/labmda +1/R). It this correct?
Yuan
On 4/1/11 2:18 PM, Bruce Ravel bra...@bnl.gov wrote:
On Friday, April 01
program?
what
do they exactly represent?How is
it determined?How is
the number of iterations decided.In
addition to R-factor what are the other parameters which determines a good
fit.For a
R-factor ~0.001, if the value of chi2~10,000
and reduced chi2 ~ 500
: 756.5273522
R-factor: 0.0023036
Measurement uncertainty (k) : 0.0002947
Measurement uncertainty (R) : 0.0004735
Number of data sets : 1
Happiness = 100.00/100 color = #D8E796
* Note: happiness is a semantic parameter and should *
*NEVER
=4334.684537717
Reduced Chi-square = 691.819976095
R-factor= 0.004250325
amp = 0.8649100 +/- 0.0412220(1.)
enot= 5.6049380 +/- 0.2950270(0.)
delr=-0.0226780
Hi all,
Could someone please answer my questions? I would really appreciate your help.
1. For linear combination fitting, there are three indicators for the goodness
of fitting: R-factor, chi-square and reduced chi-square. Could anyone tell me
how they work?
2. Since TEY is sensitive
Respected Sir,
I am new in the field of EXAFS. I have few questions regarding
to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS
data.
1. *1*.What is the ideal value of R- factor for any fit.
2. *2. * Can we use (fit) the theoretical model
Respected Sir,
I am new in the field of EXAFS. I have few questions regarding
to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS
data.
1. What is the ideal value of R- factor for any fit.
2. * * Can we use (fit) the theoretical model generated from
Respected Sir,
I am new in the field of EXAFS. I have few questions regarding
to IFEFFIT i.e., fitting of theoretical models to the experimental EXAFS
data.
1.What is the ideal value of R- factor for any fit.
2. ** Can we use (fit) the theoretical model generated from
On Friday 09 January 2009 09:12:16 am Bindu R. wrote:
Could any tell me in a simple language about the error bars returned by the
EXAFS fitting program?
what do they exactly represent?
How is it determined?
How is the number of iterations decided.
In addition to R-factor what are the other
this:
Independent points = 13.166992187
Number of variables = 8.0
Chi-square =1534.709946959
Reduced Chi-square = 297.021921317
R-factor= 0.000128095
Measurement uncertainty (k) = 0.60423
Measurement
Thank you Scott,
I guess that is a refinement of my question concerning R-factor.'
Chris
Christopher J. Patridge, PhD
NRC Post Doctoral Research Associate
Naval Research Laboratory
Washington, DC 20375
Cell: 315-529-0501
On 1/15/2013 9:39 AM, Scott Calvin
number of variables. Many analysis programs report
only a value like R-factor (ie, the misfit not scaled by the
measurement uncertainty or number of free parameters in the data).
Again, this is an OK measure of the misfit, though it too is scaled
somewhat arbitrarily, and cannot be used to compare
, is the magnitude of the
DW factor determined by assuming the total path length R is the appropriate
length to use for the correlation term in the Debye spectral density? It seems
like it would not be reasonable to treat all paths of the same R as having the
same Debye-Waller factor since a single
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
points = 8.239257812
Number of variables = 1.0
Chi-square = 0.12000E+37
Reduced Chi-square = 0.165762849E+36
R-factor= NaN
Measurement uncertainty (k) = 0.000437667
Measurement uncertainty
?
Independent points = 8.239257812
Number of variables = 1.0
Chi-square = 0.12000E+37
Reduced Chi-square = 0.165762849E+36
R-factor= NaN
Measurement uncertainty (k
Chi-square : 0.000
Reduced chi-square : 0.000
R-factor: 0.000
Number of data sets : 1
Happiness = 100.00/100 color = #D8E796
is
trying to compensate for high R space magnitude by making amp above 1
and ss negative. Have you considered your data processing in Athena?
Did you use the default settings? I would guess Cu-O bonds might be
too short for the presets in Athena. How did you check your model?
Buena salud
ables, and approximately 41.333
measurements
Weights sum to 1: no
Weights forced between 0 and 1: no
Overall e0 shift used: yes
Noise added to data: 0
R-factor = 0.0003537
Chi-square = 0.00815
Reduced chi-square = 0.858
.standard weight
suggestion of sending a project file.
For what it's worth (in case you missed it while you were reading the
docs and tutorials),
|chi(q)| = magnitude of the complex chi(q) = FT^(-1) [ chi(R) * Window(R) ]
where Window(R) is a Windowing function and chi(R) = FT[ chi(k) * k^w
* Window(k) ]
where
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.
A video of this behaviour can be found here:
https://wwwa-e.ucl.ac.uk/cgi-bin/dropbox/dropbox.cgi?state=pickup_infoid=29d3e5c2
password:
54c8545f
System info: Win 8.1
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/demeter/#windows
If you see any other questionable
Dear all,
Is there a physical limitation determining exafs bond distance resolution?
Very often the equation r = pi / 2 deltak is quoted as a measure for
bond distance resolution. But as i understand this equation is related
to the fourier transform traditionally used for exafs analysis
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 be, for example:
Standard-combi 1, 2, 3 equal to 1, 4, 6.
So,
my
On Fri, Apr 17, 2009 at 8:08 AM, Cammelli Sebastiano
sebastiano.camme...@psi.ch wrote:
In the case of a linear combination fitting on the k space performed by
ATHENA, the ∆chi needs a correction. Is it correct to write:
R_factor ≡ ∆chi(k space)) = √[ ∑ (chi_C(ki) – chi_E(ki))2 / ∑(
noisy data. Including C in the fit
might very well improve the fit in the sense of an R-factor--maybe, in
fact, there's a 45% chance of a modest improvement with a given set of
very noisy data, even if there's no C present. That does not mean that
a result like that should lead
of the single fit I get a R-factor of 2.0x10-3 whereas for the
best fit from the combinations I got 1.8x10-3 (the weights of each
standards are also different in both cases).
My answer is still the same.
It is quite possible that I am not understanding your explanation, but
it seems as though you
Hello everyone,
I am currently performing a simple curve fit on bulk MoS2 using an atoms file
for crystalline MoS2. I've found that increasing k_min on my fit (e.g. from 2
to 4) improves the quality of the fit (R-factor from 0.028 to 0.009), but also
increases S02. If I use a large enough
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 was only doing a quick first shell fit
Dear all,
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 to literature
(e.g. B.K. Teo, Inorganic Chemistry Concepts 9; Martens et
but it likes it. 5
imidazoles and 3 sulfurs and I have an R-factor of 0.2% every time.
If there is non standard multiple scattering that occurs in multiple
unrelated proteins from different organisms then we would have no idea
what this could be.
Thanks for your comments!
Carolyn Carr
s 0.9). (2) When Fitting the Debye�CWaller
factor (ss) and coordination number (N), although I use "abs()" to make it to
be positive, but the fitting results still be negative. But I did not meet
these problems in the old version in Artemis 0.8.012. I am wondering that
whether c
Hi Jenny,
1. For linear combination fitting, there are three indicators for the
goodness of fitting: R-factor, chi-square and reduced chi-square. Could
anyone tell me how they work?
This is actually documented in Athena, and the Users Guide. They are
also defined in the Feffit documentation
significantly better in R-factor (with reasonable distances,
sigma^2, etc) but for Zinc this is not the case.
I can get many good fits and Zinc likes to increase the coordination
up to 8 for all data sets I have ever fit, although there is obviously
no physical basis in this. This is true
# -
# fitFoMR-factor
Reduced_chi-square Chi-square nvar nidp
'K4W(CN)8 R(1.7-6)'1 0.022714347.765
219223.767 30 45
'K4W(CN)8 R(1.7-4) no bkg' 3 0.025718704.721
192125.245 7
0.003047
r-factor: 11
reduced-chi square: 95
Energy shift by fit shows an amount of difference from Pt L3 edge. It
is my problem.
To reduce the energy shift, I tried to remove background carefully
again and to change distance Pt-O.
However the result was failed
, there is a photoelectron spectrum showing the relative
intensity of Auger and Photopeaks. The secondaries are roughly a
factor of 100 more intense than the other contributions.
It is possible to measure both TEY and Auger electron yield (AEY) and
you will see that the AEY is more surface sensitive that TEY
1977 paper, and both are
available online.
S M Webb (2005) SIXpack: a graphical user interface for XAS analysis
using IFEFFIT. Phys. Scr. T115, 1011.
E R Malinowski (1977) Determination of the Number of Factors and the
Experimental Error in a Data Matrix. Anal Chem 49, 612.
-Leslie
-Original
the Larch manual:
http://cars.uchicago.edu/xraylarch/xafs/feffpaths.html#models-for-calculating
2. Assuming the DW factors are calculated path-by-path, is the magnitude
of the DW factor determined by assuming the total path length R is the
appropriate length to use for the correlation term
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 of a much
= 1.0
Chi-square = 0.12000E+37
Reduced Chi-square = 0.165762849E+36
R-factor= NaN
Measurement uncertainty (k) = 0.000437667
Measurement uncertainty (R) = 0.000724906
Number of data sets
Artemis gives me message “ -- falling back to Ifeffit”.
I assume it runs Ifeffit which does exactly what Bruce described:
3 data set refined to completion with sensible refined parameter, however,
R-factor for 3rd data set is 1. (overall R for 3 data set is huge too) and
after-fit plot
On 03/09/2017 05:15 AM, Victor Streltsov wrote:
3 data set refined to completion with sensible refined parameter, however,
R-factor for 3^rd data set is 1. (overall R for 3 data set is huge
too) and after-fit plot for 3^rd data set is missing, only experimental
one shown. I am using latest
it does not lower correlations
between N and sigma2 (or E0 and R) by very much.
Cheers,
On Fri, Aug 27, 2021 at 7:41 PM Peng Liu wrote:
> Dear Ifeffit members,
>
> I received the following two comments.
>
> "
> Comment 1: Authors have fixed the amplitude reduction factor (SO
=11563eV, Rbkg=1.3, kweight =1
To fit data
k -range = 3.0~13.5, R -range =2.3~13.5
1. fitting parameters
set macc = 0.0
set so2 = 0.89// reduction factor
guess ePt = 0.0 // energy shift
set npt1=1.0// the number of Pt (1.0 means 12nb! sp; Pt
atoms
ximately 41.333
measurements Weights sum to 1: no Weights forced between 0 and 1: no Overall e0
shift used: yes Noise added to data: 0 R-factor = 0.0003537 Chi-square =
0.00815 Reduced chi-square = 0.858
.standard weight e0
===
Hi Scott,
No my fault, I suffer from tl;dr itis. I didn't read beyond linear combination.
That said it still works:
Fitting Data as chi(k) from 3.000 to 12.000
fit done use k-weight = 2
Fit included 181 data points and 1 variable
R-factor = 0.209356
chi-square = 30.92638
reduced chi
this:
Independent points = 13.166992187
Number of variables = 8.0
Chi-square =1534.709946959
Reduced Chi-square = 297.021921317
R-factor= 0.000128095
Measurement uncertainty (k
I don't think it's at all strange, Anatoly, and I think Matthew's
solution is the right one--it seems obvious in retrospect that the
parameter that Ifeffit should evaluate is 1/R, but apparently it
wasn't obvious to me on Friday. :)
As for obtaining N instead of R, the beauty of both
epsilon_r with an increase in k. There's also a jump of a factor of 2 between 7.5 and 8. Why? Because there's a glitch there, and the glitch adds high-R structure.To make sure there wasn't something odd about this particular chi(k), I took one of the data sets included with the horae distribution: the fil
: 0
Reduced chi-square : 0
R-factor : 0
Measurement uncertainty (k) : 0
Measurement uncertainty (R) : 0
Guess parameters
minima. For Cobalt
and Nickel samples I typically get one or a few fits that are
obviously significantly better in R-factor (with reasonable distances,
sigma^2, etc) but for Zinc this is not the case.
I can get many good fits and Zinc likes to increase the coordination
up to 8 for all data sets I
Hi Ava,
Sorry for the trouble. It looks to me like the fit actually ran. Like,
getting non-trivial and non-starting values and uncertainties for 'ss_Cu1',
'dr_Cu1', etc tells me that many parts of the fit and code worked. I'm
not at all sure why Chi-square and R-factor would report 0.
Do
Dear Scott,
There are several papers dealing with effects of multielectron
photoexcitations present in atomic absorption background (AAB) of K and
L edge EXAFS spectra, which are responsible for the amplitude reduction
factor S02. A quantitative analysis of shake-up, shake-off and other
ed 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 cell of each phase is
> known. Given that the number of Co atoms /unit cell is known for each
>
Scott,
It is a strange result. Suppose you fit a bulk metal foil and vary the 1nn
coordination number. You will not get 12 +/- 1000. You will get about 12 +/-
0.3 depending on the data quality and the k range, and on the amplitude factor
you fix constant. Then, suppose you take your formula
-factor: 0.0266456
Measurement uncertainty (k) : 0.0007222
Measurement uncertainty (R) : 0.0017191
Number of data sets : 1
Happiness = 87.35/100 color = #F6EC91
An R-factor of 0.02665 gives
Hi Yanyun,
Good. So here's the procedure for a Hamilton test.
We're comparing the fit with S02 guessed to the one with S02 set to 0.90,
because that was your a priori best guess at S02.
I take the ratio of the first R-factor to the second. You didn't actually say
the R-factor for the fit
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 (Carlo..you wanted
some numbers)
Second
eye on the Reduced Chi-square
as you add more guess parameters. If it goes up, you may be
overreaching on your model even though the R-factor goes down!
HTH
Carlo
--
Carlo U. Segre -- Professor of Physics
Associate Dean for Special Projects, Graduate College
Illinois Institute of Technology
Nov 27 04:44:48 2007
Subject: [Ifeffit] Exafs distance resolution
Dear all,
Is there a physical limitation determining exafs bond distance resolution?
Very often the equation r = pi / 2 deltak is quoted as a measure for
bond distance resolution. But as i understand this equation is related
Bruce and Matt:
When Athena and Artemis are completely moved to BlackBerry and iPhone, 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
would indicate that C was present when it was not. That is *not* the
same thing as saying there is a 77% chance of C being present.
To see this, imagine very, very noisy data. Including C in the fit might
very well improve the fit in the sense of an R-factor--maybe, in fact,
there's a 45% chance
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?
This is the central problem of EXAFS analysis, or indeed of any
non-linear analysis. Artemis reports
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 to
literature (e.g. B.K. Teo
misleading. Lifetimes derived from
theory and experiment often differ by a factor of 2 or more. In the
transition metals of the first period plots of measured widths of the
L1(2s),L2(2p12), and L3(2p32) levels as a function of atomic number show
broad maxima which are not adequately described by theory
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 beamlines
European Synchrotron Radiation Facility (ESRF)
71 avenue des Martyrs
CS 4022
, 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 Transform. My question here is if this makes sense since Li is
much smaller scatterer
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