[Ifeffit] Fitting Commercial Molybdenum Disulfide

Kelly, Shelly D. SKelly at anl.gov
Fri Oct 29 10:41:09 CDT 2004


Hi Dan,

I would suggest using one ezero with three different delr values for
these three paths.  You are introducting only one more variable.  delr
and ezero are correlated so by constraining delr you need more ezero
values or vise versa.

Shelly


> -----Original Message-----
> From: dmc at pdx.edu [mailto:dmc at pdx.edu] 
> Sent: Friday, October 29, 2004 10:25 AM
> To: XAFS Analysis using Ifeffit
> Subject: Re: [Ifeffit] Fitting Commercial Molybdenum Disulfide
> 
> 
> Mike & list, 
> 
>       Where can I find a reasonable model for my delr terms, 
> if I do assume 
> that the bond angles are changing/there is no isotropic 
> expansion?  Is there a 
> description somewhere in the archives that I could look at?  
> 
>       Creating different sigma squared parameters for each 
> path did help the R- Factor somewhat, but not the reduced 
> chi.  Here's some data:
> 
> 
> Fit with seperate sigma's:  
> 
>     Independent points          =      14.312500000
> Number of variables         =       6.000000000
> Chi-square                  =    5778.957783654
> Reduced Chi-square          =     695.212966455
> R-factor                    =       0.029041008
> Measurement uncertainty (k) =       0.000181935
> Measurement uncertainty (R) =       0.004860095
> Number of data sets         =       1.000000000
> 
> 
> Guess parameters +/- uncertainties  (initial guess):
>   e0_1            =    -4.0347670   +/-      2.9998980    
> (guessed as -4.072009 
> (1.919404))
>   ss              =     0.0042860   +/-      0.0005990    
> (guessed as 0.004636 
> (0.000411))
>   e0              =     1.6770760   +/-      1.3230290    
> (guessed as 1.765958 
> (1.154388))
>   alpha           =     0.0009180   +/-      0.0034050    
> (guessed as 0.001090 
> (0.002843))
>   ss2             =     0.0048160   +/-      0.0006910    (0.0000)
>   ss3             =     0.0225310   +/-      0.0657250    (0.0000)
> Def parameters:
>   delr_1          =     0.0036440
> Set parameters:
>   amp             =  0.7
> 
> 
> Correlations between variables:
>         e0_1 and alpha      -->  0.8542
>           e0 and alpha      -->  0.8470
>         e0_1 and e0         -->  0.7407
>         e0_1 and ss3        -->  0.7060
>        alpha and ss3        -->  0.4715
>          ss2 and ss3        --> -0.4214
>         e0_1 and ss2        --> -0.3892
>           e0 and ss3        -->  0.3772
>        alpha and ss2        --> -0.2680
> All other correlations are below 0.25
> 
> 
> 
> 
> 
> 
> 
> 
> Fit without (original):
> 
> 
> Independent points          =      14.312500000
> Number of variables         =       4.000000000
> Chi-square                  =    6562.747150128
> Reduced Chi-square          =     636.387602437
> R-factor                    =       0.032979787
> Measurement uncertainty (k) =       0.000181935
> Measurement uncertainty (R) =       0.004860095
> Number of data sets         =       1.000000000
> 
> 
> Guess parameters +/- uncertainties  (initial guess):
>   e0_1            =    -4.0720130   +/-      1.9194050    
> (guessed as -4.072009 
> (1.919404))
>   ss              =     0.0046360   +/-      0.0004110    
> (guessed as 0.004636 
> (0.000411))
>   e0              =     1.7659560   +/-      1.1543880    
> (guessed as 1.765958 
> (1.154388))
>   alpha           =     0.0010900   +/-      0.0028430    
> (guessed as 0.001090 
> (0.002843))
> 
> Def parameters:
>   delr_1          =     0.0043250
> 
> Set parameters:
>   amp             =  0.7
> 
> 
> Correlations between variables:
>         e0_1 and alpha      -->  0.8416
>           e0 and alpha      -->  0.8045
>         e0_1 and e0         -->  0.7141
> All other correlations are below 0.25
> 
>        
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