Re: [Ifeffit] Fwd: Re: why ss_2 is negative?
Dear all, Thanks million for your great advice for my EXAFS modeling! It helps me understand more about EXAFS and I really appreciate it! But I still have some questions to consult you. I took your suggestion and have the amp and e0 the same for each path. In addition, I fixed the number axial U-O as 2. For the equatorial ligand, since the total coordination number is between 4 and 6, I guess the number of U-F as 2(that is n1), and def the number of U-O as (5-n1)(that is n2). Then I did the fit. The result showed the ss_2 is still negative. So I set the ss_2 as 0.003, did the fitting again. I don't know if it is ok to fix the ss_2=0.003. It seems the dr_1 change a lot. In addition, I tried to do fitting in Kw=2 in stead of Kw=3. At this time, the ss_2 is positive, and from my understanding, it seems the modeling is more resonable for dr_1 and dr_2, but the R-factor is 0.023, a little bit larger than 0.02. How can I decide which one I should use, the Kw=3 or Kw=2? Is there anything I can do to improve the modeling? The attached is my modeling. I am sorry to put attachment in the email that my bother you. Best regards! Hao
Hao,
A few more comments:
1. It is well advised for anyone starting to look at uranyl compounds with XAS to read Shelly's various publications on that topic. Geochem. Cosmo. Acta, 66(22) 3875-3891, (2002) is particularly useful. Google scholar can help you locate more of her papers.
2. I am the first to admit that Artemis and Ifeffit are difficult tools for the beginning exafs practitioner. These tools try to provide a usable face to a difficult problem. Ifeffit was written with enough flexibility and power to allow the so-called experts to do the analysis they want to do. That means that Artemis has enough freedom to allow the unsuspecting user to do ill-advised things.
You really need to think about what each of the parameters means. For example, just because Artemis allows you to float e0 freely for each path does not mean that doing so is a good idea. There are situations where it is a very good idea to have more than one e0 parameter in your fit, but I suspect that yours is not one of them. Consequently, you should consider constraining all your paths to have the same e0.
What do I mean by "constrain"? Well, on the Guess,Def,Set page, you can define a single e0 parameter as a guess parameter, then use that parameter on each of the path pages. In that way, you will have one floating parameter in your fit that is used to describe the e0 of all your parameters.
Similarly, you should think hard about the numbers of each kind of path. A uranyl moiety is unlikely to have more or less than 2 uranyl ligands. The uranyl bond is very strong, consequently it is energetically unfavorable in a uranyl for those two bonds to be over- or under-filled. Consequently, you can consider setting the number of yl oxygens to 2. Furthermore, the equatorial plane is likely to have between 4 and 6 oxygens, so you should think of ways to constrain the total number of equatorial oxygens to be something reasonable. Since the coordination number is highly correlated with sigma^2 in a statistical sense, thinking well about coordination number should help address your original question.
3. Scott has made a very nice Artemis tutorial which can be found at http://cars9.uchicago.edu/iffwiki/HoraeSoftware#contrib It comes in the form of a series of Artemis projects. Newcomers benefit by working through his tutorial before trying to analyse their own data with Artemis.
4. The Ifeffit web site, my home page, and especialy http://xafs.org are all filled with useful information for the XAS novice. If you haven't already looked through the resources on those sites, you really should budget some time to do so.
HTH, B
-- Bruce Ravel ---------------------------------------------- bravel@anl.gov
Molecular Environmental Science Group, Building 203, Room E-165 MRCAT, Sector 10, Advanced Photon Source, Building 433, Room B007
Argonne National Laboratory phone and voice mail: (1) 630 252 5033 Argonne IL 60439, USA fax: (1) 630 252 9793
My homepage: http://cars9.uchicago.edu/~ravel EXAFS software: http://cars9.uchicago.edu/~ravel/software/
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Hello Hao: I took a look at your fits _very_ briefly. Just a couple of things to note. The range of chi(k) which you use in the fit is probably a bit large. You are starting at 2.1 and the data at that point is really not usable. I would start at 3 or so. On the high end, it seems OK. The estimated standard deviations on lots of your parameters are very large, on the order of the parameter values themselves. This is a red flag and it generally indicates that the fit has too many variables. This is the biggest concern that I have. Look at the values: dr = 0.0010050 +/- 0.0111490 ss = 0.0031940 +/- 0.0021850 dr_1 = 0.0464110 +/- 0.1100960 ss_1 = 0.0130090 +/- 0.0188820 dr_2 = 0.0896690 +/- 0.0765040 ss_2 = 0.0043400 +/- 0.0106960 n1 = 3.3690270 +/- 3.5237430 most of these values are indistinguishable from zero. (As an aside, are you getting an error box when you try to fit? The parameter "dr" is not allowed in newer versions of Artemis.) Here is my suggestion: Change the chi(k) range to 3-13.2. Change the fitting range to 1-2.65 or so. Link the ss_1 and ss_2 parameters together and set dr to 0.0 as it is basically there already and has a large uncertainty. By doing this you will have reduced significantly the number of parameters and the uncertainties will be more manageable. More importantly, when you work on a model, start with a more highly constrained one (fewer paths, for example) and try to work your way up while always making sure that the results make sense. You will be able to reduce the parameter space that you have to cover this way. Keep a close 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 Voice: 312.567.3498 Fax: 312.567.3494 segre@iit.edu http://www.iit.edu/~segre segre@debian.org
Hi Hao, I haven't had time to look at your fits, but I have some generic responses to what you say below. It is typical of someone new to the field to chase r-factors. Don't do it! I could take any spectrum and any model and by floating enough variables, come up with a terrific looking r-factor...for a fit that's utter nonsense. At the risk of having another set of completely arbitrary criteria named after me <grin>, here's the guidelines I give undergraduates when I'm teaching the technique. (Note: these guidelines apply to decent-quality data. For cases like very dilute 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 or the wrong amplitude. Then the model may be OK, but things like the free parameters and constraints may need to be adjusted. On the other hand, the wiggles may be qualitatively wrong, in which case the underlying model must be seriously questioned. R-factor in the range 0.05 to 0.10: Underlying model may be correct, but there is likely some effect not being taken into account (for example: phase impurity, oversimplified sigma2 constraints, vacancies, etc., etc.). Alternatively, perhaps it's too wide a k-range, problems with background subtraction, or the like. I have occasionally published fits in this range, although always with an explanation of possible factors in the text of the article. R-factor in the range 0.02 to 0.05: Decently good match between fitted and actual spectra. There's still enough of a mismatch that, if the data is good quality, there are probably some issues with details of the model. At this point, R-factors are becoming less of a concern than the plausibility of the constraint scheme and the fitted parameters, the number of degrees of freedom, agreement with other source of information about the system, etc.. R-factor less than 0.02. Good match between fitted and actual spectra. Unless you're doing technical work on a very well-characterized sample (say, a piece of copper foil), there's no point in trying to reduce the R-factor any further. You're a lot better off with a constraint scheme that can be explained on physical grounds and an R-factor of 0.019, than, for example, introducing a parameter for the third cumulant of a fourth-nearest-neighbor in a metal to get an R-factor of 0.005. These are broad guidelines only; the R-factor has no meaning in a statistical sense, so what to expect is highly dependent on data quality. * * * OK--I've taken a very quick look at your fits to help answer your question about the k-weights. Your k-weight 2 and k-weight 3 fits are consistent, in that the error bars of corresponding parameters overlap. But the k-weight 2 fit has enormous uncertainties, and is thus pretty much useless. What good does it do you to find that n1 is 3.4 +/- 3.5? Presumably you knew that already. :) So in that sense the k-weight 3 fit is "better." But there are other problems: --the S02 is a bit high. Ideally it shouldn't be higher than 1.0. --You seem to be fitting too high an R-range. Going to 3 when your most distant path has an Reff of 2.4 is dangerous...depending on your substance there may be other stuff out there you're not accounting for. --The negative sigma2 that you're worried about is NOT a big problem, however. It is given as -0.003 +/- 0.008. So it could be positive according to the fitted results. --It looks like you set n2 to 0.175 based on some previous fit. Do you believe that's physically reasonable for your system? This business of running a fit, finding some parameters, and then running a fit on the same data fixing some parameters to values from a previous fit is at best dangerous, and at worst nonsense. That's different than the advice often given on this list, where you compare a fit with a parameter fixed to a suspected-prior-knowledge value to one where it is allowed to float. For example, saying "the chemists tell me this coordination number should be 6. I'll fix it at 6, and I'll let it float, and if the floated case doesn't seem better, I'll go back to fixing it at 6" is very different from "my first fit on this sample gave me a coordination number of 5.47 +/- 4.8. That's a big uncertainty, so I'll set the coordination number to 5.48 and proceed." Using the first procedure in a final, published fit is defensible, the second one is not. Hope that helps. --Scott Calvin Sarah Lawrence College At 01:48 PM 2/27/2007, you wrote:
I took your suggestion and have the amp and e0 the same for each path. In addition, I fixed the number axial U-O as 2. For the equatorial ligand, since the total coordination number is between 4 and 6, I guess the number of U-F as 2(that is n1), and def the number of U-O as (5-n1)(that is n2). Then I did the fit. The result showed the ss_2 is still negative. So I set the ss_2 as 0.003, did the fitting again. I don't know if it is ok to fix the ss_2=0.003. It seems the dr_1 change a lot.
In addition, I tried to do fitting in Kw=2 in stead of Kw=3. At this time, the ss_2 is positive, and from my understanding, it seems the modeling is more resonable for dr_1 and dr_2, but the R-factor is 0.023, a little bit larger than 0.02. How can I decide which one I should use, the Kw=3 or Kw=2? Is there anything I can do to improve the modeling?
participants (3)
-
Carlo Segre -
hw26＠njit.edu -
Scott Calvin