You have different E0’s for the nearby oxygens from more distant shells. That can be defensible in some cases. But the strange thing is that the values are identical in different fits, as if you’re setting them to some value. How did you choose those values?
I downloaded a YbVO4 structure from the Crystallographic Open Database and ran it in WebAtoms. While I wouldn’t expect it to generate identical values to those from your model, it does show much greater splitting between the nearest-neighbor oxygens (at 2.27 A) and the next-nearest (2.56 A). Your model has 2.28 A and 2.39 A. That’s quite different. Are you sure you entered the starting structure right?

Best,

Scott Calvin

Lehman College of the City University of New York

On Jan 5, 2017, at 3:12 PM, Raj kumar <rajrk37@gmail.com> wrote:

Dear all,

Earlier, I have posted few questions on large so2 value and got valuable suggestions from Scott and Bruce. Here i am presenting my summary of earlier emails and the present views. Could you please tell me whether am i going in right direction.

I have been trying to fit EXAFS signal of YbVO4 both in bulk and nanoparticles form. Here, I would like to estimate so2 from bulk (reference) and subsequently use the number, as normalization parameter, to calculate the co-ordination number in all nanoparticles. Nanoparticles were synthesized by solution route. First, I have modelled my reference (bulk YbVO4) with two so2, N and R as free parameters. So2-1 is for first two shell and so2-2 is for rest other shells. If I use single so2, the value is obtained to be around 0.9 with unsatisfactory fit whereas second so2-2 incorporation leads to satisfied fit with large uncertainty on the obtained number i.e., (2.04 +/- 0.9). Using the same strategy, I could successfully fit the nanoparticles again with large so2-2 (1.79). From literature and IFEFFIT earlier discussion, i understood that so2 should be between 0.8-1.2 value. Further, so2-2 is found to well correlated with ss1 and delc (a parameter to define the movement of atoms in c direction). Among two, the former parameter (ss1) strongly correlate with so2 and take value of 0.8 and 1.9 for fixed and varying ss1, respectively, during the fit. This large value of so2 cannot be controlled with the used model. Also, I have tried to fit the curve with fixed so2 i.e., below 1 but leads to unsatisfactory fit. For your info, i have tabulated various strategy and the resultant parameters. After considering Scott suggestions (and previous posts), i have concluded the following: Since, so2 is used as a normalization parameter and with the estimated uncertainty, i would like to consider the obtained number as reasonable value to normalize the unknown to calculate the CN in other systems. Is this strategy good to calculate the CN in unknown? and later to describe the trend on obtained parameters?

Regards,
Raj

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