Don’t Fit!

We can obtain all of the information we need just from looking at the line profile of this spectrum. Ti 4+ produces a simple doublet which can be described in terms of:

Area(1/2)  = Area(3/2) x 0.5

FWHM(1/2) = FWHM(3/2) x 

Position(1/2) = Position(3/2) + 5.7 eV (Binding energy)

If you need a reminder of where these come from, check out our article on spin-orbit splitting

Note: Ti is one of a few rare cases where FWHM (1/2) =/= FWHM (3/2). To learn why, read our article on Coster-Kronig transitions.

Fit!

In this case, we will need to know a bit more about the data in order to confirm the identity of the peak. Knowledge of the peak position can be obtained through simple analysis of the raw data, though for a more precise determination, spectral envelopes will help in compensating for the background and the metal peak.

Furthermore, quantification of the peak areas will allow us to compare the atomic % of the unknown silver species with the other elements and chemical entities discovered in the data analysis and help determine a likely  identity.

Fit!

While the researcher only wants a yes or no answer – it is hard to say if there is one or two species here without deconvolution, since we must account for the background. The fact that the doublet is roughly the same intensity would suggest that there is a competing emission within the high binding energy peak and, indeed, if you do deconvolute the spectra you will find that underneath the Pt 4f 5/2 peak of the metal there is infact a Pt 4f 7/2 oxidic peak!

Don’t Fit!

With no requirements for quantitative assessment, the mere presence of a clear and obvious carbonate peak (~290 eV) may answer the research question. While fitting this spectra would prove trivial, there are no competing emissions in the region and the carbonate signal provides all the detail we need.

Don’t Fit!

We covered ultiplet spitting in an earlier session and it really does make fitting first row TMs tricky! It’s of course possible to develop peak models based on theory or standards and deconvolute or perform linear combination fitting – but given this user is brand new to XPS, they might be advised to begin by simple using qualitative techniques to describe the data by comparing it with well known literature standards. In the case of iron, the position of the small satellite feature between the major photoemissions gives insight into the specific oxidation state.