Recently, I have written a Python program, which can fit the XPS data to a Gaussian distribution. The sample I used in XPS experiment is PMMA. The data were fit well to the Gaussian distribution with an extremely small error that it can reproduce the correct stoichiometric ratio. Nevertheless, I have found that it is also common to fit the data to a pseudo Voigt profile. I know pseudo Voigt profile is a linear combination of Gaussian function and Lorentzian function. What would happen if I take the Gaussian function only and ignore the Lorentzian function?
Hi Chi
You correctly mentioned that its a common practice to use VOIGT profile while fitting XPS narrow scans. It depends on your sample if you could use only Gaussian profile. The line profile of XPS is lorentzian in nature and due to instrumental band broadening, you get more of a Gaussian character. Having said that, for a polymer sample, you could probably get away with using 100 % Gaussian profile and get minimal residuals. That is your case. If you are fitting a metallic sample, it will have some lorentzian character to it, and require a VOIGT function to fit. If you try to fit a metallic peak with just a Gaussian profile, you will get relatively high residuals.
Let me know if this answers your question. please feel free to ask any questions you might have.
Good Luck!!
Interesting! I am only working with polymer sample at the moment. Thank you so much for your answer.
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