When approaching a deconvolution in XPS, it is important to consider which peak shapes you may wish to use to best represent your data. Below we outline and describe some of the many lineshapes available in CasaXPS for peak fitting.

Care should be taken to suitable lineshapes depending on the background chosen. For example Shirley backgrounds reduce asymmetry in the resultant peaks, compared with say a Tougaard background.

The LA lineshape

The most useful lineshape in data description is known as the LA lineshape, which takes the general form of LA (α, β, m).

α and β modify the tail shape at the higher and lower binding energy side of the peak respectively, with an increase in value reducing the spread of the tail.

m may be modified between 0 and 499 and controls the width of the Gaussian function to be convoluted with the Lorentzian function to create the peak.

In it’s more simple form (for symmetric peaks), it may be used in the following way:

LA(α, m)

In which α represents both α and β where α = β

Asymmetric modifiers

To describe asymmetric peaks the LA lineshape may use unique values for α and β to control high BE tail shape.

The LF function

The LF function is identical to the LA function except it includes an additional parameter, it takes the general form:

LF(α, β, w, m)

Where w may force the high binding energy tail towards the background to improve the fit.

The GL lineshape

We mention this since it is still a commonly used lineshape, however we would recommend sticking to the LA lineshape in general as a slightly more malleable and robust representation of the experimental data.

The Doniach-Sunjic lineshape

The GL-modified DS lineshape uses the general form:

DS(α, n)GL(X)

Where α is an asymmetry parameter and n (0-499) controls convolution width. Modification of the GL parameter controls tail spread on both energy sides.

This line shape represents a very good theoretical evaluation of asymmetric XPS peaks, however experimentally it often fails due to a lack of limits.