We start with graphene, since this is the simplest system – being a single peak.

You may notice that this peak presents a distinct asymmetry. This is due to the conductive nature of the material.

In order to model this ,we need to alter our lineshape.

For graphene, we are going to use an LF lineshape. Thsi is a voigt type function in which a modifier is used to dampen the tail spread.

LF (a, b, m, X)

a = high BE tail spread

b = low BE tail spread

m = damping factor (1 – 499) with 1 being maximum damping

X = Gaussian width

Lets start by putting in LF(0.6,1.5,25,50) into the Line Shape box in the component parameters section.

We’re also going to put in a small GL(30) peak at ~289 eV to model the pi-pi* shake up.

Try playing with the numbers in the lineshape to see how they affect the peak shape!

Gold displays relatively low asymmetry, and can actually be fit with a GL(90) lineshape. Again, play with the GL modifier (the integer in brackets) to see how this affects peak shape.

Silver has a slightly greater asymmetry than gold and as such, if we try and fit a standard GL or similar lineshape, the model will not fit the data.

Here – we use an LA(1,1.1,143) lineshape (a = 1, b = 1.1) to account for this slight asymmetry. Note – we also must put in some symmetric peaks – LA(1.53,243) – to model the small plasmons in the metal data.

A closer look at the parameters is found below:

For Iron, we’re going to make this slightly easier – since the asymmetry is high – and only fit the  Fe 2p 3/2 peak! Put a region around the major emission and try fitting a single peak.

LF(0.53,1.7,30,70)

Play around with the parameters to see if you can improve the fit!

Nickel is a fun example – since we need to model the asymmetry AND the surface and bulk plasmons associated with nickel metal. For this we are going to use the parameters from the work by Mark Biesinger available here.

Ni 2p: A(0.4,0.55,10)GL(30)

Plasmon (+3.65 eV): GL(30)

Plasmon (+6.03 eV): GL(30)

Now, when we put in our plasmons we need to ensure the peak parameters remain consistent with the reference. So we have 3 columns – metal (A), plasmon 1 (B) and plasmon 2 (C).

Plasmon 1: Area constraint = A * 0.0703518, FWHM constraint = A * 2.48, position constraint = A + 3.65

Plasmon 2: Area constraint = A * 0.18593, FWHM constraint = A * 2.48, position constraint = A + 6.03.

Palladium: LA(1.9,7,2) (as per Mark Biesinger reference)

Open the Ta metal vamas block.

Ta metal peaks: LA(1.1,7,25)

Now, this one is a little tricky – there is a small amount of oxide still on this sample!! So we now need to start adding a second set of features to model this!! We can fit the oxide with a GL(30) lineshape but the area, position and fwhm constraint should still be the same as the metal!!

Here is a closer look at the parameters:

For bonus points – why not try and fit the top example yourself…