BSE coefficient

[Ben Buse]

Hi,

Is it possible to output BSE coefficient from DTSAII, I can't see it in the GUI reports file, have I missed it?

Thanks

Ben

[jrminter]

Ben,

I have a function that does it via MonteCarlo simulation for multilayer films. It is in my jmGen.py helper library on github https://github.com/jrminter/dtsa2Scripts/tree/master/jmGen. The function is multiFilmBSE. I put this python file
with the other DTSA python functions in the lib/dtsa folder. I am attaching the help string below. Hope this helps

Best regards,
John

    """multiFilmBSE(layers, det, e0=20.0, withPoisson=True,
                    nTraj=1000, dose=60.0, bOutFull=False,
                    outDir='C:/Temp/',fullOutFile='BSE.csv')

    Monte Carlo simulate the backscattered fraction from a multilayer
    thin film.

    Parameters
    ----------
    layers - an iterable list of [material,thickness].
        Note thematerials must have associated densities.
    e0 - float (20)
        The accekerating voltage in kV
    nTraj - integer
        The number of trajectories to run
    bOutFull - boolean (False)
        A flag to write the full data to a csv file
    outDir - string ('C:/Temp/')
        Path for full output
    fullOutFile - string ('BSE.csv')
        name for full output file


    Returns
    -------
    tuple - (layers, e0, nTraj, backscatterFraction,
             forwardscatterFraction)

    Example
    -------
    import dtsa2.jmGen as jmg
    al      = material("Al",  density=2.70)
    c       = material("C",   density=2.267)
    zno     = material("ZnO", density=5.61)
    si      = material("Si",  density=2.3296)

    layers = [ [c,   20*1.0e-9],
               [zno, 20*1.0e-9],
               [al,  20*1.0e-9],
               [si,  50.0e-6]
             ]

    a = jmg.multiFilmBSE(layers, 7.0, nTraj=10000)
    print(a)

[Ben Buse]

Hi John,

Thanks that is great. Which part of the DTSA code toggles BSE output? I thinking could it be applied to a bulk using mcSimulate3- but I guess the easiest thing is to use your script with 2 layers the same composition. Just tried it - it works!

Thanks

Ben

[jrminter]

One can indeed use either. I would like to make some observations:

1. It really helps to use more trajectories to get better estimates of the BSE fraction. I'm running 10000 in the examples that follow.
2. There are small differences between the two approaches...

Here is a script that uses the MC3 backscatter function for a bulk element

import dtsa2.mcSimulate3 as mc3
al = material("Al",  density=2.70)
au = material("Au", density=19.3)
res = mc3.backscatter(al, 20, 10000)
print(res)
res = mc3.backscatter(au, 20, 10000)
print(res)

And here is the output for 20 kV

Running /Users/jrminter/Desktop/test-mc3-ver.py
Results -> /Users/jrminter/NIST DTSA-II Reports/2018/May/22-May-2018/Backscatter9179393270919868562.csv
(0.2112, 0.0)
Results -> /Users/jrminter/NIST DTSA-II Reports/2018/May/22-May-2018/Backscatter2495095179893730132.csv
(0.4869, 0.0)
Elapse: 0:01:15.2

Using the my function for a single layer (I set it to 500 microns) looks like this:

import dtsa2.jmGen as jmg
al      = material("Al",  density=2.70)
# a bulk Al film
layers = [[al,  500*1.0e-6]]
a = jmg.multiFilmBSE(layers, 20.0, nTraj=10000)
print(a)
# a bulk Au film
au = material("Au", density=19.3)
layers = [[au,  500*1.0e-6]]
a = jmg.multiFilmBSE(layers, 20.0, nTraj=10000)
print(a)

And here is the output

Running /Users/jrminter/Desktop/test-bse.py note it reports thickness in m...
([[Al, 0.0005]], 20.0, 10000, 0.2034, 0.0)
([[Au, 0.0005]], 20.0, 10000, 0.4948, 0.0)
Elapse: 0:01:15.

Best regards,
John

[Ben Buse]

Hi John,

Thanks again, that's great.

40000
(0.200275, 0.0)
(0.49215, 0.0)

([[Al, 0.0005]], 20.0, 40000, 0.203075, 0.0)
([[Au, 0.0005]], 20.0, 40000, 0.487825, 0.0)

([[Al, 0.0005]], 20.0, 400000, 0.200415, 0.0)

Al slightly high, Reimer book value [0.159 @17.3kV, 0.151 @ 25.2kV]; [penepma 0.161]. Gold is good [0.492 @ 17.3kV, 50.1 @ 25.2kV]