Tag Archives: computation

Local absorption computation much faster

The computation of depth dependent, local absorption in layer stacks is much faster now.

This improvement speeds up objects of type “Local absorption” in the list of distributions, but also objects of type “Layer absorption” and “Charge carrier generation” in the list of spectra.

In CODE the computation of the integral quantity “Photo current” benefits from the enhancement.

Special computations: Parameter variation enhanced

CODE 3.98

The capabilities of ‘parameter variation’ objects in the list of special computations have been enhanced. You can now define ‘offset functions’ which are computed once before the parameter variation is executed. The example below discusses an application of this feature.

Suppose you are computing the dependence of color coorinates a* and b* on layer thicknesses. For each layer you generate an ‘arrow diagram’ showing how the position of the layer stack in the a*-b*-plane changes with thickness modifications. Superimposing 3 of such diagrams would give a graph like this:

originalUnfortunately the model does not perfectly reproduce the measured reflectance spectrum. As a result, the ‘measured’ color position is different from the simulated one. In this situation you might want to display the arrows at the ‘measured’ color position, believing that the direction and the size of the arrows will be similar there. A graph like this would show operators where they are with their real product and where they would go with thickness variations.

You can generate the desired offset the following way. Compute a* and b* of the simulated spectrum in the list of integral quantities as item 1 and 2, and compute the a* and b* of the measured spectrum as items 4 and 5. In function definitions you can refer to these numbers as iq(1), iq(2), iq(4) and iq(5), respectively. The dialog for the first parameter variation object (modifying the TiO2 layer thickness) would look like this:


Defining similar offsets for the other two layer thickness variation objects you will get a shifted arrow graph, centered at the color position of the measured reflectance:

shiftedObviously, you should use this feature only in cases where you are sure that the applied offset is justified and does not lead to wrong conclusions.



BREIN prediction window gets measured spectra

Measured spectra are now passed to the prediction window. In order to get this working the prediction configuration has to have spectrum objects with the same names as the Bright Eye which triggers the prediction update. Only the spectra recorded at the “trigger position” are sent.

In order to use this feature you have to get brein.exe and bright_eye_traverse.exe programs generated after September 13, 2014.

Here is the BREIN download page.