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Evolutionary Algorithm for Automated IBA Spectra Fitting

Heller, R.

Abstract

In order to extract chemical compositions and layer thicknesses of layered samples from IBA spectra (RBS, ERD, etc.) experimentalists usually have to take the following approach: Simulation of a theoretical spectrum for an initial target configuration and comparison to the measured data followed by the successive adjustment of the target model iteratively until simulation result and experimental spectrum fit together. For multi-layer samples this procedure can get rather time consuming, especially when a series of similar samples with varying layer thickness and/or stoichiometry has to be analyzed.
Although modern IBA spectrum simulation software like SimNRA[1] or WINDF[2] have become quite powerful and handy tools, the analysis of IBA spectra consumes still a significant fraction of an IBA scientist’s working time. SimNRA offers therefore the opportunity to partially fit layer thicknesses and/or elemental ratios for a given layer within a certain region of a spectrum. WINDF goes a step further and has an automated spectrum fitting included which is based on a simulated annealing algorithm. However, it takes the user quite some time to set up the boundary conditions and fit parameters until the actual fit procedure can be initiated. Furthermore, the outcome of the fit procedure in some cases requires multiple re-adjustments of the boundary conditions / fit parameters.
In the present contribution, we present a new approach for automated IBA spectra fitting by implementing an evolutionary algorithm. We will show that this powerful algorithm is very well suited and robust for complete and fast IBA spectrum fitting with minimum input of boundary conditions. Furthermore, the benefits of this algorithm over other ones and the particular differences to simulated annealing are pointed out.
Based on this algorithm a software package has been developed, written in the programming language Java that is platform independent and comprises a clean and easy-to-use graphical user interface. We will introduce this software in a basic overview.

Keywords: IBA Fit routine evolutionary algorithm

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Permalink: https://www.hzdr.de/publications/Publ-26924