Artificial neural network and fuzzy clustering - New tools for evaluation of depth profile data?

Depth profiling has been performed by using Auger electron spectrometry (AE S) and X-ray photoelectron spectrometry (XPS) in combination with Ar-ion sp uttering. The data obtained by both surface-analytical methods have been ev aluated by means of factor analysis and afterwards by applying an artificia l neural network or fuzzy clustering in order to determine the compositiona l layering of different samples such as a Cr2O3/CrN sandwich layer, tarnish layers on a nickel based alloy and on steel, and the coating of a Si3N4 ce ramic powder. The applied artificial neural network was a Kohonen network. It turned out that the method of fuzzy c-means clustering was more successf ul than Kohonen network due to the fact that fuzzy c-means clustering start s with more input information which can be obtained from factor analysis.