Automatic analysis of Rutherford backscattering spectrometry spectra

It has been shown that Bayesian statistics is a powerful tool in the analys is of ion beam analysis (IBA) data. Past work has shown its applicability t o the deconvolution of the detector response function from micro-Rutherford backscattering spectrometry (RBS) and micro-proton-induced X-ray emission (PIXE) spectra, subtraction of the background from PIXE spectra, the extrac tion of depth profiles from PIXE spectra using two detectors and the extrac tion of depth profiles from RBS spectra. However, the method has sonic draw backs, e.g. numerical integration, alpha -marginalisation, etc., all of whi ch result in very long computation times. In this paper, preliminary result s are presented from the application of the Bayesian theory to the automati c extraction of depth profiles from RBS spectra with the aim of creating an online RBS analysis program, which has the advantage of minimal user input while still being as computationally intensive as conventional RBS analysi s packages to extract a depth profile. (C) 2001 Elsevier Science B.V. All r ights reserved.