Analysis of multicomponent mass spectra applying Bayesian probability theory

In this paper we develop a method for the decomposition of mass spectra of gas mixtures, together with the relevant calibration measurements. The meth od is based on Bayesian probability theory. Given a set of spectra, the alg orithm returns the relative concentrations and the associated margin of con fidence for each component of the mixture. In addition to the concentration s, such a data set enables the derivation of improved values of the crackin g coefficients of all contributing species, even for those components for w hich the set does not contain a calibration measurement. This latter featur e also allows one to analyze mixtures that contain radicals in addition to stable molecules. As an example, we analyze and discuss the mass spectra ob tained from the pyrolysis of azomethane, which contain the radical CH3 apar t from nitrogen and C-1- and C-2-hydrocarbons. Copyright (C) 2001 John Wile y & Sons, Ltd.