Decomposition of multicomponent mass spectra using Bayesian probability theory

Abstract

We present a method for the decomposition of the mass spectra of mixed gases using Bayesian probability theory. The method works without any calibration measurement and therefore applies also to the analysis of spectra containing unstable species. For the example of mixtures of three different hydrocarbon gases the algorithm provides concentrations and cracking coefficients of each mixture component and also their confidence intervals. The amount of information needed to obtain reliable results and its relation to the accuracy of our analysis are discussed.

Ion energy distributions for the identification of active species and processes in low pressure hollow cathode discharges

“…Although the detailed mechanisms of the dissociative ionization of water and ammonia are not so well known as those of the diatomic molecules discussed previously, it seems that NH + and OH + are formed with little kinetic energy (see [55][56][57] and references therein). Concurrent processes leading to OH + and NH + would be the ion molecule reactions [39] O + + H 2 → OH + + H k 10 = 1.62 × 10 -9 cm 3 s -1 (10) N + + H 2 → NH + + H k 11 = 5.0 × 10 -10 cm 3 s -1 (11) with large rate coefficients. In these reactions, the comparatively heavy atomic ions formed with high kinetic energy through dissociative ionization, behave as "spectators" [58] (i.e.…”

Estimation of low concentrations in the presence of high concentrations using Bayesian algorithms for interpretation of spectrophotometric data

“…Let us mention only a few among most recent examples reported in the relevant literature. The Bayesian approach has been applied: in general-purpose image processing, for denoising images [33,34]; in civil engineering, for prediction of building air-conditioning load [35]; in pattern recognition, for identification of handwritten symbols [36]; in medical imaging, for removing speckle from ultrasound medical images [37] and for reconstruction of tomographic images [38][39][40]; in biomedical engineering, for analysis of electroencephalograms [41]; in spectrometry, for estimation of concentrations of three hydrocarbon gases in their mixtures [42]. …”

The scavenger effect – Does it work?

“…In the literature different diagnostics were applied to study the interaction between nitrogen and hydrogen containing mixtures. In fact, one can find a lot of information for totally different experimental conditions: catalyser based HCN production at atmospheric pressure [3] , production of synthetic materials and gas phase reactions in microwave plasmas [4,5], low temperature plasma studies [6,7,12,13] as well as experiments in fusion experiments [8]. The spectrum of intermediate species and final products covers nearly all possibilities for C x H y N z (for x = 1,2,.. y =1…6 , z =1,2).…”

“…Another powerful method to evaluate the complex mass spectra and their cracking pattern is Bayesian data analysis [11,12]. It can even handle reactive species, but additional information is often needed when such complex spectra like in the case of CH 4 /N 2 mixtures are analysed.…”