Multivariate analysis of time-resolved mass spectral data

Abstract

Multvariate analysis of time-resolved pyrolysis/mass spectrometric data is described. The approach is based on the variance diagram (VARDIA), a recently developed technique that quantifies the clustering of variables in two-dimensional factor analysis (sub)-spaces in a rotational scanning procedure. A maximum in the VARDIA plot indicates a correlated behavior of the mass variables, indicating a common origin. This common origin is generally caused by a change in the concentration of a chemical component. With this information the “factor spectrum” and the scores of the component can be retrieved. For time-resolved serial data, consideration of the clustering behavior of the variables as a function of time is more appropriate than a rotational scanning procedure. Adaptation of the VARDIA for serial data, such as time-resolved data, is described. This approach has the advantage that all the factors can be used. It will be shown that the resolution of the obtained curve than the total ion current curve as a function of time. Examples will be given for time-resolved data of coal, rubber and wood samples.