Multivariate statistical analysis of particle x-ray spectra

Multivariate statistical analysis (MSA) is a powerful tool for the analysis of series of spectra. This paper explores an application of MSA to a series of energy dispersive X-ray (EDX) spectra acquired in the scanning electron microscope (SEM) from a series of particles. The raw data were series of spectra previously acquired to test analytical procedures for trace element detection. This paper explores the possibility of performing the trace element detection with MSA components that have been extracted from the raw data without any a priori assumptions about the information content of the particle spectra. Particles were prepared from two analytical glasses, dispersed onto carbon substrates and coated with carbon. The compositions of the two glasses are substantially similar, except that one glass (K-3106) contains 0.7 wt.% Fe, whereas the other glass (K-3069) does not contain Fe at a detectable level. Spectra were acquired with a 20 kV accelerating voltage from 35 different particles of each glass, with particle diameters that ranged from 1--10 {micro}m, and with acquisition times of 15, 60 and 200 S. A test data file of 75 spectra was composed for each acquisition time by arranging the 70 acquired spectra in no particular order in a composite file, and inserting 5 duplicate spectra as a test of reproducibility. MSA was performed using software developed at Oak Ridge National Laboratory