Multivariate data analysis for depth resolved chemical classification and quantification of sulfur in SNMS

Abstract The quantification of elements in quadrupole based SNMS is hampered by superpositions of atomic and cluster signals. Moreover, the conventional SNMS data evaluation employs only atomic signals to determine elemental concentrations, which not allows any chemical specifications of the determined elements. Improvements in the elemental quantification and additional chemical information can be obtained from kinetic energy analysis and the inclusion of molecular signals into mass spectra evaluation. With the help of multivariate data analysis techniques, the combined information is used for the first time for a quantitative and chemically distinctive determination of sulfur. The kinetic energy analysis, used to solve the interference of sulfur with O 2 at masses 32–34 D, turned out to be highly important for the new type of evaluation.