Evaluating cluster counting of Cs complexes through the study of nitrogen implanted zirconium

The cluster counting method (including all Cs complexes missed out in the usage of single Cs complex per element) has previously been reported to provide a significantly better composition estimate than using a single Cs complex per element, for a D9 steel sample. The current study evaluates this method with a nitrogen-implanted zirconium specimen with high oxygen impurity concentrations. Therefore, this system is prone to experiencing strong matrix effects. Quantified elemental depth profiles of the specimen were obtained using XPS to compare with SIMS results. The study confirms that cluster counting of Cs complexes yields significantly better composition estimates than the single Cs complex approach. While fluorine and chlorine are trace-level impurities, their concentrations dominate the composition estimates in both cluster counted and single Cs-complex approaches because the [Formula: see text] complexes of halogens exhibit orders of magnitude higher sensitivities than those of the other elements. Applying relative sensitivity factors of a few tens for these species renders the concentrations of these impurities insignificant. With this correction, the composition estimates by both Cs complex methods improved towards that provided by XPS. At this stage also, the match of the cluster-counted composition with the XPS estimate remains markedly better than that by the single Cs-complex estimate. Additionally, the sensitivity factor values for all cluster-counted Cs complexes were incorporated and adjusted to ensure that the elemental compositions obtained by SIMS matched exactly with those determined by XPS. These relative sensitivity factors are also provided for academic purposes, aiding future studies on secondary ion and cluster formation. Notably, a comparable match could not be achieved between the single CsX species and the XPS profiles, even when varying the sensitivity factor values for the individual CsX species. Furthermore, the cluster counting method provides a means to estimate the sputter rate at each depth of the depth profile.