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

Area of Science:

• Materials Science
• Surface Analysis
• Analytical Chemistry

Background:

• Secondary Ion Mass Spectrometry (SIMS) is crucial for elemental depth profiling.
• Accurate quantification in SIMS can be challenging due to matrix effects and varying secondary ion complex formation.
• Previous studies indicated cluster counting improves composition estimates over single complex analysis.

Purpose of the Study:

• To evaluate the cluster counting method for SIMS depth profiling on a nitrogen-implanted zirconium specimen with high oxygen impurities.
• To compare the accuracy of cluster counting versus single Cs complex analysis against X-ray Photoelectron Spectroscopy (XPS) data.
• To investigate the impact of trace impurities like fluorine and chlorine on composition estimates.

Main Methods:

• SIMS depth profiling was performed on a nitrogen-implanted zirconium specimen.
• Elemental composition was quantified using both cluster counting and single Cs complex methods.
• Results were cross-validated with XPS depth profiling data.

Main Results:

• The cluster counting method provided significantly more accurate elemental composition estimates than the single Cs complex approach.
• Trace impurities (fluorine, chlorine) initially dominated estimates due to high sensitivity, but relative sensitivity factors corrected this.
• Adjusted relative sensitivity factors for cluster-counted Cs complexes enabled exact matching of SIMS and XPS elemental compositions.

Conclusions:

• Cluster counting is a superior method for SIMS depth profiling, yielding more accurate elemental composition estimates, particularly in challenging matrices.
• The method offers improved quantification, even with significant matrix effects and trace impurities.
• The study provides valuable relative sensitivity factors for Cs complexes, aiding future SIMS research and sputter rate estimation.