| AVS 66th International Symposium & Exhibition | |
| Applied Surface Science Division | Tuesday Sessions |
| Session AS+BI+RA-TuM |
| Session: | Quantitative Surface Analysis III/Other Surface Analysis Methods |
| Presenter: | Lev Gelb, University of Texas at Dallas |
| Authors: | L.D. Gelb, University of Texas at Dallas A.V. Walker, University of Texas at Dallas |
| Correspondent: | Click to Email |
We compare strategies for analyzing high-mass resolution TOF SIMS data sets affected by detector saturation. The detectors used in many instruments undercount ions due to saturation effects. If two or more ions arrive within a very short interval (the "dead time") only the first ion is recorded. This changes both the total number of ions collected and their statistical distribution. The dead time is typically short enough that only ions of the same nominal mass are affected, but a significant fraction of the total ions reaching the detector may still be missed.
We demonstrate an approach to correct for dead time errors in which a probability model for the detector behavior is developed and used in peak fitting of the "uncorrected" data. This approach has many advantages over previous methods which required an estimate of the variance, and it behaves better under conditions of poor data quality (low counts or high saturation.)
Using both synthetic and experimental data, we examine how saturation affects apparent peak shape, position and intensity, the effects of background on estimated peak position and shape, the dependence of peak-location precision on the total number of counts, how interference between satellite peaks is best accounted for, and the biases exhibited by different data analyses. Finally, we extend these methods to imaging data taken at high mass resolution and compare the results obtained with analyses performed at unit-mass resolution.