In secondary ion mass spectrometry measurement systems, the count rate of isotopes may vary in time as a particle is consumed during the analysis. Since isotopes are measured sequentially, this drift can introduce systematic error into the estimate of the ratio of any two isotopes. We correct the measurements for drift by aligning the time series of isotopic pairs using a linear interpolation approach. We estimate an isotopic ratio for each of two cases. In one case the time series of the more abundant isotope is aligned with respect to the time series of the less abundant isotope. In the second case the less abundant isotope is aligned with respect to the more abundant one. We average both of these estimates to get a drift-corrected estimate. We present an analytical formula for the random uncertainty of the isotopic ratio that accounts for correlation introduced by interpolation. We also present an approximate hypothesis test procedure to detect and quantify possible temporal variation of the measured isotopic ratio during a single analysis. In a Monte Carlo study, the performance of the methods is quantified based on analysis of simulated data with complexity similar to that of real data generated by a secondary ion mass spectrometer.
All Science Journal Classification (ASJC) codes
- Condensed Matter Physics
- Physical and Theoretical Chemistry