Correction of mass bias drift in inductively coupled plasma mass spectrometry measurements of zinc isotope ratios using gallium as an isotope ratio internal standard

Abstract

Gallium was used as an isotope ratio internal standard to correct the mass-bias drift of an inductively coupled plasma mass spectrometer employed for zinc isotope ratio determinations. The Zn isotope ratios were measured to establish dietary Zn absorption in nutritional studies using ⁶⁷Zn, ⁶⁸Zn and ⁷⁰Zn as tracers and ⁶⁶Zn as the reference isotope. Natural abundance Zn standards were analysed before and after each group of five samples. All samples and standards were adjusted to a common Zn concentration and spiked with Ga to obtain a ⁶⁹Ga intensity roughly equal to that of ⁶⁶Zn. The measured ⁷¹Ga:⁶⁹Ga ratios served to monitor and correct for changes of the instrumental mass bias. Adding the two Ga isotopes to the data acquisition programme increased the cycle time of the mass spectrometer by only 25% and had no discernible effect on the precision of individual Zn isotope ratio determinations. Three different methods for correcting the measured Zn isotope ratios for mass-bias drift were compared: (i) simple division of the Zn isotope ratios by the Ga isotope ratios; (ii) correction based on a power law; and (iii) correction by a regression method which uses the relationships between the temporal changes of the ⁷¹Ga:⁶⁹Ga ratio and the three Zn isotope ratios for each analytical batch. The correction based on regression consistently gave the best results because it avoided undercorrection or overcorrection of mass-bias drift; even when there was little or no correlation between the drift of the Zn and Ga isotope ratios, the range of variation of the corrected data was not increased. On the average, the regression correction method reduced the drift of the Zn isotope ratios by a factor of 2.5. The study included the derivation of equations which can be used to predict the achievable improvement in precision for the simple division and regression correction methods directly from the measured data, i.e., without actually applying the corrections.