Improved laser ablation U-Pb zircon geochronology through robust downhole fractionation correction
Article first published online: 26 MAR 2010
Copyright 2010 by the American Geophysical Union.
Geochemistry, Geophysics, Geosystems
Volume 11, Issue 3, March 2010
How to Cite
2010), Improved laser ablation U-Pb zircon geochronology through robust downhole fractionation correction, Geochem. Geophys. Geosyst., 11, Q0AA06, doi:10.1029/2009GC002618., , , , , and (
- Issue published online: 26 MAR 2010
- Article first published online: 26 MAR 2010
- Manuscript Accepted: 5 JAN 2010
- Manuscript Revised: 18 DEC 2009
- Manuscript Received: 11 MAY 2009
- laser ablation;
 Elemental fractionation effects during analysis are the most significant impediment to obtaining precise and accurate U-Pb ages by laser ablation ICPMS. Several methods have been proposed to minimize the degree of downhole fractionation, typically by rastering or limiting acquisition to relatively short intervals of time, but these compromise minimum target size or the temporal resolution of data. Alternatively, other methods have been developed which attempt to correct for the effects of downhole elemental fractionation. A common feature of all these techniques, however, is that they impose an expected model of elemental fractionation behavior; thus, any variance in actual fractionation response between laboratories, mineral types, or matrix types cannot be easily accommodated. Here we investigate an alternate approach that aims to reverse the problem by first observing the elemental fractionation response and then applying an appropriate (and often unique) model to the data. This approach has the versatility to treat data from any laboratory, regardless of the expression of downhole fractionation under any given set of analytical conditions. We demonstrate that the use of more complex models of elemental fractionation such as exponential curves and smoothed cubic splines can efficiently correct complex fractionation trends, allowing detection of spatial heterogeneities, while simultaneously maintaining data quality. We present a data reduction module for use with the Iolite software package that implements this methodology and which may provide the means for simpler interlaboratory comparisons and, perhaps most importantly, enable the rapid reduction of large quantities of data with maximum feedback to the user at each stage.