Algorithms and software for U-Pb geochronology by LA-ICPMS

被引:23
|
作者
McLean, Noah M. [1 ,2 ]
Bowring, James F. [3 ]
Gehrels, George [4 ]
机构
[1] MIT, Dept Earth Atmospher & Planetary Sci, Cambridge, MA 02139 USA
[2] Univ Kansas, Dept Geol, Lawrence, KS 66045 USA
[3] Coll Charleston, Dept Comp Sci, Charleston, SC 29401 USA
[4] Univ Arizona, Dept Geosci, Tucson, AZ 85721 USA
基金
美国国家科学基金会;
关键词
geochronology; cyberinfrastructure; U-Pb; statistics; uncertainty; metrology;
D O I
10.1002/2015GC006097
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The past 15 years have produced numerous innovations in geochronology, including experimental methods, instrumentation, and software that are revolutionizing the acquisition and application of geochronological data. For example, exciting advances are being driven by Laser-Ablation ICP Mass Spectrometry (LA-ICPMS), which allows for rapid determination of U-Th-Pb ages with 10s of micrometer-scale spatial resolution. This method has become the most commonly applied tool for dating zircons, constraining a host of geological problems. The LA-ICPMS community is now faced with archiving these data with associated analytical results and, more importantly, ensuring that data meet the highest standards for precision and accuracy and that interlaboratory biases are minimized. However, there is little consensus with regard to analytical strategies and data reduction protocols for LA-ICPMS geochronology. The result is systematic interlaboratory bias and both underestimation and overestimation of uncertainties on calculated dates that, in turn, decrease the value of data in repositories such as EarthChem, which archives data and analytical results from participating laboratories. We present free open-source software that implements new algorithms for evaluating and resolving many of these discrepancies. This solution is the result of a collaborative effort to extend the U-Pb_Redux software for the ID-TIMS community to the LA-ICPMS community. Now named ET_Redux, our new software automates the analytical and scientific workflows of data acquisition, statistical filtering, data analysis and interpretation, publication, community-based archiving, and the compilation and comparison of data from different laboratories to support collaborative science.
引用
收藏
页码:2480 / 2496
页数:17
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