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Automated Extraction of a Five‐Year LA ‐ ICP ‐ MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long‐Term Data Quality, Optimisation and Laser Cell Homogeneity
Author(s) -
Evans David,
Müller Wolfgang
Publication year - 2018
Publication title -
geostandards and geoanalytical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.037
H-Index - 73
eISSN - 1751-908X
pISSN - 1639-4488
DOI - 10.1111/ggr.12204
Subject(s) - calibration , trace element , nist , fractionation , range (aeronautics) , data quality , data set , analytical chemistry (journal) , set (abstract data type) , reference data , volume (thermodynamics) , chemistry , mineralogy , materials science , computer science , data mining , mathematics , physics , statistics , chromatography , engineering , metallurgy , thermodynamics , metric (unit) , operations management , natural language processing , composite material , programming language
LA ‐ ICP ‐ MS is increasingly applied to obtain quantitative multi‐element data with minimal sample preparation, usually achieved by calibration using reference materials ( RM s). However, some ubiquitous RM s, for example the NIST SRM 61× series glasses, suffer from reported value uncertainties for certain elements. Moreover, no long‐term data set of analyses conducted over a range of ablation and tuning conditions exists. Thus, there has been little rigorous examination of the extent to which offsets between measured and reported values are the result of error in these values rather than analytically induced fractionation. We present new software (‘ LA ‐ MINE ’), capable of extracting LA ‐ ICP ‐ MS data with no user input, and apply this to our system, yielding over 5 years of data (~ 5700 analyses of ten glass and carbonate RM s). We examine the relative importance of systematic analytical bias and possible error in reported values through a mass‐specific breakdown of fourteen of the most commonly determined elements. Furthermore, these data, obtained under a wide range of different ablation conditions, enable specific recommendations of how data quality may be improved, for example the role of diatomic gas, the effect of differential inter‐glass fractionation factors and choice of transport tubing material. Finally, these data demonstrate that the two‐volume Laurin ablation cell is characterised by no discernible spatial heterogeneity in measured trace element ratios.