Simon A Mischel1, Regina Mertz-Kraus1, Klaus Peter Jochum2, Denis Scholz1. 1. Institute for Geosciences, Johannes Gutenberg University of Mainz, J.-J.-Becher Weg 21, 55128, Mainz, Germany. 2. Climate Geochemistry & Biogeochemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020, Mainz, Germany.
Abstract
RATIONALE: High spatial resolution Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICPMS) determination of trace element concentrations is of great interest for geological and environmental studies. Data reduction is a very important aspect of LA-ICP-MS, and several commercial programs for handling LA-ICPMS trace element data are available. Each of these software packages has its specific advantages and disadvantages. METHODS: Here we present TERMITE, an R script for the reduction of LA-ICPMS data, which can reduce both spot and line scan measurements. Several parameters can be adjusted by the user, who does not necessarily need prior knowledge in R. Currently, ten reference materials with different matrices for calibration of LA-ICPMS data are implemented, and additional reference materials can be added by the user. TERMITE also provides an optional outlier test, and the results are provided graphically (as a pdf file) as well as numerically (as a csv file). RESULTS: As an example, we apply TERMITE to a speleothem sample and compare the results with those obtained using the commercial software GLITTER. The two programs give similar results. TERMITE is particularly useful for samples that are homogeneous with respect to their major element composition (in particular for the element used as an internal standard) and when many measurements are performed using the same analytical parameters. In this case, data evaluation using TERMITE is much faster than with all other available software, and the concentrations of more than 100 single spot measurements can be calculated in less than a minute. CONCLUSIONS: TERMITE is an open-source software for the reduction of LA-ICPMS data, which is particularly useful for the fast, reproducible evaluation of large datasets of samples that are homogeneous with respect to their major element composition.
RATIONALE: High spatial resolution Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICPMS) determination of trace element concentrations is of great interest for geological and environmental studies. Data reduction is a very important aspect of LA-ICP-MS, and several commercial programs for handling LA-ICPMS trace element data are available. Each of these software packages has its specific advantages and disadvantages. METHODS: Here we present TERMITE, an R script for the reduction of LA-ICPMS data, which can reduce both spot and line scan measurements. Several parameters can be adjusted by the user, who does not necessarily need prior knowledge in R. Currently, ten reference materials with different matrices for calibration of LA-ICPMS data are implemented, and additional reference materials can be added by the user. TERMITE also provides an optional outlier test, and the results are provided graphically (as a pdf file) as well as numerically (as a csv file). RESULTS: As an example, we apply TERMITE to a speleothem sample and compare the results with those obtained using the commercial software GLITTER. The two programs give similar results. TERMITE is particularly useful for samples that are homogeneous with respect to their major element composition (in particular for the element used as an internal standard) and when many measurements are performed using the same analytical parameters. In this case, data evaluation using TERMITE is much faster than with all other available software, and the concentrations of more than 100 single spot measurements can be calculated in less than a minute. CONCLUSIONS: TERMITE is an open-source software for the reduction of LA-ICPMS data, which is particularly useful for the fast, reproducible evaluation of large datasets of samples that are homogeneous with respect to their major element composition.
Authors: Malte Willmes; Katherine M Ransom; Levi S Lewis; Christian T Denney; Justin J G Glessner; James A Hobbs Journal: PLoS One Date: 2018-09-27 Impact factor: 3.240
Authors: Markus Reuter; Philipp M Spreter; Thomas C Brachert; Regina Mertz-Kraus; Claudia Wrozyna Journal: Sci Rep Date: 2022-10-03 Impact factor: 4.996