TERMITE

TERMITE is an R (R Core Team, 2016) script for the reduction of LA-ICPMS data developed by Mischel et al. (2017). It can be used to reduce both spot and line scan measurements. The revised version TERMITE 2.0 (Rupprecht et al. 2019) provides a user interface (=UI) for much easier data handling compared to the previous version. 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.

Download TERMITE 2

Instructions

Installation of R

The open source software R is required to use TERMITE (we recommend using R-Studio to benefit from all interactive features of the UI. In case of any problems during the installation, please use the extensive documentation provided on the official website.

Application of TERMITE

  1. Download and unzip the TERMITE_2 files.
  2. The file “Introduction.pdf” provides detailed instructions how to run the script.
  3. The folder “TERMITE_2” contains the R code of TERMITE as well as all mandatory files required to run the script. It also contains example data sets of a line scan and spot measurements.

In case of any problems or questions, please contact us.


References

Mischel, S. A., Mertz-Kraus, R., Jochum, K. P., and Scholz, D., 2017. TERMITE - An R script for fast reduction of LA-ICPMS data and its application to trace element measurements. Rapid Communications in Mass Spectrometry 31, 1079-1087.

R Core Team, 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.

Rupprecht D, Mertz-Kraus R, Mischel S, Budsky A, Jochum KP & Scholz D (2019). TERMITE 2.0 – An R Script for Data Reduction of LA-ICP-MS Trace Element Measurements. Goldschmidt Abstracts, 2019