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PySILLS, a newly developed Python-based open source tool for a modern data reduction of LA-ICP-MS experiments

Laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS) is a sensitive, efficient and cost-effective method for analyzing the major, minor and trace element compositions of minerals as well as of fluid and melt inclusions. Due to the high spatial resolution, low detection limits and multi-element capabilities of the LA-ICP-MS technique, it is ideally suited for rapid in situ chemical analysis of geological materials with minimal sample preparation requirements. Because of the wide use of LA-ICP-MS in geosciences, materials sciences and life sciences, there is a considerable need for modern data reduction tools that combine an intuitive and efficient workflow, a comprehensive statistical analysis and the strengths of open source software development. The new LA-ICP-MS data analysis tool PySILLS is completely written in Python, a popular, high-level and general-purpose programming language. A key design concept of PySILLS is to keep the code simple, in order to make the development of plugins, for example novel quantification methods for the analysis of fluid or melt inclusions, as user-friendly as possible. Another key concept is to keep the workflow and the possible settings efficient and flexible. PySILLS was initially developed in the context of a MSc thesis project and has been brought to the level that the widely used SILLS tool offers, and features already a number of important improvements. Further extensions, for example the implementation of user-developed plugins such as a fluid inclusion quantification method that combines LA-ICP-MS and microthermometric data with thermoynamic modeling, can be exptected in the near future.


Maximilian Beeskow1, Thomas Wagner1, Fußwinkel Tobias1
1RWTH Aachen University, Germany
GeoMinKöln 2022