PySILLS

PySILLS is a new, Python-based open source tool for a modern data reduction of LA-ICP-MS experiments. It is focused on the compositional analysis of major, minor, and trace elements of minerals (and glasses) as well as of fluid and melt inclusions. PySILLS, started as a M.Sc. thesis project, is developed by Maximilian Alexander Beeskow, who is part of the work group of Prof. Dr. Thomas Wagner and Dr. Tobias Fusswinkel at RWTH Aachen University. PySILLS was conceptionally inspired by the widely-used data reduction tool SILLS, developed and maintained by Prof. Dr. Christoph A. Heinrich and Dr. Marcel Guillong at ETH Zürich.

Top features¶

The following list shows some of the main features that differentiate PySILLS from alternative data reduction tools:

• works on all common computer systems that can run Python code,

• use of multiple standard reference materials in one project file,

• use of multiple internal standards in one project file,

• consideration of isotope-specific standard reference materials,

• assemblage definition,

• file-specific quick analysis,

• intuitive, fast and flexible workflow,

• use of PyPitzer, which enables thermodynamic modeling of fluid inclusion systems based on the Pitzer model,

• multiple check-up possibilities,

• export of processed LA-ICP-MS data (e.g., signal intensity ratios, analytical sensitivities, etc.) for external calculations,

• many quality-of-life features that support and accelerate a fast and reliable workflow.

Planned features¶

The following list shows some ideas, that we have in mind, for the future development of PySILLS.

• replacement of scattered signal intensity values by regression curves,

• Jupyter notebooks for a browser-based data reduction of LA-ICP-MS experiments,

• production of a YouTube video course.

Citing PySILLS¶

If you have used PySILLS for your work, please use the following citation:

• Maximilian Beeskow, Fusswinkel, T., & Wagner, T. (2026). PySILLS, Python-based and open source data reduction tool for the major, minor, and trace element analysis of minerals, fluid and melt inclusions, Zenodo, Maximilian Beeskow et al. (2026)

Disclaimer¶

Although PySILLS has been tested extensively and many issues encountered during development have been resolved, undiscovered bugs may still exist. Please report any suspected bugs using a structured and detailed bug report, including clear instructions on how the issue can be reproduced.

Based on our experience, a considerable number of reported issues were not caused by software errors but by workflows that deviated from the documented tutorials. PySILLS is a powerful but complex data reduction tool, and careful adherence to the provided tutorials is essential for correct usage. An intuitive workflow does not imply the absence of methodological constraints. Users are therefore strongly encouraged to read and follow the tutorials thoroughly before reporting potential issues.

Last updated: 22.01.2026