Issue 4, 2022

Ilaps – python software for data reduction and imaging with LA-ICP-MS

Abstract

In the past couple of years, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been widely used for trace element analysis in solid samples and the study of their distribution. The data acquired by this technique are exceedingly complex and call for a wealth of processing steps, such as data segmentation, background correction, calibration and normalisation. Imaging of the distribution additionally requires a reconstruction of the data into a two-dimensional matrix. In this work, we present a new standalone software written in python – Ilaps, that allows easy and straightforward processing of the LA-ICP-MS data for bulk analysis and imaging. Ilaps is built using a free, open-source python package imgMS, which simplifies the customisation of the used functions. The combination of imgMS as a python package with a standalone graphical software makes it possible to be used by researchers with or without programming knowledge at the same level. However, at the same time, it encourages open collaboration for the software to evolve. Ilaps does not require any data preparation, and can process a bulk analysis or convert the data into an image in a matter of minutes. The software offers an automatic selection of the signals that are representative of the composition of the sample, but at the same time allows the user to exclude contaminants manually. We discuss the key advantages of Ilaps and show its potential in two separate cases, one focused on bulk analysis of archaeological glass samples and the other on imaging of a mouse brain.

Graphical abstract: Ilaps – python software for data reduction and imaging with LA-ICP-MS

Supplementary files

Article information

Article type
Technical Note
Submitted
02 Nov. 2021
Accepted
10 Marts 2022
First published
10 Marts 2022

J. Anal. At. Spectrom., 2022,37, 733-740

Ilaps – python software for data reduction and imaging with LA-ICP-MS

V. Faltusová, T. Vaculovič, M. Holá and V. Kanický, J. Anal. At. Spectrom., 2022, 37, 733 DOI: 10.1039/D1JA00383F

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements