Themed collection Fast Transient Signals – Getting the most out of Multidimensional Data

5 items
Open Access Accepted Manuscript - Paper

SPCal - An open source, easy-to-use processing platform for ICP-TOFMS based single event data

Thomas Edward Lockwood, Lukas Schlatt and David Clases
From the themed collection: Fast Transient Signals – Getting the most out of Multidimensional Data
The article was first published on 12 Nov 2024
J. Anal. At. Spectrom., 2024, Accepted Manuscript
https://doi.org/10.1039/D4JA00241E
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Open Access Paper

Machine learning analysis to classify nanoparticles from noisy spICP-TOFMS data

Raven L. Buckman and Alexander Gundlach-Graham

A two-stage semi-supervised machine learning approach was developed as a robust method to classify cerium-rich engineered, incidental, and natural nanoparticles measured by spICP-TOFMS.

Graphical abstract: Machine learning analysis to classify nanoparticles from noisy spICP-TOFMS data
From the themed collection: Fast Transient Signals – Getting the most out of Multidimensional Data
The article was first published on 16 Mai 2023
J. Anal. At. Spectrom., 2023,38, 1244-1252
https://doi.org/10.1039/D3JA00081H
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Paper

Nanoparticle identification using single particle ICP-ToF-MS acquisition coupled to cluster analysis. From engineered to natural nanoparticles

Mickaël Tharaud, Lukas Schlatt, Phil Shaw and Marc F. Benedetti

Characterization and identification of multielement nanoparticles thanks to the use of a spICP-ToF-MS coupled to hierarchical agglomerative clustering (HAC).

Graphical abstract: Nanoparticle identification using single particle ICP-ToF-MS acquisition coupled to cluster analysis. From engineered to natural nanoparticles
From the themed collection: Fast Transient Signals – Getting the most out of Multidimensional Data
The article was first published on 23 Aug 2022
J. Anal. At. Spectrom., 2022,37, 2042-2052
https://doi.org/10.1039/D2JA00116K
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Paper

Machine learning: our future spotlight into single-particle ICP-ToF-MS analysis

Timothy Ronald Holbrook, Doriane Gallot-Duval, Thorsten Reemtsma and Stephan Wagner

Using the multi-element capabilities of single-particle ICP-ToF-MS in combination with a laser ablation and machine learning algorithms, environmentally relevant road runoff samples were characterized.

Graphical abstract: Machine learning: our future spotlight into single-particle ICP-ToF-MS analysis
From the themed collection: Fast Transient Signals – Getting the most out of Multidimensional Data
The article was first published on 27 Okt 2021
J. Anal. At. Spectrom., 2021,36, 2684-2694
https://doi.org/10.1039/D1JA00213A
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Open Access Technical Note

Introducing “time-of-flight single particle investigator” (TOF-SPI): a tool for quantitative spICP-TOFMS data analysis

Alex Gundlach-Graham, Stasia Harycki, Sarah E. Szakas, Tristen L. Taylor, Hark Karkee, Raven L. Buckman, Shahnaz Mukta, Rui Hu and Woolin Lee

TOF-SPI is software for accurate, robust, and high-throughput analysis of single-particle ICP-TOFMS data.

Graphical abstract: Introducing “time-of-flight single particle investigator” (TOF-SPI): a tool for quantitative spICP-TOFMS data analysis
From the themed collection: Fast Transient Signals – Getting the most out of Multidimensional Data
The article was first published on 15 Jan 2024
J. Anal. At. Spectrom., 2024,39, 704-711
https://doi.org/10.1039/D3JA00421J
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5 items

About this collection

This collection consists of recently published and invited contributions that highlight strategies to maximise information extraction from multidimensional dataset generated from ICP-ToF-MS. The collection is Guest Edited by Björn Meermann (BAM, Germany), Lukas Schlatt (Nu Instruments Ltd, UK) and Lyndsey Hendriks (University of Vienna, Austria). The collection is now open to new submissions and new articles will be added as they are published.

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