IsotopeTrack

A fast, free, and open-source desktop application for single-particle ICP-ToF-MS data analysis

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Downloads

Platform	Requirements	Download
macOS — Apple Silicon	macOS 11.0 (Big Sur) or later · 4 GB RAM (8 GB recommended)	IsotopeTrack_M.dmg
Windows	Windows 10 (64-bit) or later · 4 GB RAM (8 GB recommended)	IsotopeTrack_Setup_W.exe

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Key Features

• Multi-isotope single-particle detection across all measured elements simultaneously
• Three detection methods — Compound Poisson Log-Normal, CPLN lookup table, and Manual threshold
• Single-ion distribution (SIA) support — per-isotope σ fitted from real single-ion data
• Detector non-linearity filter — flat-topped saturated events excluded automatically
• Transport rate calibration — liquid weight, particle number, and particle mass methods
• Ionic calibration — automatic model selection (force through zero, linear, weighted linear)
• 16 result plot types on a drag-and-drop canvas — histograms, heatmaps, correlation, clustering, isotope ratios, ternary plots, network graphs, and more
• Supports Nu Vitesse folders (run.info), TOFWERK (.h5), and CSV formats
• Built-in materials database with mass fraction and density lookup
• Batch processing and CSV export
• Interactive in-app documentation — Help → User Guide (clickable screenshots of every window) and Help → Equations (every equation in LaTeX with worked examples and linked references)

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Recommended Workflow

1 · Load Sample Data

Click Import Data in the File menu or sidebar. Load all samples you plan to analyze in a single session to ensure consistent processing parameters.

2 · Choose Isotopes

Use the periodic table interface to select the isotopes of interest. Selected isotopes are carried automatically into all calibration panels.

3 · Ionic Calibration (Sensitivity)

Configure ionic calibration to convert raw counts to mass. Use -1 to exclude samples from specific calibration sets. IsotopeTrack evaluates three calibration models and automatically selects the best R². Manual override is available.

4 · Transport Rate Calibration

Calibrate aerosol transport efficiency using one of three methods: liquid weight, particle number, or particle mass. Average multiple measurements or select the most reliable single value.

5 · Mass Fraction & Density

For each sample, specify the mass fraction of the target element and the particle density from the built-in materials database.

6 · Set Detection Parameters

Configure detection method, alpha error rate, minimum peak points, watershed splitting and more for each element individually or via Batch Edit Parameters.

7 · Review Results in Canvas

Use the drag-and-drop results canvas to visualize and validate the analysis. Add plot nodes, adjust parameters, and explore multi-element relationships interactively.

8 · Export Data

Export a summary file (all samples and elements, statistics, concentrations, calibration info) and/or sample files (individual particle data per sample).

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User Guide

The full interactive user guide ships inside the application (Help → User Guide): every screenshot below is clickable there, with a detailed explanation of each region, guide-wide search, and region-by-region navigation. The sections below mirror it — click any section to expand it.

The Main Window

The main window is organised around four areas:

• Sidebar — calibration tools (Transport Rate, Sensitivity, Calibration Info) and sample management (Import Data, Add/Edit Elements, Results, Export, Sample List).
• Data Visualization — the raw signal of the selected isotope with zoom/pan, Time and m/z views, and the detection overlay after running Detect Peaks.
• Particle summary statistics — per-element particle counts, background, threshold, masses and concentrations.
• Particle peak detection parameters — one row per isotope: detection method, sigma, manual threshold, min points, alpha, iterative background, window size, integration method, watershed splitting and valley ratio. Below it: Batch Edit Parameters, Multi-Signal View, Detect Peaks, and the Non-linearity Filter.

Getting Started — welcome screen and data import

The welcome screen is the fastest way to begin: import data, load a saved .itproj project, or open a new window.

Import Data asks for the data source type — Nu folders (with run.info), delimited data files, or TOFWERK .h5:

For delimited files, the File Import Configuration dialog auto-detects isotope columns from their names (e.g. 107Ag); you control the time column, dwell time, and column mappings before importing:

Every user action, warning and error of the session is recorded in the Application Log (View → Show Application Log) — invaluable when reporting an issue:

Elements & Signals — periodic table, signal views, multi-element particles

Left-click an element to select its most abundant low-interference isotope; right-click to choose specific isotopes. Gray elements are not present in the dataset. Selections can be saved as named presets.

After Detect Peaks, the signal view overlays the background level, detection threshold, integrated points (orange) and peak maxima (green):

Zooming shows exactly how each transient was integrated:

Selecting a row in the results table highlights that particle in red:

Multi-Signal View plots several isotopes together — coincident peaks reveal multi-element particles, with a per-particle composition box:

Detection & SIA — batch parameters, single-ion distribution, non-linearity filter

Batch Edit Parameters applies identical settings to any set of elements and samples at once:

Upload a single-ion distribution (Nu Vitesse or TOFWERK) to fit the log-normal σ of the detector response — per mass or globally, with outlier flagging:

The detector non-linearity filter recognises saturated, flat-topped events and excludes their time window for all isotopes:

Calibration — sensitivity, transport rate, mass fraction, dilution, isobaric correction

Ionic Calibration Analysis (sidebar → Sensitivity): load standards, enter concentrations (-1 excludes a sample), and review the fits — slope, intercept, BEC, R², LOD and LOQ per isotope. Click a point to exclude it from the fit.

Transport Rate Calibration offers three methods — liquid weight, mass based, and number based:

Calibration Information summarises everything: which transport methods are in use, and the full per-isotope table with MDL/MQL (fg) and SDL/SQL (nm):

The Mass Fraction Calculator converts compound formulas (e.g. TiO2, Fe3O4) into mass fractions, molecular weights and densities from the built-in materials database:

Dilution factors (auto-detected from sample names) correct reported particles/mL, and Isobaric Correction subtracts isobaric interferences with editable per-analyte equations and a live before/after preview:

Results Canvas — node-based workflow builder

The results canvas is a Workflow Builder: drag data blocks (Single Sample, Multiple Sample, Batch Windows, Particle Filter) and visualization blocks (histogram, correlation, clustering, ternary, network, dashboard…) onto the canvas and connect them.

Sample nodes select and group samples (replicates can be combined automatically); the Particle Filter node keeps particles by elemental composition, element count, or per-element signal thresholds:

Every plot window has format settings, quantity configuration (counts, mass, moles, diameter, element groups summed per particle) and publication-quality figure export:

Export — sample files and summary file

Choose the data type (Element or Particle), the samples, and the outputs: sample files (particle-by-particle data) and/or a summary file (statistics, concentrations, calibration info for all samples). Dilution factors can be set right from the export dialog.

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Data Loading

Supported Formats

• Folder with run.info — Raw data from Nu Vitesse instruments
• TOFWERK .h5 — HDF5 acquisition files
• Data files — Delimited/spreadsheet time-series data (csv, txt, xls, xlsx, xlsm, xlsb)

CSV Format Requirements

• First column must be Time (units: ms, ns, or s)
• Each element column must include mass number + element symbol (e.g., 107Ag, 56Fe)
• Data must be provided in counts

Example Data

Example datasets for trying out IsotopeTrack (ionic calibration sets, transport efficiency standards, and multi-element nanoparticle samples) are available as zip files in the example-data release. Download, unzip, and import via File → Import Data.

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Detection Methods

Method	Description
Compound Poisson Log-Normal	Threshold from the compound Poisson–log-normal distribution of ToF single-ion signals
CPLN table	Same quantile drawn from a precomputed λ×σ lookup table for speed and accuracy
Manual	User-defined threshold value

Every equation behind these methods — with parameter definitions, worked numerical examples, and clickable literature references — is documented in the app under Help → Equations.

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Export Options

Summary File

Statistical summaries (mean, median, standard deviation), particle concentrations, size distributions, calibration information and method parameters for all samples and elements.

Sample Files

Individual particle data for each sample with complete particle-by-particle information, peak characteristics, and integration results.

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Acknowledgements

IsotopeTrack builds upon the work of the spICP-MS community. We are deeply grateful to all scientists whose published methodologies, open-source tools, and foundational research form the scientific backbone of this software.

SPCal

We particularly acknowledge SPCal, developed by T. E. Lockwood, R. Gonzalez de Vega, L. Schlatt, and D. Clases. Certain algorithmic approaches and detection methods implemented in IsotopeTrack were informed by their work.

Lockwood, T. E., Gonzalez de Vega, R., & Clases, D. (2021). An interactive Python-based data processing platform for single particle and single cell ICP-MS. Journal of Analytical Atomic Spectrometry, 36(11), 2536–2544. https://doi.org/10.1039/D1JA00297J

If you use IsotopeTrack in your research, please cite if not enjoy using it:

Ahabchane H, Goodman A, Hadioui M, Wilkinson K. IsotopeTrack: A fast and flexible application for the analysis of SP-ICP-TOF-MS datasets. Environmental Chemistry 2026; EN25111. https://doi.org/10.1071/EN25111

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The methodologies implemented in IsotopeTrack are based on the following studies.

Transport efficiency & quantification

Pace, H. E., Rogers, N. J., Jarolimek, C., Coleman, V. A., Higgins, C. P. & Ranville, J. F. (2011). Determining transport efficiency for the purpose of counting and sizing nanoparticles via single particle ICP-MS. Analytical Chemistry, 83(24), 9361–9369. https://doi.org/10.1021/ac201952t

Laborda, F., Bolea, E. & Jiménez-Lamana, J. (2014). Single particle inductively coupled plasma mass spectrometry: a powerful tool for nanoanalysis. Analytical Chemistry, 86(5), 2270–2278. https://doi.org/10.1021/ac402980q

Hadioui, M., Knapp, G., Azimzada, A., Jreije, I., Frechette-Viens, L. & Wilkinson, K. J. (2019). Lowering the size detection limits of Ag and TiO2 nanoparticles by single particle ICP-MS. Analytical Chemistry, 91(20), 13275–13284. https://doi.org/10.1021/acs.analchem.9b04007

Particle detection & thresholding

Gundlach-Graham, A., Hendriks, L., Mehrabi, K. & Günther, D. (2018). Monte Carlo simulation of low-count signals in time-of-flight mass spectrometry and its application to single-particle detection. Analytical Chemistry, 90(20), 11847–11855. https://doi.org/10.1021/acs.analchem.8b01551

Hendriks, L., Gundlach-Graham, A. & Günther, D. (2019). Performance of sp-ICP-TOFMS with signal distributions fitted to a compound Poisson model. Journal of Analytical Atomic Spectrometry, 34(9), 1900–1909. https://doi.org/10.1039/C9JA00186G

Gundlach-Graham, A. & Lancaster, R. (2023). Mass-dependent critical value expressions for particle finding in single-particle ICP-TOFMS. Analytical Chemistry, 95(13), 5618–5626. https://doi.org/10.1021/acs.analchem.2c05243

Lockwood, T. E., Schlatt, L. & Clases, D. (2025). SPCal — an open source, easy-to-use processing platform for ICP-TOFMS-based single event data. Journal of Analytical Atomic Spectrometry, 40(1), 130–136. https://doi.org/10.1039/D4JA00241E

Lockwood, T. E., Gonzalez de Vega, R., Schlatt, L. & Clases, D. (2025). Accurate thresholding using a compound-Poisson-lognormal lookup table and parameters recovered from standard single particle ICP-TOFMS data. Journal of Analytical Atomic Spectrometry, 40(10), 2633. https://doi.org/10.1039/D5JA00230C

Clustering of multi-element particle data

Tharaud, M., Schlatt, L., Shaw, P. & Benedetti, M. F. (2022). Nanoparticle identification using single particle ICP-ToF-MS acquisition coupled to cluster analysis. From engineered to natural nanoparticles. Journal of Analytical Atomic Spectrometry, 37, 2042–2052. https://doi.org/10.1039/D2JA00116K

Erfani, M., Baalousha, M. & Goharian, E. (2023). Unveiling elemental fingerprints: a comparative study of clustering methods for multi-element nanoparticle data. Science of The Total Environment. https://www.sciencedirect.com/science/article/abs/pii/S0048969723058035

Cuss, C. W., Benedetti, M. F., Costamanga, C., Mesnard, L. & Tharaud, M. (2025). Self-organizing maps for the detection and classification of natural nanoparticles, nanoparticle systems and engineered nanoparticles characterized using single particle ICP-time-of-flight-MS. Journal of Analytical Atomic Spectrometry, 40, 2471. https://doi.org/10.1039/D5JA00179J

The complete reference list — including the foundational statistics and every clustering algorithm and validity index — is available inside the application under Help → Equations, with clickable citations throughout.

Contributors

Thanks to everyone who has contributed to building IsotopeTrack:

Contributor	Name
	1nvertedProtagonist — Bogdan-Vladimir Damian
	TNTY100 — Yohan Thibault
	github-actions[bot] — automation/CI bot
	Houssame-EA — Houssame-Eddine Ahabchane

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License

IsotopeTrack is free and open-source software released under the GNU General Public License v3.0.