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Key Features for Single Particle Analysis Released in TOFpilot 2.11

single particle tofpilot feature

TOFpilot 2.11 provides new key features for single particle analysis. In addition to improvements in the single particle workflow, this release implements a new algorithm for reliable particle detection and thresholding. The algorithm development was carried out in collaboration with Alex Gundlach-Graham, Assistant Professor of Chemistry at Iowa State University. Improvements and bug fixes for laser ablation are also included in this release. Lastly, to facilitate routine analysis, an automatic shutdown procedure has been included to allow switch off in the middle of the night after completion of a workflow.  

TOFpilot is the control software for all three models of the icpTOF (S2, R, 2R). The icpTOF is based on the iCAP RQ (Thermo Scientific), and TOFpilot has full control over both the iCAP front-end and the TOF mass analyzer. TOFpilot greatly simplifies the workflow for the user by integrating control of the icpTOF with various sample introduction systems, such as different laser ablation systems (e.g., Teledyne CETAC and Elemental Scientific Lasers) and autosamplers (e.g., Teledyne, ESI). TOFpilot operates on a module-basis which allows the user to set up different workflow sequences, including plasma startup, instrument tuning (manual or automated), liquid solution analysis, single particle and single cell analysis, and laser ablation analyses (including imaging with real-time display.

Key New Features

  • Compound-Poisson based algorithm for reliable particle detection and thresholding 
  • Bug fixes and improvements for laser ablation 
  • Automatic shutdown procedure 

Compound-Poisson Based Algorithm for Reliable and Accurate Particle Detection and Thresholding 

Nanoparticles are challenging to detect – they are small (only a few thousands of atoms) and consequently may only produce low intensity signals. Because of this, a key step in nanoparticle characterization is their accurate recognition in the measured data. In order to accurately count particles in a measurement, the background must be determined as well as identifying an acceptable false-positive rate (α).  

Low-count icpTOF signals are best described by a Compound-Poisson distribution, in which the detector’s response function (SIS distribution of MCPs) is compounded with Poisson-distributed arrival of the ions at the detector.  Through modeling of this Compound-Poisson noise, improved NP-detection thresholds—with user-defined false positive rates—are achieved.  This allows for more reliable particle event recognition and thus more accurate determination of particle number concentrations. 

Please refer to the following publications for a complete description of the Compound-Poisson based algorithm and applications thereof:  

  • A. Gundlach-Graham, L. Hendriks, K. Mehrabi and D. Gunther, “Monte Carlo Simulation of Low-Count Signals in Time-of-Flight Mass Spectrometry and Its Application to Single-Particle Detection”, Analytical Chemistry2018, 90, 11847-11855. 
  • L. Hendriks, A Gundlach-Graham and D. Gunther, “Performance of sp-ICP-TOFMS with signal distributions fitted to a compound Poisson model”, Journal of Analytical Atomic. Spectrometry2019, 34, 1900-1909 
  • Mehrabi K. Gunther D. Gundlach-Graham A. “Single-particle ICP-TOFMS with online microdroplet calibration for the simultaneous quantification of diverse nanoparticles in complex matrices”,  Environ. Sci.: Nano., 2019, 6, 3349–3358 
  • Gundlach-Graham A and K. Mehrabi, “Monodisperse microdroplets: a tool that advances single-particle ICP-MS measurements”, Journal of Analytical Atomic. Spectrometry2020, 35, 1727-1739. 
  • Mehrabi, K.; Kaegi, R.; Günther, D.; Gundlach-Graham, A.,”Emerging investigator series: automated single-nanoparticle quantification and classification: a holistic study of particles into and out of wastewater treatment plants in Switzerland”. Environ. Sci.: Nano 2021, 8 (5), 1211-1225 

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