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Skip the beat: minimizing aliasing error in LA-ICP-MS measurements.
Bodo Hattendorf1, Urs Hartfelder2, Detlef Günther3
1Laboratory of Inorganic Chemistry, ETH Zurich, Vladimir-Prelog-Weg 1, 8093, Zurich, Switzerland. bodo@inorg.chem.ethz.ch.
Signal beat in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) can cause biased results. Averaging signal intensities using the least common multiple (LCM) method effectively minimizes this bias, improving quantitative accuracy in LA-ICP-MS experiments.
Area of Science:
- Analytical Chemistry
- Geochemistry
- Spectroscopy
Background:
- Pulsed laser ablation sampling coupled with sequential isotope detection can introduce signal beat.
- This signal beat can lead to significant biases in intensity ratios and concentrations, especially when aerosol transport times approach mass scan durations.
Purpose of the Study:
- To develop and validate a method to eliminate systematic bias caused by signal beat in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS).
- To improve the accuracy of quantitative LA-ICP-MS measurements.
Main Methods:
- Averaging signal intensities based on the least common multiple (LCM) of scan duration and laser pulse period.
- Experimental investigation using an ablation cell with specific washout times and quadrupole-based ICP-MS acquisition.
- Comparison and extension of experimental data with numerical simulations.
Main Results:
- The systematic bias due to signal beat can exceed the inherent noise in LA-ICP-MS experiments.
- The LCM averaging method effectively minimizes this bias.
- Simulation revealed that the effectiveness of LCM averaging depends on the integer multiple relationship between laser pulses and isotopes acquired per scan.
Conclusions:
- LCM averaging is a viable method to prevent systematic bias in LA-ICP-MS measurements.
- The method enhances the accuracy of quantitative laser ablation experiments.
- Considerations for element imaging applications include potential increases in pixel size due to averaging parameters.
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