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Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation

Longerich, Henry P., Jackson, Simon E., Günther, Detlef·1996·J. Anal. At. Spectrom.

Abstract

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) produces complex, time-dependent signals. These require significantly different treatment both during data acquisition and reduction from the more steady-state signals produced by solution sample introduction. This paper discusses, in detail, data acquisition and reduction considerations in LA-ICP-MS analysis. Optimum data acquisition parameters are suggested. Equations are derived for the calculation of sample concentrations and LOD when time-resolved data acquisition is employed, sensitivity calibration is obtained from reference materials with known analyte concentrations and naturally occurring internal standards are used to correct for the multiplicative correction factors of drift, matrix effects and the amount of material ablated and transported to the ICP.

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Metadata

Authors
Longerich, H. P., Jackson, S. E., & Günther, D.
Venue
J. Anal. At. Spectrom.
Published
1996
Volume
11
Issue
9
Pages
899-904
ISSN
  • 0267-9477 (ISSN-L)
  • 1364-5544
OpenAlex
W2072062807
Cited by
1,651
References
0
FWCI
10.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. https://app.cochat.ai/papers/10.1039/ja9961100899
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Longerich, H. P., Jackson, S. E., & Günther, D. (1996). Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. J. Anal. At. Spectrom. https://doi.org/10.1039/ja9961100899

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.