| Download | - View author's version: Application of regression methods to solve general isotope dilution measurement equations (PDF, 4.9 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1088/1681-7575/ab6b3d |
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| Author | Search for: Meija, Juris1ORCID identifier: https://orcid.org/0000-0002-3349-5535; Search for: McRae, Garnet1; Search for: Pagliano, Enea1 |
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| Affiliation | - National Research Council of Canada. Metrology Research Centre
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| Format | Text, Article |
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| Subject | isotope dilution; least squares methods; graphical approach |
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| Abstract | Isotope dilution is among the most accurate quantitation approaches in chemical analysis. This calibration method is often employed using a plurality of mathematical formulations. While most analysts find the calibration curve approach most appealing, there is a lack of rigorous general procedures involving calibration curves in isotope dilution and analysts resort to empirical polynomial calibration functions. In this contribution we discuss the adoption of regression analysis, commonly known as least squares methods, to solve isotope dilution equations of varied complexity. This manuscript introduces general regression-based methods to isotope dilution applicable to all known variants of classical isotope dilution known to date, including the fusion of the isotope dilution and standard additions methods. |
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| Publication date | 2020-03-19 |
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| Publisher | IOP |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 416bf966-041f-4650-a1e8-e47b3c52bfd6 |
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| Record created | 2020-05-27 |
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| Record modified | 2020-05-27 |
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