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Double Spike-Standard Addition Technique and Its Application in Measuring Isotopes.

Zhuo LuJian-Ming ZhuDecan TanThomas M JohnsonXiangli Wang
Published in: Analytical chemistry (2023)
Double spike (DS) method has been extensively used in determining stable isotope ratios of many elements. However, challenges remain in obtaining high-precision isotope data for ultra-trace elements owing to the limitations of instrumental signal-to-noise ratios and the systematics of precision of DS-based measurements. Here, the DS-standard addition (SA) (DSSA) technique is proposed to improve measurements of isotope compositions of ultra-trace elements in natural samples. According to the U-shaped relationship between DS measurement uncertainty and the spike/sample ratio, theoretical equations and an error propagation model (EPM) were constructed comprehensively. In our method, a spiked secondary standard solution with a high, precisely known spike/sample ratio is mixed with samples such that the mixtures have spike/sample ratios within the optimal range. The abundances of the samples relative to the added standards (sample fraction; f spl ) and the samples' isotope ratios can then be obtained exactly using a standard DS data reduction routine and the isotope binary mixing model. The accuracy and precision of the DSSA approach were verified by measurements of cadmium and molybdenum isotopes at as low as 5 ng levels. Compared with traditional DS measurements, the sample size for isotope analysis is reduced to 1/6-1/5 of the original with no loss of measurement precision. The optimal mixing range f spl = 0.15-0.5 is recommended. The DSSA method can be extended to isotope measurement of more than 33 elements where the DS method is applicable, especially for the ultra-trace elements such as platinum group and rare earth element isotopes.
Keyphrases
  • gas chromatography
  • high resolution
  • electronic health record
  • ionic liquid
  • big data
  • wastewater treatment
  • clinical practice
  • machine learning
  • tandem mass spectrometry
  • data analysis