@article{fdi:010085373,
  title = {{F}aster and more precise isotopic water analysis of discrete samples by predicting the repetitions' asymptote instead of averaging last values},
  author = {{H}achgenei, {N}. and {V}aury, {V}. and {N}ord, {G}. and {S}padini, {L}. and {D}uwig, {C}{\'e}line},
  editor = {},
  language = {{ENG}},
  abstract = {{W}ater stable isotope analysis using {C}avity {R}ing-{D}own {S}pectroscopy ({CRDS}) has a strong between-sample memory effect. {T}he classic approach to correct this memory effect is to inject the sample at least 6 times and ignore the first two to three injections. {T}he average of the remaining injections is then used as measured value. {T}his is in many cases insufficient to completely compensate the memory effect. {W}e propose a simple approach to correct this memory effect by predicting the asymptote of consecutive repeated injections instead of averaging over them. {T}he asymptote is predicted by fitting a y = a/x + b relation to the sample repetitions and keeping b as measured value. {T}his allows to save analysis time by doing less injections while gaining precision. {W}e provide a {P}ython program applying this method and describe the steps necessary to implement this method in any other programming language. {W}e also show validation data comparing this method to the classical method of averaging over the last couple of injections. {T}he validation suggests a gain in time of a factor two while gaining in precision at the same time. {T}he method does not have any specific requirements for the order of analysis and can therefore also be applied to an existing set of analyzes in retrospect. {W}e fit a simple y = a/x + b relation to the sample repetitions of {P}icarro {L}2130-i isotopic water analyzer, in order to keep the asymptote (b) as measured value instead of using the average over the last couple of measurements. {T}his allows a higher precision in the measured value with less repetitions of the injection saving precious time during analysis. {W}e provide a sample code using {P}ython, but generally this method is easy to implement in any automated data treatment protocol.},
  keywords = {{P}icarro ; {W}ater stable isotopes ; {C}avity ring-down spectroscopy ({CRDS}) ; {C}alibration ; {H}ydrology ; {T}racer},
  booktitle = {},
  journal = {{M}ethods{X}},
  volume = {9},
  numero = {},
  pages = {101656 [11 ]},
  year = {2022},
  DOI = {10.1016/j.mex.2022.101656},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085373},
}