Caution on the use of liquid nitrogen traps in stable hydrogen isotope-ratio mass spectrometry

Tyler B. Coplen; Haiping Qi

doi:10.1021/ac101570f

Home/Archive/USGS

USGS · 70042347

Caution on the use of liquid nitrogen traps in stable hydrogen isotope-ratio mass spectrometry

Tyler B. Coplen·Haiping Qi

View original source ↗Export metadata ↓

Abstract

An anomalous stable hydrogen isotopic fractionation of 4 ‰ in gaseous hydrogen has been correlated with the process of adding liquid nitrogen (LN 2 ) to top off the dewar of a stainless-steel water trap on a gaseous hydrogen-water platinum equilibration system. Although the cause of this isotopic fractionation is unknown, its effect can be mitigated by (1) increasing the capacity of any dewars so that they do not need to be filled during a daily analytic run, (2) interspersing isotopic reference waters among unknowns, and (3) applying a linear drift correction and linear normalization to isotopic results with a program such as Laboratory Information Management System (LIMS) for Light Stable Isotopes. With adoption of the above guidelines, measurement uncertainty can be substantially improved. For example, the long-term (months to years) δ 2 H reproducibility (1& sigma; standard deviation) of nine local isotopic reference waters analyzed daily improved substantially from about 1‰ to 0.58 ‰. This isotopically fractionating mechanism might affect other isotope-ratio mass spectrometers in which LN 2 is used as a moisture trap for gaseous hydrogen

Explore related subjects

Analytical Chemistry Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Tyler B. Coplen, Haiping Qi. 2010-08-18. Caution on the use of liquid nitrogen traps in stable hydrogen isotope-ratio mass spectrometry. https://doi.org/10.1021/ac101570f

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2021

Exploring the potential of electrospray-Orbitrap for stable isotope analysis using nitrate as a model

Widely used isotope ratio mass spectrometers have limited capabilities to measure metabolites, drugs, or small polyatomic ions without the loss of structural isotopic information. A new approach has recently been introduced that uses electrospray ionization Orbitrap to measure multidimensional isotope signatures of intact polar compounds. Using nitrate as a model compound, this study aims to establish performance metrics for comparisons with conventional IRMS at the natural abundance level. We present a framework on how to convert isotopolog intensities to δ values that are commonly used in the isotope geochemistry community. The quantification of seven nitrate isotopologs provides multiple pathways for obtaining the primary N and O δ values including non-mass-dependent O isotope variations, as well as opportunities to explore nonrandom isotopic distributions (i.e., clumping effects) within molecular nitrate. Using automation and the adaptation of measurement principles that are specific to isotope ratio analysis, nitrate δ15NAIR, δ18OVSMOW, and δ17OVSMOW were measured with a long-term precision of 0.4‰ or better for isotopic reference materials and purified nitrate from environmental samples. In addition, we demonstrate promising results for unpurified environmental samples in liquid form. With these new developments, this study connects the two largely disparate mass spectrometry fields of bioanalytical MS and isotope ratio MS, thus providing a route to measure new isotopic signatures in diverse organic and inorganic solutes.

Analytical Chemistry↗

USGS2016

New organic reference materials for hydrogen, carbon, and nitrogen stable isotope-ratio measurements: caffeines, n-alkanes, fatty acid methyl esters, glycines, L-valines, polyethylenes, and oils

An international project developed, quality-tested, and determined isotope−δ values of 19 new organic reference materials (RMs) for hydrogen, carbon, and nitrogen stable isotope-ratio measurements, in addition to analyzing pre-existing RMs NBS 22 (oil), IAEA-CH-7 (polyethylene foil), and IAEA-600 (caffeine). These new RMs enable users to normalize measurements of samples to isotope−δ scales. The RMs span a range of δ 2 H VSMOW-SLAP values from −210.8 to +397.0 mUr or ‰, for δ 13 C VPDB-LSVEC from −40.81 to +0.49 mUr and for δ 15 N Air from −5.21 to +61.53 mUr. Many of the new RMs are amenable to gas and liquid chromatography. The RMs include triads of isotopically contrasting caffeines, C 16 n -alkanes, n -C 20 -fatty acid methyl esters (FAMEs), glycines, and l -valines, together with polyethylene powder and string, one n -C 17 -FAME, a vacuum oil (NBS 22a) to replace NBS 22 oil, and a 2 H-enriched vacuum oil. A total of 11 laboratories from 7 countries used multiple analytical approaches and instrumentation for 2-point isotopic normalization against international primary measurement standards. The use of reference waters in silver tubes allowed direct normalization of δ 2 H values of organic materials against isotopic reference waters following the principle of identical treatment. Bayesian statistical analysis yielded the mean values reported here. New RMs are numbered from USGS61 through USGS78, in addition to NBS 22a. Because of exchangeable hydrogen, amino acid RMs currently are recommended only for carbon- and nitrogen-isotope measurements. Some amino acids contain 13 C and carbon-bound organic 2 H-enrichments at different molecular sites to provide RMs for potential site-specific isotopic analysis in future studies.

Analytical Chemistry↗

USGS2015

Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Analytical Chemistry↗