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双入口同位素质谱数据多点归一化的物理模型。

Physical model for multi-point normalization of dual-inlet isotope ratio mass spectrometry data.

机构信息

Chemical Sciences Division, Materials Measurement Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, MD, 20899, USA.

出版信息

Anal Bioanal Chem. 2022 Aug;414(19):5773-5779. doi: 10.1007/s00216-022-04137-w. Epub 2022 Jun 1.

DOI:10.1007/s00216-022-04137-w
PMID:35648173
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9795337/
Abstract

A simple model is presented for multi-point normalization of dual-inlet isotope ratio mass spectrometry (DI-IRMS) data. The model incorporates the scale contraction coefficient and the normalized working reference gas isotope delta value as its two physical parameters. The model allows the full use of isotope measurement data and outputs the normalized sample isotope delta value along with the mentioned parameters. The model reduces to the expected linear behavior on application to a natural range CO isotopic composition sample, under typically observed scale contraction levels. Next, DI-IRMS measurements of the NIST CO gas isotopic reference materials (RMs) 8562, 8563, and 8564 are used to construct a three-point linear calibration, spanning 40‰ for the [Formula: see text] and 20‰ for the [Formula: see text] raw data. Accuracy of the regression at the 0.009‰ level for [Formula: see text] and 0.01‰ for [Formula: see text] is observed for the three NIST RMs. The model derived scale contraction term is found to be a more accurate measure of cross-contamination in contrast to its end of day measurements by the enriched sample method. The constructed multi-point normalization model is next used to assign [Formula: see text] and [Formula: see text] isotope delta values on the Vienna PeeDee Belmnite-CO (VPDB-CO) scale, for pure CO gas samples in the natural isotopic range. A Monte Carlo analysis of the uncertainty, including estimates for the normalization step, is provided to assist future multi-point normalization with more than three reference points.

摘要

提出了一种用于双入口同位素比质谱(DI-IRMS)数据多点归一化的简单模型。该模型包含标度收缩系数和归一化工作参考气体同位素 δ 值作为其两个物理参数。该模型允许充分利用同位素测量数据,并输出归一化样品同位素 δ 值以及所述参数。该模型在应用于典型观察到的标度收缩水平下的天然范围 CO 同位素组成样品时,简化为预期的线性行为。接下来,使用 NIST CO 气体同位素标准物质(RMs)8562、8563 和 8564 的 DI-IRMS 测量值来构建三点线性校准,涵盖 [Formula: see text] 的 40‰和 [Formula: see text] 的 20‰原始数据。对于三个 NIST RM,观察到 [Formula: see text] 的回归精度为 0.009‰,[Formula: see text] 的回归精度为 0.01‰。与使用富集样品方法进行的一天结束时的测量相比,所得到的标度收缩项是交叉污染的更准确度量。接下来,使用构建的多点归一化模型将 [Formula: see text] 和 [Formula: see text] 同位素 δ 值分配到维也纳 PeeDee 贝蒙特石-CO(VPDB-CO)标度上,用于天然同位素范围内的纯 CO 气体样品。提供了对不确定性的蒙特卡罗分析,包括归一化步骤的估计,以协助未来具有三个以上参考点的多点归一化。