FT-ICR MS and NMR analysis of an isotopically labeled complex mixture of water disinfection byproducts formed by chloramine disinfection of model phenolic acids is described. A new molecular formula assignment procedure using the CoreMS Python library able to assign isotopically enriched formulas is proposed. Statistical analysis of the assigned formulas showed that the number of compounds, the diversity of the mixture, and the chlorine count increase during the chloramination reaction. The complex reaction mixture was investigated as a network of reactions using PageRank and Reverse PageRank algorithms. Independent of the MS signal intensities, the PageRank algorithm calculates the formulas with the highest probability at convergence of the reaction; these were chlorinated and nitrated derivatives of the starting materials. The Reverse PageRank revealed that the most probable chemical transformations in the complex mixture were chlorination and decarboxylation. These agree with the data obtained from INADEQUATE NMR spectra and literature data, indicating that this approach could be applied to gain insight into reactions pathways taking place in complex mixtures without any prior knowledge.

中文翻译：

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同位素标记的氯胺消毒副产物的 MS 和 NMR 分析：超链接和化学反应

描述了对模型酚酸进行氯胺消毒形成的水消毒副产物的同位素标记复杂混合物的 FT-ICR MS 和 NMR 分析。提出了一种使用 CoreMS Python 库的新分子式分配程序，能够分配同位素富集的分子式。对指定式的统计分析表明，在氯胺化反应过程中，化合物的数量、混合物的多样性和氯计数增加。使用 PageRank 和反向 PageRank 算法将复杂的反应混合物作为反应网络进行研究。 PageRank 算法独立于 MS 信号强度计算反应收敛时概率最高的公式；这些是起始材料的氯化和硝化衍生物。反向 PageRank 显示复杂混合物中最可能的化学转化是氯化和脱羧。这些与从不充分的核磁共振谱和文献数据获得的数据一致，表明这种方法可以用于在没有任何先验知识的情况下深入了解复杂混合物中发生的反应途径。