Thirty two commercially available standards were used to determine chromatographic retention indices (RIs) for three different stationary phases. The selected compounds were nitrogen-containing heterocycles and amides, which are unsymmetrical dimethylhydrazine (UDMH) transformation products or its assumed transformation products. UDMH is a highly toxic compound widely used in the space industry, that forms a number of different compounds in the environment. Well-known transformation products may exceed UDMH itself in their toxicity, but most of the products are poorly investigated, while posing a huge environmental threat. Experimental RIs for the stationary phases, RIs from the NIST database, and predicted RIs are presented in this paper. It is shown that there are virtually no RIs for UDMH transformation products in the NIST database. In addition, even among those compounds for which RIs were known, inconsistencies were identified. Adding RIs to the database and eliminating erroneous data would allow for more reliable identification when standards are not available. The discrepancies identified between experimental RI values and predicted values will allow for adjustments to the machine learning models that are used for prediction. Previously proposed compounds as possible transformation products without the use of standards and NMR method were confirmed.

中文翻译：

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使用气相色谱保留指数和机器学习验证已知和假设的 UDMH 转化产物的识别可靠性

使用 32 个市售标准品来测定三种不同固定相的色谱保留指数 (RI)。所选化合物为含氮杂环和酰胺，它们是不对称二甲基肼（UDMH）转化产物或其假定转化产物。 UDMH 是一种广泛用于航天工业的剧毒化合物，会在环境中形成多种不同的化合物。众所周知的转化产品的毒性可能超过偏二甲肼本身，但大多数产品的研究很少，同时对环境造成巨大威胁。本文介绍了固定相的实验 RI、NIST 数据库中的 RI 以及预测的 RI。结果表明，NIST 数据库中几乎没有 UDMH 转化产品的 RI。此外，即使在 RI 已知的化合物中，也发现了不一致的情况。将 RI 添加到数据库并消除错误数据将有助于在标准不可用时进行更可靠的识别。实验 RI 值和预测值之间发现的差异将允许调整用于预测的机器学习模型。先前提出的化合物作为可能的转化产物，无需使用标准品和NMR方法就得到了证实。