Enders Jeffrey R, O'Neill Grace M, Whitten Jerry L, Muddiman David C
Molecular Education Technology and Research Innovate Center (METRIC), North Carolina State University, 2620 Yarbrough Drive, Raleigh, NC, 27695, USA.
Department of Biological Sciences, North Carolina State University, Raleigh, NC, 27695, USA.
Anal Bioanal Chem. 2022 Jan;414(3):1227-1234. doi: 10.1007/s00216-021-03545-8. Epub 2021 Jul 21.
Per- and polyfluoroalkyl substances (PFAS) are used extensively in commercial products. Their unusual solubility properties make them an ideal class of compounds for various applications. However, these same properties have led to significant contamination and bioaccumulation given their persistence in the environment. Development of analytical techniques to detect and quantify these compounds must take into account the potential for these properties to perturb these measurements, specifically the potential to bias the electrospray ionization (ESI) process. Direct injection ESI analysis of 23 different PFAS species revealed that hydrophobicity and PFAS class can predict the ESI overall response factors. In this study, a method for predicting the behavior of individual PFAS compounds, including relative retention order in chromatography, is presented which is simply based on the number of fluorine atoms in the molecule as well as the class of the compound (e.g., perfluroalkylcarboxylic acids) vs. computational estimations (e.g., non-polar surface area and logP).
全氟和多氟烷基物质（PFAS）在商业产品中广泛使用。它们独特的溶解性使其成为各类应用的理想化合物。然而，鉴于其在环境中的持久性，这些相同的特性导致了严重的污染和生物累积。开发用于检测和定量这些化合物的分析技术必须考虑到这些特性对测量产生干扰的可能性，特别是对电喷雾电离（ESI）过程产生偏差的可能性。对23种不同PFAS物种的直接进样ESI分析表明，疏水性和PFAS类别可以预测ESI的整体响应因子。在本研究中，提出了一种预测单个PFAS化合物行为的方法，包括色谱中的相对保留顺序，该方法仅基于分子中的氟原子数量以及化合物的类别（例如全氟烷基羧酸）与计算估计值（例如非极性表面积和logP）。
