Resolving Relationships: Determining the Impacts of Environmental Matrices on the Ionization Efficiencies of Per and Polyfluoroalkyl Substances (PFAS) for the Development of a Semi-Quantitation Model

摘要： 一些分析方面的挑战阻碍了准确识别和量化 全氟烷基和多氟烷基物质（PFAS）。这些挑战包括缺乏 PFAS参比物质的浓度以及 电喷雾电离在这次实习中，我计划通过评估来应对这些挑战。 环境水样的主要基质特征及其与电离的关系 效率观察到的关系将用于开发初步的统计模型， 不含参比物质的PFAS半定量。通过与联合国 美国环境保护局，我将获得专业知识的导师，博士索布斯和博士。 McCord，在使用化学信息学解决分析问题。半定量模型 开发的作为一个结果的externship可以用来量化转化产物的PFAS 降解研究，如在母体NIH下设计的纳米生物修复技术 格兰特，R01ES032717。

Abstract: A number of analytical challenges hinder the accurate identification and quantification of per and polyfluoroalkyl substances (PFAS) in the environment. These challenges include the lack of reference materials for PFAS as well as the ionization variability due to matrix interferences in electrospray ionization. In this externship, I plan on addressing these challenges by evaluating major matrix characteristics of environmental water samples and their relationship to the ionization efficiency. The observed relationships will be used to develop a preliminary statistical model for the semi-quantitation of PFAS without reference materials. Through collaboration with the United States Environmental Protection Agency, I will gain expertise from mentors, Dr. Sobus and Dr. McCord, in using cheminformatics for solving analytical problems. The semi-quantitation model developed as a result of the externship can be used to quantify transformation products of PFAS degradation studies, such as the nano bio-remediation techniques designed under the parent NIH grant, R01ES032717.