Integrating Computational Chemistry and Ion Mobility Spectrometry into Non-Targeted Analysis Workflows for the Structural Elucidation of Emerging PFAS.

Per- and polyfluoroalkyl substances (PFAS) are an evolving class of synthetic chemicals that are pervasive in the environment due to widespread manufacturing and consumer use, such that PFAS contamination is of great concern. Although thousands of PFAS structures have been reported to date, this number increases daily with the identification of new PFAS from advances in non-targeted analysis (NTA) workflows. Ion mobility spectrometry in combination with mass spectrometry (IMS-MS) has recently been incorporated into PFAS NTA studies. Although MS provides essential precursor and fragmentation data, IMS offers complementary structural information via the measurement of the ion-neutral collision cross section (CCS) values. Experimental CCS values can then be compared with those calculated in silico from candidate 3D structures to meet confidence-level criteria in analyte assignments within NTA workflows. Although this approach has been applied since the late 1990s, PFAS often exhibited poorer agreement between the calculated and experimental CCS values. To address this limitation, we propose an optimized computational workflow to calculate Boltzmann-weighted CCS values for PFAS structures generated via quantum-chemical calculations. This workflow was assessed with experimental CCS values from 56 known PFAS structures across seven classes and resulted in an average percent error of 2.0%. Moreover, 11 new PFAS structures were proposed from NTA, with average errors of 1.3%. The combination of this new computational workflow and experimental IMS-MS measurements therefore establishes a workflow for structural elucidation of emerging PFAS.