How Homologous Series and CCS Trends Reveal Unknown PFAS

In this interview filmed at ASMS in June 2026, Sheher Mohsin, Founder and CEO of Beyond Spectral Peaks and mass spectrometry consultant at Innovative Omics, and Jeremy Koemel, research faculty at Yale University and CEO of Innovative Omics, examine how ion mobility and collision cross section (CCS) measurements are transforming non-targeted per- and polyfluoroalkyl substances (PFAS) analysis.¹  

In this interview clip, they discuss:

• How useful have homologous series analysis and CCS trends been in supporting unknown identification — and can you walk us through a specific example where they made a real difference? 

The pair explain why CCS adds a critical layer of confidence when accurate mass, retention time, and fragmentation patterns alone cannot distinguish between the thousands of closely related features found in complex environmental matrices, because it introduces a physical measurement of a molecule's gas-phase size and shape. They discuss practical strategies for identifying low-intensity PFAS features, including leveraging MS1 isotopic patterns and Kendrick mass defect analysis when MS/MS data is limited by sensitivity constraints. Mohsin and Koemel also detail how homologous series analysis, supported by open-access tools like FluoroMatch IM 2.0, enables identification of unknown PFAS compounds without relying on spectral libraries, illustrated through a neutral loss pattern within a complex PFAS class that was ultimately added to their CCS Atlas. The conversation turns to the ongoing role of human expert reviewers in validating annotations, the promise of CCS as a fast, high-confidence single-measurement match, and the bottleneck posed by limited CCS reference libraries compared to established liquid chromatography–mass spectrometry (LC–MS databases). Finally, the pair discuss the emerging role of large language models in non-targeted analysis, sharing early results where general-purpose LLMs like ChatGPT accurately annotated complex PFAS compounds by synthesizing multiple layers of spectral evidence, sometimes surfacing patterns human reviewers had missed.

Reference

1. Mohsin, S.; Koelmel, J.; Chang, P.; et al. Leveraging Ion Mobility for PFAS Non-Targeted Analysis using FluoroMatch IM 2.0 and a Collision Cross Section (CCS) Atlas. Presented at ASMS 2026, in San Diego, California, USA. https://asms.org/docs/default-source/conference/74th-asms-final-program_as-of-may-8-2026.pdf?sfvrsn=1234fc3_0 (accessed 2026-07-06).