Pub Date : 2025-09-18DOI: 10.1021/acs.estlett.5c00699.s001
Kai-Hung Huang (5334098), Namita Narendra (22272754), Kaili Yap (16993749), Nicolás M. Morato (22272757), Kitmin Chen (13725014), Yunfei Feng (10268318), R. Graham Cooks (1278798), Tillmann Kubis (8443497), Christina R. Ferreira (461379)
Per- and polyfluoroalkyl substances (PFAS) are a global challenge due to their exceptional thermal and chemical durability which leads to environmental persistence, bioaccumulation, and toxicity. Tackling this challenge is a complex endeavor as the ever-expanding number of emerging PFAS hinders their monitoring while current countermeasures remain limited. Thus, there is a need for rapid strategies that can transform PFAS into safer, degradable analogs or expand libraries for untargeted monitoring. Here, we describe the implementation of a high-throughput (1 Hz) desorption electrospray ionization mass spectrometry (HT-DESI-MS) platform for the chemical transformation of perfluorocarboxylic acids (PFCAs) via a data-driven workflow that led to 915 new PFCA analogs (89% success rate) and revealed reactivity trends. Tandem mass spectrometry (MS/MS) enabled online structural confirmation and diagnostic fragment identification, supporting standard-free LC-MS/MS analysis. Further integration with ion mobility spectrometry (IMS) provided drift time measurements correlating with molecular size and shape, adding a new dimension that can improve feature annotation in untargeted PFAS analysis. Complementary quantum mechanical calculations of dipole moment and HOMO–LUMO gap predicted polarity and electronic reactivity, guiding analog selection. Collectively, this workflow combines rapid synthesis, structural annotation, and multidimensional profiling, with potential to discover safer PFAS and enhance environmental monitoring.
{"title":"High-ThroughputSmall-Scale Platform for Synthesis,Characterization, and Modeling of Per- and Polyfluoroalkyl SubstancesAnalogs","authors":"Kai-Hung Huang (5334098), Namita Narendra (22272754), Kaili Yap (16993749), Nicolás M. Morato (22272757), Kitmin Chen (13725014), Yunfei Feng (10268318), R. Graham Cooks (1278798), Tillmann Kubis (8443497), Christina R. Ferreira (461379)","doi":"10.1021/acs.estlett.5c00699.s001","DOIUrl":"https://doi.org/10.1021/acs.estlett.5c00699.s001","url":null,"abstract":"Per- and polyfluoroalkyl substances (PFAS) are a global challenge due to their exceptional thermal and chemical durability which leads to environmental persistence, bioaccumulation, and toxicity. Tackling this challenge is a complex endeavor as the ever-expanding number of emerging PFAS hinders their monitoring while current countermeasures remain limited. Thus, there is a need for rapid strategies that can transform PFAS into safer, degradable analogs or expand libraries for untargeted monitoring. Here, we describe the implementation of a high-throughput (1 Hz) desorption electrospray ionization mass spectrometry (HT-DESI-MS) platform for the chemical transformation of perfluorocarboxylic acids (PFCAs) via a data-driven workflow that led to 915 new PFCA analogs (89% success rate) and revealed reactivity trends. Tandem mass spectrometry (MS/MS) enabled online structural confirmation and diagnostic fragment identification, supporting standard-free LC-MS/MS analysis. Further integration with ion mobility spectrometry (IMS) provided drift time measurements correlating with molecular size and shape, adding a new dimension that can improve feature annotation in untargeted PFAS analysis. Complementary quantum mechanical calculations of dipole moment and HOMO–LUMO gap predicted polarity and electronic reactivity, guiding analog selection. Collectively, this workflow combines rapid synthesis, structural annotation, and multidimensional profiling, with potential to discover safer PFAS and enhance environmental monitoring.","PeriodicalId":522341,"journal":{"name":"Figshare","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147895594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：