[Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl

Shen-Zheng Sun1,2, Yao-Yao Li2, Yan Gao2

  • 1China Jiliang University,College of Materials and Chemistry,Hangzhou 310018,China.

Summary

This study developed a machine learning model to predict ionization efficiency for per- and polyfluoroalkyl substances (PFASs), enabling semi-quantitative analysis even without reference standards. The XGBoost model accurately estimated PFAS concentrations in various matrices, improving environmental risk assessment.