[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.
Se Pu = Chinese Journal of Chromatography
|April 13, 2026
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.
Area of Science:
- Environmental Chemistry
- Analytical Chemistry
- Toxicology
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