Thiamethoxam (TMX) is a widely used neonicotinoid insecticide in pest control. Identification of structurally related impurities is very important during certified reference material development and pesticide registration, thus it needs to be carefully characterized. In this study, a combined strategy with liquid chromatography-high resolution mass spectrometry and computer assisted elucidation (SIRIUS) has been developed for the impurity elucidation in TMX material. MS and MS/MS spectra were used to score the impurity candidates by isotope score and fragment tree in SIRIUS. TMX, the main component, worked as an anchor for formula identification and structure elucidation of impurity. With this strategy, four impurities were identified, including two byproducts (TMX-OCH3 and TMX-Cl) and two metabolites (clothianidin and TMX-urea). Their fragmentation pathways were concluded, and mechanism of impurity formation was also proposed. This result showed successful application of combining human intelligence with machine learning in impurity identification from chemicals.
Keywords: High resolution mass spectrometry; Impurity identification; SIRIUS; Thiamethoxam.
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