Issue 40, 2023

First GC/MS identification of aqueous ammonia: utilization of ethenesulfonyl fluoride as a selective and rapid derivatization reagent of ammonia in aqueous media

Abstract

Identification as well as quantification of ammonia are required in some analytical fields including forensic science. For this purpose, gas chromatography/mass spectrometry (GC/MS) analysis is one of the most suitable techniques. Although ammonia needs to be derivatized for GC/MS analysis, conventional derivatization reagents require anhydrous conditions because they are highly reactive with water. Here, we investigated ethenesulfonyl fluoride (ESF) as a selective reagent for ammonia derivatization in aqueous media to develop a rapid identification method for ammonia in aqueous media. The Michael addition reaction of ammonia with ESF rapidly produced a tri-ESF derivative suitable for GC/MS analysis. We optimized the derivatization reaction conditions and extraction solvent. With the optimized protocol, the detection limit for aqueous ammonia was 0.05 μg mL−1. The calibration curve showed good linearity (R2 = 0.9998) in the range of 0.10–100.0 μg mL−1, and the accuracy (% bias) and the precision (% relative standard deviation) for concentrations of 0.10, 0.25, 10.0, and 75.0 μg mL−1 were within ± 10% (intra- and inter-day). The proposed ESF-based method could quantify ammonia in samples containing interfering nucleophilic substances. This method was successfully applied to ammonia-containing commercial products.

Graphical abstract: First GC/MS identification of aqueous ammonia: utilization of ethenesulfonyl fluoride as a selective and rapid derivatization reagent of ammonia in aqueous media

Supplementary files

Article information

Article type
Communication
Submitted
26 Jun 2023
Accepted
21 Sep 2023
First published
09 Oct 2023

Anal. Methods, 2023,15, 5294-5299

First GC/MS identification of aqueous ammonia: utilization of ethenesulfonyl fluoride as a selective and rapid derivatization reagent of ammonia in aqueous media

R. Shiraki, K. Wakigawa, S. Ogawa, A. Gohda, T. Mori and Y. Katayama, Anal. Methods, 2023, 15, 5294 DOI: 10.1039/D3AY01071F

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