Magnetic Graphene Dispersive Solid-Phase Extraction for the Determination of Phthalic Acid Esters in Flavoring Essences by Gas Chromatography Tandem Mass Spectrometry. (29th July 2020)

• Record Type: Journal Article
• Authors: Zhu, Jing; Lu, Binglin; Liu, Shanshan; Xu, Aifei; Tang, Guifang; Chen, Zhiyan; Pan, Yuling; Tang, Gangling; Yang, Fei; Zhou, Yun
• Is Part Of: Journal of chromatographic science. Volume 58:Number 8(2020)
• Page Start: 770
• Page End: 778
• Publication Date: 2020-07-29
• Subjects: Chromatographic analysis -- Periodicals; 543.8
• DOI: 10.1093/chromsci/bmaa032
• Languages: English
• ISSNs: 0021-9665

Abstract

Abstract: In the present study, a sensitive, efficient and repeatable method for the simultaneous extraction and determination of 13 types of phthalic acid esters (PAEs) in flavoring essence samples using magnetic graphene solid-phase extraction coupled with gas chromatography tandem mass spectrometry was developed. Due to the unique structure of magnetic graphene, it has several advantages, such as large surface area and fast separation ability. This unique structure not only provided strong magnetic responsiveness for the separation but also prevented the self-aggregation of graphene. The large delocalized p-electron system of graphene can form strong π-stacking interactions with the benzene ring. Thus, graphene may be also a good candidate adsorbent for the adsorption of benzenoid-form compounds. Several magnetic soild-phase extraction parameters, such as elution solvents, amounts of sorbents, enrichment time and desorption time were optimized. The optimized procedures for this method were performed by ultrasonication using ethyl acetate as elution solvent for 5 min. Under the optimal conditions, the developed method provided spiked recoveries of 75.0–105.3% with relative standard deviations of ~5.6% and limits of detection were 0.011–0.091 mg/kg. Good linear relationships were observed with the coefficient of determination (R2) > 0.993 for all the analytes. Finally, the validated method was successfully applied to the analysis of PAEs in real samples.