Title of article :
Chemometric tools to highlight non-intentionally added substances (NIAS) in polyethylene terephthalate (PET)
Author/Authors :
Kassouf، Wassim نويسنده Division of Urology & Robotics, McGill University Health Centre , , Amine and Maalouly، نويسنده , , Jacqueline and Chebib، نويسنده , , Hanna and Rutledge، نويسنده , , Douglas N. and Ducruet، نويسنده , , Violette، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2013
Abstract :
In an effort to identify non-intentionally added substances (NIAS), which is still a challenging task for analytical chemists, PET pellets, preforms and bottles were analyzed by an optimized headspace solid phase microextraction coupled to gas chromatography–mass spectrometry (HS–SPME/GC–MS). Fingerprints obtained by the proposed method were analyzed by three chemometric tools: Principal Components Analysis (PCA), Independent Components Analysis (ICA) and a multi-block method (Common Components and Specific Weights Analysis CCSWA) in order to extract pertinent variations in NIAS concentrations. Total ion current (TIC) chromatograms were used for PCA and ICA while extracted ion chromatograms (EIC) were used for CCSWA, each ion corresponding to a block. PCA managed to discriminate pellets and preforms from bottles due to several NIAS. Volatiles like 2-methyl-1,3-dioxolane, ethylene glycol, ethylbenzene and xylene were responsible for the discrimination of pellets and preforms. Less volatile compounds like linear aldehydes and phthalates were responsible for the discrimination of bottles. ICA showed more specific discriminations especially for bottles and pellets while CCSWA managed to discriminate preforms. The proposed methodology, combining HS–SPME/GC–MS with chemometric tools proved its efficiency in highlighting NIAS in PET samples in a relatively simple and fast approach compared to classical techniques.
Keywords :
PET , NIAS , Principal components analysis (PCA) , Independent Components Analysis (ICA) , HS–SPME/GC–MS , Common Components and Specific Weights Analysis (CCSWA)