Separation and size characterization of highly polydisperse titanium dioxide nanoparticles (E171) in powdered beverages by using Asymmetric Flow Field-Flow Fractionation hyphenated with Multi-Angle Light Scattering and Inductively Coupled Plasma Mass Spectrometry.

2021 
ABSTRACT The application of titanium dioxide as E171 food additive has become an issue of debate due to numerous reports that titanium dioxide nanoparticles (TiO2 NPs) inside the products may pose risks to human health. However, there is still a lack of an official standardized methodology for the detection and size characterization of TiO2 particles in foods containing E171. In this study, a method was presented for size characterization of TiO2 particles with various independent verifications in coffee creamer and instant drink powders, using Asymmetric Flow Field-Flow Fractionation hyphenated with Multi-Angle Light Scattering and Inductively Coupled Plasma Mass Spectrometry (AF4-MALS-ICP-MS). TiO2 particles from these products were well extracted, followed by their optimized AF4 separation using anionic surfactant Sodium Dodecyl Sulfate (SDS) (0.05%, pH 9) and mixed surfactant NovaChem (0.2%), respectively. Size determination of TiO2 NPs was conducted based on AF4 calibration with polystyrene nanospheres and verification with TiO2 NPs standard suspension of 100 nm under two different AF4 conditions. The TiO2 particle sizes detected ranged from 24.4 – 544.3 nm for coffee creamer and 27.7 – 574.3 nm for instant drink powders, with the TiO2 NPs detection recoveries of 75% and 92%, respectively. Hydrodynamic diameters from AF4 size calibration could be independently validated by the gyration diameters from online MALS measurement. The established approach was demonstrated to be reliable and pragmatic for size profiling of highly polydisperse TiO2 particles and thus useful for monitoring E171 in similar foodstuffs.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    43
    References
    0
    Citations
    NaN
    KQI
    []