Measurement of TiO2 Nanoscale Ingredients in Sunscreens by Multidetector AF4, TEM, and spICP-MS Supported by Computational Modeling
Source abstract
Abstract
There is a growing need to disclose the presence of nanostructures on the labeling of commercial products in South Africa. This work deals with complementary analytical techniques for the separation, quantification, and characterization of titanium dioxide nanoparticles (TiO2NPs) capped with poly(ethylene glycol) (PEG) for applications in cosmetic sunscreens. Asymmetrical flow field-flow fractionation (AF4) coupled online to multiangle light-scattering (MALS) and dynamic light-scattering (DLS) detectors has been implemented to optimize a method to evaluate the radius of gyration (rg-MALS), hydrodynamic radius (rh-DLS), and shape factor (rg/rh) of the PEGylated TiO2NPs. The size distribution obtained using single-particle inductively coupled plasma mass spectrometry supported with imagery from transmission electron microscopy provided further information on the PEG-coated TiO2NPs in comparison to the uncapped TiO2NPs. Furthermore, computational adsorption studies coupled with Monte Carlo simulations provided structural insights into the spatial distribution of the curved TiO2NP interactions with PEG/water substrates at an atomistic and molecular level. Finally, the developed multidetector AF4 method was applied to two commercial SPF 50 sunscreens, exhibiting promising separation and detection efficiency. These findings may contribute to regulatory measures in line with the South African National Nanotechnology Strategy for the cosmetics industry.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Field-Flow Fractionation Techniques · Nanoparticles: synthesis and applications · TiO2 Photocatalysis and Solar Cells
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry, Durban University of Technology, P. O. Box 1334, Durban 4000, South Africa
Postnova Analytics GmbH, Rankine-Strasse 1, 86899 Landsberg, Germany
Funding
Durban University of Technology · National Research Foundation
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