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Author ORCID Identifier


Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Food Science

Year Degree Awarded


Month Degree Awarded


First Advisor

Lili He

Subject Categories

Analytical Chemistry | Food Chemistry | Other Food Science


Titanium dioxide (TiO2) and its nanoparticles (NPs) are widely used in various applications. Recently, the presence of TiO2 NPs in food and consumer products raised safety concerns to human health and the environment. The goal of this project is to explore the capability of Raman Spectroscopy in the analysis of TiO2-NPs and apply this technique for the analysis of TiO2-NPs in food and environmental samples. Two approaches, i.e. the ligand-based and the mapping-based, were evaluated. The ligand-based approach utilized the surface enhanced Raman scattering (SERS) property of the TiO2 NPs as a substrate to enhance the signal of a surface bound ligand, gallocyanin (GLN). This SERS property is only specific to NPs of TiO2, thus based on the R-value obtained from the ratio of TiO2 to GLN peak intensities, the R-value can be used to differentiate the NPs from their counterparts. Particles raning from 65-8 nm had a similar R-value ranged from 2.4 to 3.4 with no statistical difference, however, the R was found significantly higher for 93 nm and 173 nm samples. We then evaluated the second approach that is based on Raman mapping in combination with filtration to analyze TiO2-NPs. The results revealed linear correlation of both Raman intensity and map area occupied by the particles with particle size at different concentrations. We then evaluated both SERS and Raman mapping methods to determine the mean particle size and the amount of NPs from commercial E171 and food samples. Using R obtained from SERS analysis we were able to predict the mean particle size of chewing gum samples, however, due to the lack of R-values from standards between 65 to 200 nm, the SERS approach was not successfully able to estimate the mean particle size of the samples that contained a higher percentage of particles in that range. Consequently, using the correlation established between the map area and Raman intensity with the particle size, we were able to successfully estimate the particle size of TiO2 particles from both E171 and food samples. We then estimated the amount of NPs from the map area obtained by applying the Raman intensity threshold for the cut-off intensity of 93 nm particles.