Influence of organic molecules on the aggregation of TiO2 nanoparticles in acidic conditions

• DOI: 10.1007/s11051-017-3807-9
• Publication Date: 2017-04-05T07:24:26Z
• Authors: Karin Danielsson; Julián A. Gallego...; Martin Hassellov; Stefan Gustafsson; Caroline M. Jonsson
• Keywords: 01 natural sciences; Research Paper; 0104 chemical sciences

Engineered nanoparticles released into the environment may interact with natural organic matter (NOM). Surface complexation affects the surface potential, which in turn may lead to aggregation of the particles. Aggregation of synthetic TiO2 (anatase) nanoparticles in aqueous suspension was investigated at pH 2.8 as a function of time in the presence of various organic molecules and Suwannee River fulvic acid (SRFA), using dynamic light scattering (DLS) and high-resolution transmission electron microscopy (TEM). Results showed that the average hydrodynamic diameter and ζ-potential were dependent on both concentration and molecular structure of the organic molecule. Results were also compared with those of quantitative batch adsorption experiments. Further, a time study of the aggregation of TiO2 nanoparticles in the presence of 2,3-dihydroxybenzoic acid (2,3-DHBA) and SRFA, respectively, was performed in order to observe changes in ζ-potential and particle size over a time period of 9 months. In the 2,3-DHBA-TiO2 system, ζ-potentials decreased with time resulting in charge neutralization and/or inversion depending on ligand concentration. Aggregate sizes increased initially to the micrometer size range, followed by disaggregation after several months. No or very little interaction between SRFA and TiO2 occurred at the lowest concentrations tested. However, at the higher concentrations of SRFA, there was an increase in both aggregate size and the amount of SRFA adsorbed to the TiO2 surface. This was in correlation with the ζ-potential that decreased with increased SRFA concentration, leading to destabilization of the system. These results stress the importance of performing studies over both short and long time periods to better understand and predict the long-term effects of nanoparticles in the environment.