Determination and prediction of surface coating composition, surface properties, and colloidal stability of nanoparticles after in situ exposure to natural waters

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Nanoparticles (NPs) are emerging pollutants whose environmental fate differs fundamentally from molecular pollutants. The sorption of natural organic matter (NOM) onto the NP surface is a key factor for relevant processes which control the NP fate such as particle aggregation or sorption on natural surfaces. Currently available data are limited to simplified laboratory conditions and systems. To model the nanoparticle fate under natural conditions, it is therefore essential to explore the sorption mechanisms occurring under environmentally relevant conditions and complex NOM. We recently developed and validated a new method using a dialysis bag for in situ exposure of NPs to NOM and other dissolved components in surface waters. This enables us now to obtain particles with a surface coating as close as possible from what would occur under realistic conditions. In addition, advancements in surface characterization techniques allow to determine the composition and properties of complex natural NP coatings with an unprecedented level of detail.In this project, we aim at exploring and predicting the sorption mechanism under environmental conditions, its influence on the colloidal stability, and its relation to the initial NP coating. We will investigate the composition and structure of NOM-coating formed under field conditions for five different TiO2-nanoparticle types, including particles extracted from commercial products. These particles will be exposed to 60 different natural waters from a wide range of water quality parameters using the dialysis bag method. Once retrieved, we will analyze the particles using XPS, FT-IR, ToF-SIMS, and AFM for determining the surface composition, sorption mode, and coating thickness. For investigating the thickness of the coating using AFM, a dedicated sample preparation method, developed in our group will be further tested and validated. The molecular composition and stability of the NP coating will be investigated via direct measurement of molecules on the particle surface using a newly developed laser desorption ionization ultrahigh resolution FT-ICR MS method as well as sequential extraction followed by electrospray ionization FT-ICR MS. Finally, we will perform aggregation kinetics experiments of the exposed NPs in the corresponding natural water with and without natural colloids in order to account for both hetero- and homoaggregation.The obtained data will feed a multivariate machine learning model to explore to explore the relationship between initial coating, natural coating, water composition, and aggregation and to predict the characteristics of the NOM-coating and the aggregation rate from the incidental water parameters. The model results will provide invaluable inputs for the prediction of the environmental fate of nanoparticles in natural waters.