Functional Assessment and Interpretation of Nanoparticle Surface Affinity for Fate Prediction

N. Geitner
Duke University,
United States

Keywords: nanoparticle, EHS, enviromental


As process-based environmental fate and transport models for engineered nanoparticles are developed, there is a need for relevant and reliable measures of nanoparticle behavior. However, we have seen that traditional measures such as partitioning coefficients are not adequate for nanoparticles. Instead, we must utilize analog kinetic measures. The affinity of nanoparticles for various surfaces (α) is one such measure. Previously commonly measured by flowing particles or other contaminants through a packed column, we have developed batch mixing methods of measuring α which are applicable to a wide variety of physical and environmental scenarios. We have applied these methods and framework of surface attachment to a wide variety of experimental and modeling efforts of nanoparticle fate. These include correlation of nanoparticle trophic transfer and changing α, and how surface chemistry of nanoparticles and their surrounding environment directly affect α. We have subsequently developed mathematical models for nanoparticle fate based on α, which may allow a simple, functional assay-based prediction of the fate and transport of emerging materials in complex environmental systems.