Abstract View
Mechanisms of Nanoparticle Formation and Their Health Effects
ANGELA VIOLI, University of Michigan
Abstract Number: 493
Working Group: Invited by Conference Chair
Abstract
An important step in predicting the growth of soot nanoparticles is understanding how gas phase variations affect the formation of their aromatic precursors. Once formed, these aromatic structures begin to assemble into nanoparticles and, regardless of the clustering process, the molecular properties of the aromatic precursors play an important role.
This presentation is divided in two parts: first we report on a detailed study of compounds formed in flames discussing formation mechanisms and their relative importance according to the environment. Using a unique computational model based on Monte Carlo techniques (named SNapS2), we are able to predict the structure and chemical evolution of various polycyclic aromatic compounds (PACs) and nanoparticle. PACs predicted in various conditions show diverse chemical properties, including aliphatic chains, five-membered, and heteroaromatic rings. Using graph theory and network analysis, we investigated the complex reaction network generated by SNapS2 and determined that the growth pathways of many PACs center around a few stable structures that also promote oxygen addition reactions due to their morphology and long lifetimes.
In the second part of the talk, we will address the health effects of PACs and nanoparticles. Indeed, one of the main issues related to the health effects of pollutants is their ability to cross biological cells, i.e. the transport through a physiological cellular membrane. The behavior of nanoparticles in a biological matrix is a very complex problem that depends not only on the type of nanoparticle but also on its size, shape, phase, surface charge, chemical composition, and agglomeration state. We present a theoretical model that predicts the average time of entry of nanoparticles in lipid membranes, using a combination of molecular dynamics simulations and statistical approaches. The model identifies four parameters that separate the contributions of molecules characteristics (i.e., size, shape, solubility) from the membrane properties (density distribution). The robustness of the model is supported by experimental data carried out in lipid vesicles encapsulating graphene quantum dots as nanoparticles. The new model, named LDA, is applied to the permeation of PAHs through various cellular membranes. Given the high level of interest across multiple areas of study in modulating intracellular targets, and the need to understand and improve the effects of nanoparticles and to assess their effect on human health (i.e., cytotoxicity, bioavailability), this work contributes to the understanding and prediction of interactions of nanoparticles and environmental media that affect fate, transport and risk.