Multi-Scale Modelling of Aggregation of TiO₂ Nanoparticle Suspensions in Water

Area of Science:

• Nanomaterial Science
• Computational Chemistry
• Toxicology

Background:

• Titanium dioxide nanoparticles (TiO2) raise toxicity concerns, leading to regulatory actions like the EU ban on their use in food.
• Predicting nanomaterial toxicity often requires extensive in vivo studies, which are time-consuming and ethically challenging.

Purpose of the Study:

• To establish a link between the atomic structure of nanomaterials and their potential toxicity without large-scale biological experiments.
• To investigate the aggregation behavior of titanium dioxide nanoparticles using a novel multi-scale computational approach.

Main Methods:

• Utilized a multi-scale simulation technique combining ab initio Density Functional Theory (DFT) for electronic structure, classical Molecular Dynamics (MD) for Potential of Mean Force calculations, and Brownian Dynamics (BD) for large-scale aggregation studies.
• Developed a coarsening strategy where each nanoparticle is represented as a spherical bead in BD simulations to efficiently model the aggregation of thousands of nanoparticles.

Main Results:

• Identified three new molecular descriptors: aggregation free energy and two parameters correcting deviations from Smoluchowski aggregation kinetics.
• Successfully simulated the aggregation of a few thousand titanium dioxide nanoparticles.

Conclusions:

• The developed multi-scale method provides a pathway to predict nanomaterial toxicity based on physicochemical properties.
• The identified molecular descriptors can be integrated into Quantitative Structure-Activity Relationship (QSAR) models for safe-by-design strategies in nanotechnology.