Understanding Nanoparticles Through Small-Scale Information

Nanoparticles produced during combustion — in engines, heating systems, or industrial processes — are thousands of times smaller than a grain of sand, yet they play a major role in both health and industry. Their ability to penetrate deep into the lungs and their influence on the efficiency of combustion systems make them critically important to understand.

Modeling how these particles move through turbulent air is still a major challenge. Turbulence — the chaotic, swirling motion of fluids — disrupts their trajectories in complex ways, making them hard to predict. And because these flows involve many different scales, standard simulations often miss key details.

This project aims to improve the way we model nanoparticle transport by combining physical equations with modern data techniques. A key goal is to recover fine-scale information lost in traditional models, using super-resolution methods inspired by image processing.

By better capturing how these particles behave, the work could lead to more accurate pollution forecasts, cleaner industrial processes, and safer combustion technologies — all crucial in a world facing both environmental and energy challenges.