Whether the dust borne on the violent winds of a tornado or the sugar grains in a swirled cup of coffee, the behavior of particles carried along in turbulence is subject to some similarities -- all of them difficult to predict at scale. As described in a recent publication in the Proceedings of the National Academies of Science, a research team led by Los Alamos National Laboratory scientists has developed a first-of-its-kind machine learning framework that models chaotic particle motions in a t