Atmospheric particles impact climate and health. Most particles form through gas molecules colliding and sticking together. We use molecular dynamics accelerated by machine learning to study this process. We found that standard machine learning models often fail to capture the long-range forces driving collisions, and models with explicit long-range corrections are needed. This work provides a blueprint for accurate simulations of particle formation.