When the dust settles: predicting deposition of particulate and aerosols

预测超细颗粒和雾化液滴的沉积在广泛的应用中非常重要：从了解呼吸系统中的病原体或载药液滴沉积到使用环境传感器确定空气中颗粒物的组成。在起作用的物理是多种多样的，它的准确预测需要一个多尺度和多物理模型，远远超出了目前的最先进的技术。这样的模型将结合流体动力学、动力学理论、朗之万动力学和不确定性量化的技术，并解决广泛的物理问题，包括稀薄气体动力学、蠕动流动、微尺度蒸发和布朗运动。

Predicting the deposition of ultra-fine particulate and aerosolized drops is important in a wide range of applications: from understanding pathogen or drug-laden droplet deposition in the respiratory systems to determining the composition of airborne particulate matter using environmental sensors. The physics at play is diverse, and its accurate prediction requires a multi-scale and multi-physics model, far beyond the current state-of-the-art. Such a model will combine techniques from fluid dynamics, kinetic theory, Langevin dynamics, and uncertainty quantification, and tackle a broad range of physics including rarefied gas dynamics, creeping flow, micro-scale evaporation, and Brownian motion.