论文标题
模型研究呼吸液滴通过面罩驱动的呼吸液滴研究
Model studies on motion of respiratory droplets driven through a face mask
论文作者
论文摘要
面罩用于拦截呼吸液滴，以防止空气疾病扩散。设计具有提高效率的面罩需要微观了解呼吸液滴如何通过口罩移动。在这里，我们研究了一个简单的模型，以通过口罩拦截液滴。掩模被视为不对称限制中的聚合物网络，而液滴则被视为微米大小的示踪胶体粒子，以模仿呼吸的驱动力。我们使用Langevin Dynamics（通过聚合物网络的示踪粒子渗透）进行数值研究。我们表明，渗透是在Arrhenius依赖温度之后的激活过程。负责激活过程的势能曲线会随着示踪剂的大小，示踪珠相互作用，网络刚度以及驱动力和限制长度的降低而增加。更深的能屏障导致提高效率，以在室温下驱动力的情况下拦截给定尺寸的示踪剂颗粒。我们的研究可能有助于以提高效率设计面具。
Face masks are used to intercept respiratory droplets to prevent spreading of air-borne diseases. Designing face masks with better efficiency needs microscopic understanding on how respiratory droplets move through a mask. Here we study a simple model on the interception of droplets by a face mask. The mask is treated as a polymeric network in an asymmetric confinement, while the droplet is taken as a micrometer sized tracer colloidal particle, subject to driving force that mimics the breathing. We study numerically, using the Langevin dynamics, the tracer particle permeation through the polymeric network. We show that the permeation is an activated process following an Arrhenius dependence on temperature. The potential energy profile responsible for the activation process increases with tracer size, tracer bead interaction, network rigidity and decreases with the driving force and confinement length. A deeper energy barrier led to better efficiency to intercept the tracer particles of a given size in the presence of driving force at room temperature. Our studies may help to design mask with better efficiency.
