Université Paris-Est, Laboratoire Navier (ENPC-IFSTTAR-CNRS), Champs sur Marne 77420, France.
Experimental Soft Condensed Matter Group, School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA.
Phys Rev Lett. 2018 Apr 6;120(14):148001. doi: 10.1103/PhysRevLett.120.148001.
From observations of the progressive deposition of noncolloidal particles by geometrical exclusion effects inside a 3D model porous medium, we get a complete dynamic view of particle deposits over a full range of regimes from transport over a long distance to clogging and caking. We show that clogging essentially occurs in the form of an accumulation of elements in pore size clusters, which ultimately constitute regions avoided by the flow. The clusters are dispersed in the medium, and their concentration (number per volume) decreases with the distance from the entrance; caking is associated with the final stage of this effect (for a critical cluster concentration at the entrance). A simple probabilistic model, taking into account the impact of clogging on particle transport, allows us to quantitatively predict all these trends up to a large cluster concentration, based on a single parameter: the clogging probability, which is a function of the confinement ratio. This opens the route towards a unification of the different fields of particle transport, clogging, caking, and filtration.
通过观察非胶体颗粒在 3D 模型多孔介质中因几何排除效应而逐渐沉积的情况，我们可以全面了解颗粒在整个传输范围内的沉积情况，包括从远距离传输到堵塞和结块的过程。我们表明，堵塞实质上是以在孔径群中积累元素的形式发生的，这些元素最终构成了流动所避免的区域。这些簇分散在介质中，其浓度（单位体积的数量）随着与入口的距离的增加而降低；结块与该效应的最后阶段相关（在入口处达到临界簇浓度时）。一个简单的概率模型，考虑了堵塞对颗粒传输的影响，允许我们根据单一参数（堵塞概率）定量预测所有这些趋势，直至达到较大的簇浓度，该参数是约束比的函数。这为颗粒传输、堵塞、结块和过滤等不同领域的统一开辟了道路。
