Studying the generation of foam in the presence of nanoparticles using a microfluidic system

In this paper, a study on the generation of foam in the presence of nanoparticles in porous media using microfluidics is reported. Drainage and co-injection tests were carried out and monitored with a high-speed camera. Convolutional neural network model was applied to quantify foam texture over time, efficiently. Microscopy images show a generation process characterized by early snap-off, followed by lamella-division, and finally leave-behind. In the presence of nanoparticles, the latter stage is delayed due to resistance to drainage imparted by capillary forces within the liquid films. Moreover, a general relationship between the generation rate and the pressure gradient, which resembles the classical constitutive equation for foam generation, i.e., rg∝∇Pα, could be formulated. This indicates that the generation of a foam in the presence of partially hydrophobic nanoparticles and anionic surfactant, used for strong foam formation, follows the same mechanism of a foam stabilized only with surfactant.