We believe that a thorough understanding of bubble lodgement and dislodgment in a complex capillary network can contribute to control the bubble flow in blood vessels and improve the feasibility and efficiency of transport, by helping us understand where the bubble ultimately lodges, whether the bubble can be lodged and dislodged properly, and the persistence time of microbubbles lodged around the targeted sites.
In the past, research work reported in the literature only investigated bubble dislodgment in single straight channels and Y-type or U-type channels and did not consider the effect of network complexity on the dislodgment. Here in this paper, we focus on the pressure required to dislodge single bubbles from a microscopic capillary network and investigate the factors affecting the dislodging pressure to facilitate the precise control of bubble flows in porous media.
We designed a capillary network with multibifurcation and a smoothly changed diameter to closely mimic the structure of the physiological vascular networks and conducted more than 600 bubble dislodgment experiments to understand the effect of the network structure, channel dimensions, and bubble length on the dislodging pressure.
The results indicate that the network structure is a dominant factor affecting the dislodging pressure that increases with the increase in network complexity. The effect of bubble length on the dislodging pressure depends on the bubble length. When the bubble length is less than a certain value, which is around 2 mm in this study, the dislodging pressure increases significantly with the decrease of bubble length. When the bubble length is larger than 2 mm, the dislodging pressure is independent of the bubble length.
To explain the bubble dislodgment in complex capillary networks, we have also derived a one-dimensional model to fully describe the bubble dislodgment in a complex capillary network and to predict the dislodging pressure. The model agrees well with the experimental results and indicates that the dislodging pressure is the function of bubble length, channel dimension, and network structure.
For more information on this work, you can read the original paper here: https://www.liebertpub.com/doi/pdf/10.1089/soro.2018.0026
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