Journal
JOURNAL OF FLUID MECHANICS
Volume 947, Issue -, Pages -Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/jfm.2022.641
Keywords
porous media; polymers; microfluidics
Categories
Funding
- Leverhulme Trust Research Leadership Award 'Shape-Transforming Active Microfluidics'
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Thermo-responsive hydrogels exhibit significant expansion and contraction in response to temperature changes, making them promising materials for controllable actuators in micro-scale devices. By studying these systems using a poro-elastic model, we can better understand the dynamic properties and different swelling and shrinking behaviors of thermo-responsive hydrogels.
Thermo-responsive hydrogels arc a promising material for creating controllable actuators for use in micro-scale devices, since they expand and contract significantly (absorbing or expelling fluid) in response to relatively small temperature changes. Understanding such systems can be difficult because of the spatially and temporally varying properties of the gel, and the complex relationships between the fluid dynamics, elastic deformation of the gel and chemical interaction between the polymer and fluid. We address this using a poro-elastic model, considering the dynamics of a thermo-responsive spherical hydrogel after a sudden change in the temperature that should result in substantial swelling or shrinking. We focus on two model examples, with equilibrium parameters extracted from data in the literature. We find a range of qualitatively different behaviours when swelling and shrinking, including cases where swelling and shrinking happen smoothly from the edge, and other situations that result in the formation of an inwards-travelling spherical front that separates a core and shell with markedly different degrees of swelling. We then characterise when each of these scenarios is expected to occur. An approximate analytical form for the front dynamics is developed, with two levels of constant porosity, that well-approximates the numerical solutions. This system can be evolved forward in time, and is simpler to solve than the full numerics, allowing for more efficient predictions to be made, such as when deciding dosing strategies for drug-laden hydrogels.
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