Constrained Hydrogel swelling in Biological Sensors : A Finite Element Method Approach

Material models has been developed for anionic and/or cationic hydrogels, with a simulation framework implemented in MATLAB and the finite element software ABAQUS. The geometry of the simulations is a hemispheroidal hydrogel, divided into a core with a shell, covalently attached to an optical fiber....

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Bibliographic Details
Main Author: Sveinsson, Hrafn Mar
Format: Others
Language:English
Published: Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk 2012
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Online Access:http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19103
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Summary:Material models has been developed for anionic and/or cationic hydrogels, with a simulation framework implemented in MATLAB and the finite element software ABAQUS. The geometry of the simulations is a hemispheroidal hydrogel, divided into a core with a shell, covalently attached to an optical fiber. The material models have been used to estimate the chemical parameters of poly-acrylamide hydrogels containing anionic or cationic monomer groups. Simulations comparing free and constrained swelling has been conducted in order to determine the effect of the geometrical constriction to the optical fiber. Constrained hydrogel swelling featuring shells with different properties than the core was also investigated.The aim of the study was to validate the material models and examine the effects of geometrical constrictions together with shell-impregnation. The anionic material model was shown to reproduce experimental swelling data, while the cationic material model only reproduced the data for ionic strength greater than 100 mM. Restricting the hydrogel to an optical fiber resulted in decreased change in volume and an increase in the axial swelling. The model was able to reproduce reported reduction in the swelling for an impregnated anionic hydrogel by using a neutral shell in the simulations, but failed to recreate the shape of the swelling curve. With the reduction of swelling as a basis, a new method for estimating thin-layer properties has been developed.