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Title: Modelling degradation of bioresorbable polymeric devices
Author: Wang, Ying
ISNI:       0000 0004 2715 1634
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2009
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Bioresorbable polymers, especially the homo and co-polymers of poly lactic acid (PLA) and poly glycolic acid (PGA), have been used for a broad range of applications for the last three decades owing to their biodegradable, biocompatible and non-toxic natures. One of the applications for these polymers is in the orthopaedic surgery as bone fixation device. According to the Wolff‟s law, if the bone fixation devices are overly strong to shield the healing bone from sufficient stress stimulation, the bone will resorb to an extent. Therefore the optimised design of such devices relies on the prediction of the stress redistribution between the device and the bone during the device degradation. However, the auto-catalysis nature of the polymer degradation brings extra complications to the modelling of the device degradation. Currently the time consuming trial and error approach is widely employed in the device development. In fact mathematical models and the finite element method can be a great assistance to the designing of these resorbable devices. This thesis presents a complete model for the interaction between a resorbable fixation device and a healing bone. A phenomenological model is firstly presented that can capture the main features of the polymer degradation. An important factor in this model is the effective diffusion coefficient for the oligmers which is studied subsequently. Then an entropy theory based model is presented to relate the decay of Young‟s modulus to the polymer degradation. Finally the polymer degradation model and the Young‟s modulus decay model is integrated with a bone remodelling model and stress analysis to predict the growth or decay of a healing bone that is “protected” by a bioresorbable fixation device. The work in this thesis focuses on amorphous polymers. The work is entirely computational which is guided by existing experimental data and observations in the literature.
Supervisor: Pan, Jingzhe Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available