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Fabrication and characterization of shape memory polymers at small scales

The objective of this research is to thoroughly investigate the shape memory effect
in polymers, characterize, and optimize these polymers for applications in information storage systems.
Previous research effort in this field concentrated on shape memory metals for
biomedical applications such as stents. Minimal work has been done on shape memory poly-
mers; and the available work on shape memory polymers has not characterized the behaviors
of this category of polymers fully. Copolymer shape memory materials based on diethylene
glycol dimethacrylate (DEGDMA) crosslinker, and tert butyl acrylate (tBA) monomer are
designed. The design encompasses a careful control of the backbone chemistry of the materials.
Characterization methods such as dynamic mechanical analysis (DMA), differential
scanning calorimetry (DSC); and novel nanoscale techniques such as atomic force microscopy
(AFM), and nanoindentation are applied to this system of materials. Designed experiments
are conducted on the materials to optimize spin coating conditions for thin films. Furthermore,
the recovery, a key for the use of these polymeric materials for information storage, is
examined in detail with respect to temperature. In sum, the overarching objectives of the
proposed research are to: (i) design shape memory polymers based on polyethylene glycol
dimethacrylate (PEGDMA) and diethylene glycol dimethacrylate (DEGDMA) crosslinkers,
2-hydroxyethyl methacrylate (HEMA) and tert-butyl acrylate monomer (tBA). (ii) utilize
dynamic mechanical analysis (DMA) to comprehend the thermomechanical properties of
shape memory polymers based on DEGDMA and tBA. (iii) utilize nanoindentation and
atomic force microscopy (AFM) to understand the nanoscale behavior of these SMPs, and
explore the strain storage and recovery of the polymers from a deformed state. (iv) study
spin coating conditions on thin film quality with designed experiments. (iv) apply neural
networks and genetic algorithms to optimize these systems.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/26714
Date17 November 2008
CreatorsWornyo, Edem
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Detected LanguageEnglish
TypeDissertation

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