Visco-Chemo-Rheological Behavior in High Tg Shape Memory Polymers

Thursday, May 23, 2013: 11:30
Congress Hall 2 (OREA Pryamida Hotel)
Mr. Kannan Dasharathi , University of Michigan, Ann Arbor, MI
Dr. John A. Shaw , University of Michigan, Ann Arbor, MI
Thermo-responsive Shape Memory Polymers (SMPs) rely on the dramatic change in characteristic relaxation time across the rubber-glass transition temperature (Tg) to exhibit shape memory behavior. This ability to revert to a preset shape makes thermo-responsive SMPs an attractive option for adaptive tooling and as matrix material for damage healing or memory composites. In some SMPs, the Tg may be nearby or even exceed the chemo-rheological temperature (Tcr). While the changes to the macromolecular network  resulting from purely visco-elastic behavior are recoverable in time, the chemo-rheological degradation at temperatures beyond Tcr due to oxidative scission and recross-linking results in either irrecoverable residual strain or embrittlement of the polymer. These can limit the useful life of an SMP device or application.

The purpose of this research is to study the chemo-rheological degradation of SMPs and its effects on the shape memory behavior and develop a design space to predict the useful operating range for particular applications. We present an experimental study of the degradation of the uniaxial thermo-mechanical behavior in a commercially available epoxy SMP, Veriflex-E (Tg~100°C), subjected to temperature conditions of 110-150°C. Extending the approach originated by Tobolsky, the effects of scission and recross-linking of the macromolecular network on the shape memory behavior is deduced by performing intermittent shape memory cycles during constant strain and intermittent stretch-relaxation experiments. The intermittent stretch-relaxation tests are also used to study the interpenetrative characteristics of visco-chemo-rheological behavior. These results are finally used to calibrate a constitutive model within a continuum multi-network framework to predict the evolution of behavior for general cyclic thermo-mechanical histories.