This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.

Identification of early damage in polymer composites is of great importance. We have incorporated cyclobutane-containing cross-linked polymers into an epoxy matrix, studied the effect on thermal and mechanical properties, and, more importantly, demonstrated early damage detection through mechanically induced fluorescence generation. Two cinnamate derivatives, 1,1,1-tris(cinnamoyloxymethyl) ethane (TCE) and poly(vinyl cinnamate) (PVCi), were photoirradiated to produce cyclobutane-containing polymer. The effects on the thermal and mechanical properties with the addition of cyclobutane-containing polymer into epoxy matrix were investigated. The emergence of cracks was detected by fluorescence at a strain level just beyond the yield point of the polymer blends, and the fluorescence intensified with accumulation of strain. Overall, the results show that damage can be detected through fluorescence generation along crack propagation.

Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.