Doctor of Philosophy (PhD)
Department of Mechanical & Industrial Engineering
In this study, a new shape memory thermoset network with giant stress and energy output in rubbery state is synthesized and studied firstly since the low output in stress and energy in rubbery state has been a bottleneck for wide-spread applications of thermoset shape memory polymers (SMPs). Traditionally, stress or energy storage in thermoset network is through entropy reduction by mechanical deformation or programming. We here report another mechanism for energy storage, which stores energy primarily through enthalpy increase by stretched bonds during programming. As compared to entropy-driven counterparts, which usually have a stable recovery stress from tenths to several MPa and energy output of several tenths MJ/m3, our rubbery network achieved a recovery stress of 17.0 MPa and energy output of 2.12 MJ/m3 in bulk form. Subsequently, this new shape memory thermoset polymer is fabricated into powder and particle for to serve as the expansive additive of the cement used in petroleum industry. Shape memory polymer has been identified and studied as a new generation of the expansive additive for the cement from our previous study. It has showed a good expansion ability and the preservation of the mechanical property. However, for the deeper unground, the higher temperature as the trigger of shape memory effect is necessary. Here we report the new shape memory polymer with the giant stress and energy output can achieve a 1.2% circumferential expansion by adding 6% weight percent in particle form. Moreover, it can enhance the mechanical property in terms of compressive strength, Young’s modulus and the compressive strain at the same time which is a rare accomplishment by single type additive. Moreover, the E-glass fiber FRP rebar and the reinforced concrete can be obtained. The curved FRP can produce 77.8 MPa bending recovery stress.
Fan, Jizhou, "High Enthalpy Storage Thermoset Network with Giant Stress and Energy Output in Rubbery State and Associated Applications" (2019). LSU Doctoral Dissertations. 4991.