Flexible high-deflection strain gauges have been demonstrated as cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, partially owing to the viscoelastic nature of the strain gauges. On top of the non-linear viscoelastic behavior, dynamic resistance response is even more difficult to capture due to spikes in resistance during strain changes. This research examines the relationships between stress, strain, and resistance in nanocomposite sensors during dynamic strain situations. Under the assumption that both macroscopic stress and resistance are governed by microscopic stress concentrations at the junctions between nanoparticles and silicone matrix, the stress-resistance relationship is analyzed. Both stress and resistance are found to exhibit aspects of viscoelastic behavior, including creep decay and relaxation during constant strains. However, the resistance spikes are found to be more complex than a simple stress-resistance model can capture. This research then develops a model that captures the strain-resistance relationship of the sensors, including resistance spikes, during cyclical movements. The forward model, which converts strain to resistance, is comprised of four parts to accurately capture the different aspects of the sensor response: a quasi-static linear model, a spike magnitude model, a long-term creep decay model, and a short-term decay model. An inverse problem approach is used to create an inverse model, which predicts the strain vs time data that would result in the observed resistance data. The model is calibrated for a particular sensor from a small amount of cyclic data from a single test. The resulting sensor-specific model is able to accurately predict the resistance output with an R-squared value of 0.90. The inverse model is able to accurately predict key strain characteristics with a percent error of 0.5. The model can be used in a wide range of applications, including biomechanical modeling and analysis. It is found that the resistance spikes are directly correlated to the strain acceleration in terms of timing and in terms of magnitude. Poisson contraction rates and voids in the material are possible causes for resistance spikes during dynamic strain movements.

Molecular dynamics simulations were carried out on traditional polymers copolymerized with POSS (Polyhedral Oligomeric Silsesquioxanes) derivatives to identify the reason behind improved properties imparted to the conventional polymers with the chemical incorporation of POSS. Two classes of systems are used in the present study, namely the polystyrene and polymethyl methacrylate systems. Seven systems are studied in the polystyrene class. The effect of corner substituent groups of the POSS cage on the properties of the polymer nanocomposites was studied using the polystyrene. In addition, the effect of the type of cage structure on the properties was studied using T8, T10 and T12 POSS cage structures containing phenyl substituents on each POSS cage. Systems with polymethyl methacrylate were studied to analyze the effect of mole percent of POSS on the polymer properties, holding the corner substituents on the POSS unit constant. The corner function used was the isobutyl group. The properties analyzed using simulations include glass transition temperature, volumetric thermal expansion coefficient, X-ray scattering data, solubility parameter and mechanical properties. In both polystyrene and polymethyl methacrylate systems, simulations were also carried out on the pure parent polymers for the sake of comparison. The effect of forcefield on the predicted properties was studied using both COMPASS and PCFF forcefields. Performance analysis of the code used in the present simulation was done by analyzing the parallel run time of simulations involving pure atactic polystyrene.

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