Biological materials : Part A. tuning LCST of raft copolymers and gold/copolymer hybrid nanoparticles and Part B. biobased nanomaterials

The research described in this dissertation is comprised of two major parts. The first part studied the effects of asymmetric amphiphilic end groups on the thermo-response of diblock copolymers of (oligo/di(ethylene glycol) methyl ether (meth)acrylates, OEGA/DEGMA) and the hybrid nanoparticles of these copolymers with a gold nanoparticle core. Placing the more hydrophilic end group on the more hydrophilic block significantly increased the cloud point compared to a similar copolymer composition with the end group placement reversed. For a given composition, the cloud point was shifted by as much as 28 °C depending on the placement of end groups. This is a much stronger effect than either changing the hydrophilic/hydrophobic block ratio or replacing the hydrophilic acrylate monomer with the equivalent methacrylate monomer. The temperature range of the coil-globule transition was also altered. Binding these diblock copolymers to a gold core decreased the cloud point by 5-15 °C and narrowed the temperature range of the coil-globule transition. The effects were more pronounced when the gold core was bound to the less hydrophilic block. Given the limited numbers of monomers that are approved safe for in vivo use, employing amphiphilic end group placement is a useful tool to tune a thermo-response without otherwise changing the copolymer composition. The second part of the dissertation investigated the production of value-added nanomaterials from two biorefinery “wastes”: lignin and peptidoglycan. Different solvents and spinning methods (melt-, wet-, and electro-spinning) were tested to make lignin/cellulose blended and carbonized fibers. Only electro-spinning yielded fibers having a small enough diameter for efficient carbonization ( Peptidoglycan (a bacterial cell wall material) was copolymerized with poly-(3-hydroxybutyrate), a common polyhydroxyalkanoate produced by bacteria with the objective of determining if a useful material could be obtained with a less rigorous work-up on harvesting polyhydroxyalkanoates. The copolyesteramide product having 25 wt.% peptidoglycan from a highly purified peptidoglycan increased thermal stability by 100-200 °C compared to the poly-(3-hydroxybutyrate) control, while a less pure peptidoglycan, harvested from B. megaterium (ATCC 11561), gave a 25-50 °C increase in thermal stability. Both copolymers absorbed more moisture than pure poly-(3-hydroxybutyrate). The results suggest that a less rigorously harvested and purified polyhydroxyalkanoate might be useful for some applications.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.