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.

Control design and genetic algorithm optimization for electrostatic MEMS

This dissertation discusses structural-electrostatic modeling techniques, genetic algorithm based optimization and control design for electrostatic micro devices. First, an alternative modeling technique, the interpolated force model, for electrostatic micro devices is discussed. The method provides improved computational efficiency relative to a benchmark model, as well as improved accuracy for irregular electrode configurations relative to a common approximate model, the parallel plate approximation model. For the configuration most similar to two parallel plates, expected to be the best case scenario for the approximate model, both the parallel plate approximation model and the interpolated force model maintained less than 2.2% error in static deflection compared to the benchmark model. For the configuration expected to be the worst case scenario for the parallel plate approximation model, the interpolated force model maintained less than 2.9% error in static deflection while the parallel plate approximation model is incapable of handling the configuration. Second, genetic algorithm based optimization is shown to improve the design of an electrostatic micro sensor. The design space is enlarged from published design spaces to include the configuration of both sensing and actuation electrodes, material distribution, actuation voltage and other geometric dimensions. For a small population, the design was improved by approximately a factor of 6 over 15 generations to a fitness value of 3.2 fF. For a larger population seeded with the best configurations of the previous optimization, the design was improved by another 7% in 5 generations to a fitness value of 3.0 fF. Third, a learning control algorithm is presented that reduces the closing time of a radiofrequency microelectromechanical systems switch by minimizing bounce while maintaining robustness to fabrication variability. Electrostatic actuation of the plate causes pull-in with high impact velocities, which are difficult to control due to parameter variations from part to part. A single degree-of-freedom model was utilized to design a learning control algorithm that shapes the actuation voltage based on the open/closed state of the switch. Experiments on 3 test switches show that after 5-10 iterations, the learning algorithm lands the switch with an impact velocity not exceeding 0.2 m/s, eliminating bounce.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

Evaluation of sugar maple dieback in the Upper Great Lakes region and development of a forest health youth education program

Acer saccharum Marsh., is one of the most valuable trees in the northern hardwood forests. Severe dieback was recently reported by area foresters in the western Upper Great Lakes Region. Sugar Maple has had a history of dieback over the last 100 years throughout its range and different variables have been identified as being the predisposing and inciting factors in different regions at different times. Some of the most common factors attributed to previous maple dieback episodes were insect defoliation outbreaks, inadequate precipitation, poor soils, atmospheric deposition, fungal pathogens, poor management, or a combination of these. The current sugar maple dieback was evaluated to determine the etiology, severity, and change in dieback on both industry and public lands. A network of 120 sugar maple health evaluation plots was established in the Upper Peninsula, Michigan, northern Wisconsin, and eastern Minnesota and evaluated annually from 2009-2012. Mean sugar maple crown dieback between 2009-2012 was 12.4% (ranging from 0.8-75.5%) across the region. Overall, during the sampling period, mean dieback decreased by 5% but individual plots and trees continued to decline. Relationships were examined between sugar maple dieback and growth, habitat conditions, ownership, climate, soil, foliage nutrients, and the maple pathogen sapstreak. The only statistically significant factor was found to be a high level of forest floor impacts due to exotic earthworm activity. Sugar maple on soils with lower pH had less earthworm impacts, less dieback, and higher growth rates than those on soils more favorable to earthworms. Nutritional status of foliage and soil was correlated with dieback and growth suggesting perturbation of nutrient cycling may be predisposing or contributing to dieback. The previous winter's snowfall totals, length of stay on the ground, and number of days with freezing temperatures had a significant positive relationship to sugar maple growth rates. Sapstreak disease, Ceratocystis virescens, may be contributing to dieback in some stands but was not related to the amount of dieback in the region. The ultimate goal of this research is to help forest managers in the Great Lakes Region prevent, anticipate, reduce, and/or salvage stands with dieback and loss in the future. An improved understanding of the complex etiology associated with sugar maple dieback in the Upper Great Lakes Region is necessary to make appropriate silvicultural decisions. Forest Health education helps increase awareness and proactive forest management in the face of changing forest ecosystems. Lessons are included to assist educators in incorporating forest health into standard biological disciplines at the secondary school curricula.