Quantum dot / optical protein bio-nano hybrid system biosensing

The integration of novel nanomaterials with highly-functional biological molecules has advanced multiple fields including electronics, sensing, imaging, and energy harvesting. This work focuses on the creation of a new type of bio-nano hybrid substrate for military biosensing applications. Specifically it is shown that the nano-scale interactions of the optical protein bacteriorhodopsin and colloidal semiconductor quantum dots can be utilized as a generic sensing substrate. This work spans from the basic creation of the protein to its application in a novel biosensing system. The functionality of this sensor design originates from the unique interactions between the quantum dot and bacteriorhodopsin molecule when in nanoscale proximity. A direct energy transfer relationship has been established between coreshell quantum dots and the optical protein bacteriorhodopsin that substantially enhances the protein’s native photovoltaic capabilities. This energy transfer phenomena is largely distance dependent, in the sub-10nm realm, and is characterized experimentally at multiple separation distances. Experimental results on the energy transfer efficiency in this hybrid system correlate closely to theoretical predictions. Deposition of the hybrid system with nano-scale control has allowed for the utilization of this energy transfer phenomena as a modulation point for a functional biosensor prototype. This work reveals that quantum dots have the ability to activate the bacteriorhodopsin photocycle through both photonic and non-photonic energy transfer mechanisms. By altering the energy transferred to the bacteriorhodopsin molecule from the quantum dot, the electrical output of the protein can be modulated. A biosensing prototype was created in which the energy transfer relationship is altered upon target binding, demonstrating the applicability of a quantum dot/bacteriorhodopsin hybrid system for sensor applications. The electrical nature of this sensing substrate will allow for its efficient integration into a nanoelectronics array form, potentially leading to a small-low power sensing platform for remote toxin detection applications.

Development of a high performance parallel computing platform and its use in the study of nanostructures : clusters, sheets and tubes .

Small clusters of gallium oxide, technologically important high temperature ceramic, together with interaction of nucleic acid bases with graphene and small-diameter carbon nanotube are focus of first principles calculations in this work. A high performance parallel computing platform is also developed to perform these calculations at Michigan Tech. First principles calculations are based on density functional theory employing either local density or gradient-corrected approximation together with plane wave and gaussian basis sets. The bulk Ga2O3 is known to be a very good candidate for fabricating electronic devices that operate at high temperatures. To explore the properties of Ga2O3 at nonoscale, we have performed a systematic theoretical study on the small polyatomic gallium oxide clusters. The calculated results find that all lowest energy isomers of GamOn clusters are dominated by the Ga-O bonds over the metal-metal or the oxygen-oxygen bonds. Analysis of atomic charges suggest the clusters to be highly ionic similar to the case of bulk Ga2O3. In the study of sequential oxidation of these slusters starting from Ga2O, it is found that the most stable isomers display up to four different backbones of constituent atoms. Furthermore, the predicted configuration of the ground state of Ga2O is recently confirmed by the experimental result of Neumark's group. Guided by the results of calculations the study of gallium oxide clusters, performance related challenge of computational simulations, of producing high performance computers/platforms, has been addressed. Several engineering aspects were thoroughly studied during the design, development and implementation of the high performance parallel computing platform, rama, at Michigan Tech. In an attempt to stay true to the principles of Beowulf revolutioni, the rama cluster was extensively customized to make it easy to understand, and use - for administrators as well as end-users. Following the results of benchmark calculations and to keep up with the complexity of systems under study, rama has been expanded to a total of sixty four processors. Interest in the non-covalent intereaction of DNA with carbon nanotubes has steadily increased during past several years. This hybrid system, at the junction of the biological regime and the nanomaterials world, possesses features which make it very attractive for a wide range of applicatioins. Using the in-house computational power available, we have studied details of the interaction between nucleic acid bases with graphene sheet as well as high-curvature small-diameter carbon nanotube. The calculated trend in the binding energies strongly suggests that the polarizability of the base molecules determines the interaction strength of the nucleic acid bases with graphene. When comparing the results obtained here for physisorption on the small diameter nanotube considered with those from the study on graphene, it is observed that the interaction strength of nucleic acid bases is smaller for the tube. Thus, these results show that the effect of introducing curvature is to reduce the binding energy. The binding energies for the two extreme cases of negligible curvature (i.e. flat graphene sheet) and of very high curvature (i.e. small diameter nanotube) may be considered as upper and lower bounds. This finding represents an important step towards a better understanding of experimentally observed sequence-dependent interaction of DNA with Carbon nanotubes.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study

The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.

Synthesis of PDMS-metal oxide hybrid nanocomposites using an in situ sol-gel route

Organic-inorganic hybrid nanocomposites are widely studied and applied in broad areas because of their ability to combine the flexibility, low density of the organic materials with the hardness, strength, thermal stability, good optical and electronic properties of the inorganic materials. Polydimethylsiloxane (PDMS) due to its excellent elasticity, transparency, and biocompatibility has been extensively employed as the organic host matrix for nanocomposites. For the inorganic component, titanium dioxide and barium titanate are broadly explored as they possess outstanding physical, optical and electronic properties. In our experiment, PDMS-TiO2 and PDMS-BaTiO3 hybrid nanocomposites were fabricated based on in-situ sol-gel technique. By changing the amount of metal precursors, transparent and homogeneous PDMS-TiO2 and PDMS-BaTiO3 hybrid films with various compositions were obtained. Two structural models of these two types of hybrids were stated and verified by the results of characterization. The structures of the hybrid films were examined by a conjunction of FTIR and FTRaman. The morphologies of the cross-sectional areas of the films were characterized by FESEM. An Ellipsometer and an automatic capacitance meter were utilized to evaluate the refractive index and dielectric constant of these composites respectively. A simultaneous DSC/TGA instrument was applied to measure the thermal properties. For PDMS-TiO2 hybrids, the higher the ratio of titanium precursor added, the higher the refractive index and the dielectric constant of the composites are. The highest values achieved of refractive index and dielectric constant were 1.74 and 15.5 respectively for sample PDMS-TiO2 (1-6). However, when the ratio of titanium precursor to PDMS was as high as 20 to 1, phase separation occurred as evidenced by SEM images, refractive index and dielectric constant decreased. For PDMS-BaTiO3 hybrids, with the increase of barium and titanium precursors in the system, the refractive index and dielectric constant of the composites increased. The highest value was attained in sample PDMS-BaTiO3 (1-6) with a refractive index of 1.6 and a dielectric constant of 12.2. However, phase separation appeared in SEM images for sample PDMS-BaTiO3 (1-8), the refractive index and dielectric constant reduced to lower values. Different compositions of PDMS-TiO2 and PDMS-BaTiO3 hybrid films were annealed at 60 °C and 100 °C, the influences on the refractive index, dielectric constant, and thermal properties were investigated.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.