Bacteriorhodopsin protein hybrids for chemical and biological sensing

Bacteriorhodopsin (bR), an optoelectric protein found in Halobacterium salinarum, has the potential for use in protein hybrid sensing systems. Bacteriorhodopsin has no intrinsic sensing properties, however molecular and chemical tools permit production of bR protein hybrids with transducing and sensing properties. As a proof of concept, a maltose binding protein-bacteriorhodopsin ([MBP]-bR) hybrid was developed. It was proposed that the energy associated with target molecule binding, maltose, to the hybrid sensor protein would provide a means to directly modulate the electrical output from the MBP-bR bio-nanosensor platform. The bR protein hybrid is produced by linkage between bR (principal component of purified purple membrane [PM]) and MBP, which was produced by use of a plasmid expression vector system in Escherichia coli and purified utilizing an amylose affinity column. These proteins were chemically linked using 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS), which facilitates formation of an amide bond between a primary carboxylic acid and a primary amine. The presence of novel protein hybrids after chemical linkage was analyzed by SDSPAGE. Soluble proteins (MBP-only derivatives and unlinked MBP) were separated from insoluble proteins (PM derivatives and unlinked PM) using size exclusion chromatography. The putatively identified MBP-bR protein hybrid, in addition to unlinked bR, was collected. This sample was normalized for bR concentration to native PM and both were deposited onto indium tin oxide (ITO) coated glass slides by electrophoretic sedimentation. The photoresponse of both samples, activated using 100 Watt tungsten lamp at 10 cm distance, were equal at 175 mV. Testing of deposited PM with 1 mM sucrose or 1 mM maltose showed no change in the photoresponse of the xiv material, however addition of 1 mM maltose to the deposited MBP-bR linked hybrid material elicited a 57% decrease in photoresponse indicating a positive response for targeting of maltose. This chemically linked MBP-bR hybrid protein, with bacteriorhodopsin, as a photoresponsive transducing substrate, shows promise for creation of a universal sensing array by attachment of other pertinent sensing materials, in lieu of the maltose binding protein utilized. This strategy would allow significant reduction in sensor size, while increasing responsiveness and sensitivity at nano and picomolar levels.

HIGH VOLTAGE ELECTROPHORETIC DEPOSITION FOR ELECTROCHEMICAL ENERGY STORAGE AND OTHER APPLICATIONS

High voltage electrophoretic deposition (HVEPD) has been developed as a novel technique to obtain vertically aligned forests of one-dimensional nanomaterials for efficient energy storage. The ability to control and manipulate nanomaterials is critical for their effective usage in a variety of applications. Oriented structures of one-dimensional nanomaterials provide a unique opportunity to take full advantage of their excellent mechanical and electrochemical properties. However, it is still a significant challenge to obtain such oriented structures with great process flexibility, ease of processing under mild conditions and the capability to scale up, especially in context of efficient device fabrication and system packaging. This work presents HVEPD as a simple, versatile and generic technique to obtain vertically aligned forests of different one-dimensional nanomaterials on flexible, transparent and scalable substrates. Improvements on material chemistry and reduction of contact resistance have enabled the fabrication of high power supercapacitor electrodes using the HVEPD method. The investigations have also paved the way for further enhancements of performance by employing hybrid material systems and AC/DC pulsed deposition. Multi-walled carbon nanotubes (MWCNTs) were used as the starting material to demonstrate the HVEPD technique. A comprehensive study of the key parameters was conducted to better understand the working mechanism of the HVEPD process. It has been confirmed that HVEPD was enabled by three key factors: high deposition voltage for alignment, low dispersion concentration to avoid aggregation and simultaneous formation of holding layer by electrodeposition for reinforcement of nanoforests. A set of suitable parameters were found to obtain vertically aligned forests of MWCNTs. Compared with their randomly oriented counterparts, the aligned MWCNT forests showed better electrochemical performance, lower electrical resistance and a capability to achieve superhydrophpbicity, indicating their potential in a broad range of applications. The versatile and generic nature of the HVEPD process has been demonstrated by achieving deposition on flexible and transparent substrates, as well as aligned forests of manganese dioxide (MnO2) nanorods. A continuous roll-printing HVEPD approach was then developed to obtain aligned MWCNT forest with low contact resistance on large, flexible substrates. Such large-scale electrodes showed no deterioration in electrochemical performance and paved the way for practical device fabrication. The effect of a holding layer on the contact resistance between aligned MWCNT forests and the substrate was studied to improve electrochemical performance of such electrodes. It was found that a suitable precursor salt like nickel chloride could be used to achieve a conductive holding layer which helped to significantly reduce the contact resistance. This in turn enhanced the electrochemical performance of the electrodes. High-power scalable redox capacitors were then prepared using HVEPD. Very high power/energy densities and excellent cyclability have been achieved by synergistically combining hydrothermally synthesized, highly crystalline α-MnO2 nanorods, vertically aligned forests and reduced contact resistance. To further improve the performance, hybrid electrodes have been prepared in the form of vertically aligned forest of MWCNTs with branches of α-MnO2 nanorods on them. Large- scale electrodes with such hybrid structures were manufactured using continuous HVEPD and characterized, showing further improved power and energy densities. The alignment quality and density of MWCNT forests were also improved by using an AC/DC pulsed deposition technique. In this case, AC voltage was first used to align the MWCNTs, followed by immediate DC voltage to deposit the aligned MWCNTs along with the conductive holding layer. Decoupling of alignment from deposition was proven to result in better alignment quality and higher electrochemical performance.

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.