Integration of virus-like particle macromolecular bioreceptors in electrochemical biosensors

Rapid, sensitive and selective detection of chemical hazards and biological pathogens has shown growing importance in the fields of homeland security, public safety and personal health. In the past two decades, efforts have been focusing on performing point-of-care chemical and biological detections using miniaturized biosensors. These sensors convert target molecule binding events into measurable electrical signals for quantifying target molecule concentration. However, the low receptor density and the use of complex surface chemistry in receptors immobilization on transducers are common bottlenecks in the current biosensor development, adding to the cost, complexity and time. This dissertation presents the development of selective macromolecular Tobacco mosaic virus-like particle (TMV VLP) biosensing receptor, and the microsystem integration of VLPs in microfabricated electrochemical biosensors for rapid and performance-enhanced chemical and biological sensing. Two constructs of VLPs carrying different receptor peptides targeting at 2,4,6-trinitrotoluene (TNT) explosive or anti-FLAG antibody are successfully bioengineered. The VLP-based TNT electrochemical sensor utilizes unique diffusion modulation method enabled by biological binding between target TNT and receptor VLP. The method avoids the influence from any interfering species and environmental background signals, making it extremely suitable for directly quantifying the TNT level in a sample. It is also a rapid method that does not need any sensor surface functionalization process. For antibody sensing, the VLPs carrying both antibody binding peptides and cysteine residues are assembled onto the gold electrodes of an impedance microsensor. With two-phase immunoassays, the VLP-based impedance sensor is able to quantify antibody concentrations down to 9.1 ng/mL. A capillary microfluidics and impedance sensor integrated microsystem is developed to further accelerate the process of VLP assembly on sensors and improve the sensitivity. Open channel capillary micropumps and stop-valves facilitate localized and evaporation-assisted VLP assembly on sensor electrodes within 6 minutes. The VLP-functionalized impedance sensor is capable of label-free sensing of antibodies with the detection limit of 8.8 ng/mL within 5 minutes after sensor functionalization, demonstrating great potential of VLP-based sensors for rapid and on-demand chemical and biological sensing.

A Ride-Sharing System with High Capacity Vehicles and Flexible Meeting Points

In many major cities, fixed route transit systems such as bus and rail serve millions of trips per day. These systems have people collect at common locations (the station or stop), and board at common times (for example according to a predetermined schedule or headway). By using common service locations and times, these modes can consolidate many trips that have similar origins and destinations or overlapping routes. However, the routes are not sensitive to changing travel patterns, and have no way of identifying which trips are going unserved, or are poorly served, by the existing routes. On the opposite end of the spectrum, personal modes of transportation, such as a private vehicle or taxi, offer service to and from the exact origin and destination of a rider, at close to exactly the time they desire to travel. Despite the apparent increased convenience to users, the presence of a large number of small vehicles results in a disorganized, and potentially congested road network during high demand periods. The focus of the research presented in this paper is to develop a system that possesses both the on-demand nature of a personal mode, with the efficiency of shared modes. In this system, users submit their request for travel, but are asked to make small compromises in their origin and destination location by walking to a nearby meeting point, as well as slightly modifying their time of travel, in order to accommodate other passengers. Because the origin and destination location of the request can be adjusted, this is a more general case of the Dial-a-Ride problem with time windows. The solution methodology uses a graph clustering algorithm coupled with a greedy insertion technique. A case study is presented using actual requests for taxi trips in Washington DC, and shows a significant decrease in the number of vehicles required to serve the demand.

Effects of Information and Time of Use Pricing on Irish Electricity Demand and Supply

In this dissertation I quantify residential behavior response to interventions designed to reduce electricity demand at different periods of the day. In the first chapter, I examine the effect of information provision coupled with bimonthly billing, monthly billing, and in-home displays, as well as a time-of-use (TOU) pricing scheme to measure consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time usage information reduces electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the in-home display group is indistinguishable from the monthly treatment group. Monthly and bi-monthly billing treatments are not found to be statistically different from another. These findings suggest that increasing billing reports to the monthly level may be more cost effective for electricity generators who wish to decrease expenses and consumption, rather than providing in-home displays. In the following chapter, I examine the response of residential households after exposure to time of use tariffs at different hours of the day. I find that these treatments reduce electricity consumption during peak hours by almost four percent, significantly lowering demand. Within the model, I find evidence of overall conservation in electricity used. In addition, weekday peak reductions appear to carry over to the weekend when peak pricing is not present, suggesting changes in consumer habit. The final chapter of my dissertation imposes a system wide time of use plan to analyze the potential reduction in carbon emissions from load shifting based on the Ireland and Northern Single Electricity Market. I find that CO2 emissions savings are highest during the winter months when load demand is highest and dirtier power plants are scheduled to meet peak demand. TOU pricing allows for shifting in usage from peak usage to off peak usage and this shift in load can be met with cleaner and cheaper generated electricity from imports, high efficiency gas units, and hydro units.