ASU Scholarship Showcase

We investigate near-field radiative heat transfer between Indium Tin Oxide (ITO) nanowire arrays which behave as type 1 and 2 hyperbolic metamaterials. Using spatial dispersion dependent effective medium theory to model the dielectric function of the nanowires, the impact of filling fraction on the heat transfer is analyzed. Depending on the filling fraction, it is possible to achieve both types of hyperbolic modes. At 150 nm vacuum gap, the heat transfer between the nanowires with 0.5 filling fraction can be 11 times higher than that between two bulk ITOs. For vacuum gaps less than 150 nm the heat transfer increases as the filling fraction decreases. Results obtained from this study will facilitate applications of ITO nanowires as hyperbolic metamaterials for energy systems.

Gold absorbers based on plasmonic tapered coaxial holes (PTCHs) are demonstrated theoretically and experimentally. An average absorption of over 0.93 is obtained theoretically in a broad wavelength range from 300 nm to 900 nm without polarization sensitivity due to the structural symmetry. Strong scattering of the incident light by the tapered coaxial holes is the main reason for the high absorption in the short wavelength range below about 550 nm, while gap surface plasmon polaritons propagating along the taper dominate the resonance-induced high absorption in the long wavelength range. Combining two PTCHs with different structural parameters can further enhance the absorption and thus increase the spectral bandwidth, which is verified by a sample fabricated by focused ion beam milling. This design is promising to be extended to other metals to realize effective and efficient light harvesting and absorption.

Over the past couple of decades, quality has been an area of increased focus. Multiple models and approaches have been proposed to measure the quality in the construction industry. This paper focuses on determining the quality of one of the types of roofing systems used in the construction industry, i.e., sprayed polyurethane foam roofs (SPF roofs). Thirty-seven urethane-coated SPF roofs that were installed in 2005/2006 were visually inspected to measure the percentage of blisters and repairs three times over a period of four years, six years, and seven years. A repairing criteria was established after a six-year mark based on the data that were reported to contractors as vulnerable roofs. Furthermore, the relation between four possible contributing time-of-installation factors—contractor, demographics, season, and difficulty (number of penetrations and size of the roof in square feet) that could affect the quality of the roof was determined. Demographics and difficulty did not affect the quality of the roofs, whereas the contractor and the season when the roof was installed did affect the quality of the roofs.

Studies on urban heat island (UHI) have been more than a century after the phenomenon was first discovered in the early 1800s. UHI emerges as the source of many urban environmental problems and exacerbates the living environment in cities. Under the challenges of increasing urbanization and future climate changes, there is a pressing need for sustainable adaptation/mitigation strategies for UHI effects, one popular option being the use of reflective materials. While it is introduced as an effective method to reduce temperature and energy consumption in cities, its impacts on environmental sustainability and large-scale non-local effect are inadequately explored. This paper provides a synthetic overview of potential environmental impacts of reflective materials at a variety of scales, ranging from energy load on a single building to regional hydroclimate. The review shows that mitigation potential of reflective materials depends on a set of factors, including building characteristics, urban environment, meteorological and geographical conditions, to name a few. Precaution needs to be exercised by city planners and policy makers for large-scale deployment of reflective materials before their environmental impacts, especially on regional hydroclimates, are better understood. In general, it is recommended that optimal strategy for UHI needs to be determined on a city-by-city basis, rather than adopting a “one-solution-fits-all” strategy.

Land surface energy balance in a built environment is widely modelled using urban canopy models with representation of building arrays as big street canyons. Modification of this simplified geometric representation, however, leads to challenging numerical difficulties in improving physical parameterization schemes that are deterministic in nature. In this paper, we develop a stochastic algorithm to estimate view factors between canyon facets in the presence of shade trees based on Monte Carlo simulation, where an analytical formulation is inhibited by the complex geometry. The model is validated against analytical solutions of benchmark radiative problems as well as field measurements in real street canyons. In conjunction with the matrix method resolving infinite number of reflections, the proposed model is capable of predicting the radiative exchange inside the street canyon with good accuracy. Modeling of transient evolution of thermal filed inside the street canyon using the proposed method demonstrate the potential of shade trees in mitigating canyon surface temperatures as well as saving of building energy use. This new numerical framework also deepens our insight into the fundamental physics of radiative heat transfer and surface energy balance for urban climate modeling.

With the onset of large numbers of energy-flexible appliances, in particular plug-in electric and hybrid-electric vehicles, a significant portion of electricity demand will be somewhat flexible and accordingly may be responsive to changes in electricity prices. In the future, this increased degree of demand flexibility (and the onset of only short-term predictable intermittent renewable supply) will considerably exceed present level of uncertainty in day-ahead prediction of assumed inelastic demand. For such a responsive demand idealized, we consider a deregulated wholesale day-ahead electricity marketplace wherein bids by generators (or energy traders) are determined through a Nash equilibrium via a common clearing price (i.e., no location marginality). This model assumes the independent system operator (ISO) helps the generators to understand how to change their bids to improve their net revenue based on a model of demand-response. The model of demand-response (equivalently, demand-side bidding day ahead) is based on information from load-serving entities regarding their price-flexible demand. We numerically explore how collusion between generators and loads can manipulate this market. The objective is to learn how to deter such collusion, e.g., how to set penalties for significant differences between stated and actual demand, resulting in higher energy prices that benefit certain generators.

Location-based social networks (LBSNs) have attracted an increasing number of users in recent years, resulting in large amounts of geographical and social data. Such LBSN data provide an unprecedented opportunity to study the human movement from their socio-spatial behavior, in order to improve location-based applications like location recommendation. As users can check-in at new places, traditional work on location prediction that relies on mining a user’s historical moving trajectories fails as it is not designed for the cold-start problem of recommending new check-ins. While previous work on LBSNs attempting to utilize a user’s social connections for location recommendation observed limited help from social network information. In this work, we propose to address the cold-start location recommendation problem by capturing the correlations between social networks and geographical distance on LBSNs with a geo-social correlation model. The experimental results on a real-world LBSN dataset demonstrate that our approach properly models the geo-social correlations of a user’s cold-start check-ins and significantly improves the location recommendation performance.

We investigate high-dimensional nonlinear dynamical systems exhibiting multiple resonances under adiabatic parameter variations. Our motivations come from experimental considerations where time-dependent sweeping of parameters is a practical approach to probing and characterizing the bifurcations of the system. The question is whether bifurcations so detected are faithful representations of the bifurcations intrinsic to the original stationary system. Utilizing a harmonically forced, closed fluid flow system that possesses multiple resonances and solving the Navier-Stokes equation under proper boundary conditions, we uncover the phenomenon of the early effect. Specifically, as a control parameter, e.g., the driving frequency, is adiabatically increased from an initial value, resonances emerge at frequency values that are lower than those in the corresponding stationary system. The phenomenon is established by numerical characterization of physical quantities through the resonances, which include the kinetic energy and the vorticity field, and a heuristic analysis based on the concept of instantaneous frequency. A simple formula is obtained which relates the resonance points in the time-dependent and time-independent systems. Our findings suggest that, in general, any true bifurcation of a nonlinear dynamical system can be unequivocally uncovered through adiabatic parameter sweeping, in spite of a shift in the bifurcation point, which is of value to experimental studies of nonlinear dynamical systems.

As awareness of traumatic brain injury (TBI) increases, the need to detect mild forms and distinguish between the different severities of TBI becomes more apparent. The goal of this work is to develop a point-of-care sensor to detect whole blood biomarkers for rapid and sensitive diagnosis of TBI severity. Presented herein is the enzymatic detection of norepinephrine through the use of immobilization chemistry and impedance techniques. Sustained elevation of norepinephrine concentrations in the blood has been correlated to negative long-term outcomes in TBI cases, often resulting in permanent cognitive or physical deficits.

Novel analysis techniques have been used to identify an optimal binding frequency (371.1 Hz) of norepinephrine to the immobilized enzyme on a gold disk electrode. This form of analysis yielded a logarithmic fit characterized by exceptional responsivity (20.89 Ω/pgmL^-1), reproducibility (R² = 0.96), and lower limit of detection (98 pg/mL) first in purified samples, then in rabbit whole blood solutions. Once the optimal binding frequency was determined, the preliminary use of an impedance-time technique was attempted in this work. This technique more closely resembles the amperometric detection method used in commercial self-monitoring blood glucose meters, allowing for continuous or instantaneous measurement of blood borne biomarkers without compromising sensitivity. Future directions include exploration of simultaneous multi-marker detection with the impedance-time technique and experimentation with novel mesoporous materials to filter large blood components.

Electroplating of aluminum (Al) on silicon (Si) substrates has been demonstrated in an above-room-temperature ionic liquid for the metallization of wafer-Si solar cells. The electrolyte was prepared by mixing anhydrous aluminum chloride and 1-ethyl-3-methylimidazolium tetrachloroaluminate. The plating was carried out by means of galvanostatic electrolysis. The structural and compositional properties of the Al deposits were characterized, and the sheet resistance of the deposits revealed the effects of pre-bake conditions, deposition temperature, and post-deposition annealing conditions. It was found that dense, adherent Al deposits with resistivity in the high 10^-6 Ω-cm range can be reproducibly obtained directly on Si substrates.