ASU Scholarship Showcase

In this letter, we study the near-field radiative heat transfer between two metamaterial substrates coated with silicon carbide (SiC) thin films. It is known that metamaterials can enhance the near-field heat transfer over ordinary materials due to excitation of magnetic plasmons associated with s polarization, while strong surface phonon polariton exists for SiC. By careful tuning of the optical properties of metamaterial, it is possible to excite electrical and magnetic resonances for the metamaterial and surface phonon polaritons for SiC at different spectral regions, resulting in the enhanced heat transfer. The effect of the SiC film thickness at different vacuum gaps is investigated. Results obtained from this study will be beneficial for application of thin film coatings for energy harvesting.

Accelerated life test (ALT) planning in Bayesian framework is studied in this paper with a focus of differentiating competing acceleration models, when there is uncertainty as to whether the relationship between log mean life and the stress variable is linear or exhibits some curvature. The proposed criterion is based on the Hellinger distance measure between predictive distributions. The optimal stress-factor setup and unit allocation are determined at three stress levels subject to test-lab equipment and test-duration constraints. Optimal designs are validated by their recovery rates, where the true, data-generating, model is selected under the DIC (Deviance Information Criterion) model selection rule, and by comparing their performance with other test plans. Results show that the proposed optimal design method has the advantage of substantially increasing a test plan׳s ability to distinguish among competing ALT models, thus providing better guidance as to which model is appropriate for the follow-on testing phase in the experiment.

In this work, a selective solar absorber made of nanostructured titanium gratings deposited on an ultrathin MgF₂ spacer and a tungsten ground film is proposed and experimentally demonstrated. Normal absorptance of the fabricated solar absorber is characterized to be higher than 0.9 in the UV, visible and, near infrared (IR) regime, while the mid-IR emittance is around 0.2. The high broadband absorption in the solar spectrum is realized by the excitation of surface plasmon and magnetic polariton resonances, while the low mid-IR emittance is due to the highly reflective nature of the metallic components. Further directional and polarized reflectance measurements show wide-angle and polarization-insensitive high absorption within solar spectrum. Temperature-dependent spectroscopic characterization indicates that the optical properties barely change at elevated temperatures up to 350 °C. The solar-to-heat conversion efficiency with the fabricated metamaterial solar absorber is predicted to be 78% at 100 °C without optical concentration or 80% at 400 °C with 25 suns. The performance could be further improved with better fabrication processes and geometric optimization during metamaterial design. The strong spectral selectivity, favorable diffuse-like behavior, and good thermal stability make the metamaterial selective absorber promising for significantly enhancing solar thermal energy harvesting in various systems at mid to high temperatures.

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

Primary emissions from anthropogenic and biogenic sources as well as secondary formation are responsible for the pollution levels of ambient air in major urban areas. These sources release fine particles into the air that negatively impact human health and the environment. Organic molecular markers, which are compounds that are unique to specific PM_2.5 sources, can be utilized to identify the major emission sources in urban areas. In this study, 43 representative PM_2.5 samples, for both daytime and nighttime periods, were built from individual samples collected in an urban site of the Monterrey metropolitan area (MMA) during the spring and fall of 2011 and 2012. The samples were analyzed for organic carbon, elemental carbon, and organic molecular markers. Several diagnostic tools were employed for the preliminary identification of emission sources. Organic compounds for eight compound classes were quantified. The n-alkanoic acids were the most abundant, followed by n-alkanes, wood smoke markers, and levoglucosan/alkenoic acids. Polycyclic aromatic hydrocarbons (PAHs) and hopanes were less abundant. The carbon preference index (0.7–2.6) for n-alkanes indicates a major contribution of anthropogenic and mixed sources during the fall and the spring, respectively. Hopanes levels confirmed the contribution from gasoline and diesel engines. In addition, the contribution of gasoline and diesel vehicle exhaust was confirmed and identified by the PAH concentrations in PM_2.5. Diagnostic ratios of PAHs showed emissions from burning coal, wood, biomass, and other fossil fuels. The total PAHs and elemental carbon were correlated (r² =  0.39–0.70) across the monitoring periods, reinforcing that motor vehicles are the major contributors of PAHs. Cholesterol levels remained constant during the spring and fall, showing evidence of the contribution of meat-cooking operations, while the isolated concentrations of levoglucosan suggested occasional biomass burning events. Finally, source attribution results obtained using the CMB (chemical mass balance) model indicate that emissions from motor vehicle exhausts are the most important, accounting for the 64 % of the PM_2.5, followed by meat-cooking operations with 31 % The vegetative detritus and biomass burning had the smallest contribution (2.2 % of the PM_2.5). To our knowledge, this is only the second study to explore the organic composition and source apportionment of fine organic aerosol based on molecular markers in Mexico and the first for the MMA. Particularly molecular marker were quantified by solvent extraction with dichloromethane, derivatization, and gas chromatography with mass spectrometry (GC/MS).

The posterior parietal cortex (PPC) is thought to play an important role in the planning of visually-guided reaching movements. However, the relative roles of the various subdivisions of the PPC in this function are still poorly understood. For example, studies of dorsal area 5 point to a representation of reaches in both extrinsic (endpoint) and intrinsic (joint or muscle) coordinates, as evidenced by partial changes in preferred directions and positional discharge with changes in arm posture. In contrast, recent findings suggest that the adjacent medial intraparietal area (MIP) is involved in more abstract representations, e.g., encoding reach target in visual coordinates. Such a representation is suitable for planning reach trajectories involving shortest distance paths to targets straight ahead. However, it is currently unclear how MIP contributes to the planning of other types of trajectories, including those with various degrees of curvature. Such curved trajectories recruit different joint excursions and might help us address whether their representation in the PPC is purely in extrinsic coordinates or in intrinsic ones as well. Here we investigated the role of the PPC in these processes during an obstacle avoidance task for which the animals had not been explicitly trained. We found that PPC planning activity was predictive of both the spatial and temporal aspects of upcoming trajectories. The same PPC neurons predicted the upcoming trajectory in both endpoint and joint coordinates. The predictive power of these neurons remained stable and accurate despite concomitant motor learning across task conditions. These findings suggest the role of the PPC can be extended from specifying abstract movement goals to expressing these plans as corresponding trajectories in both endpoint and joint coordinates. Thus, the PPC appears to contribute to reach planning and approach-avoidance arm motions at multiple levels of representation.

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

Nanomaterials enabled technologies have been seamlessly integrated into applications such as aviation and space, chemical industry, optics, solar hydrogen, fuel cell, batteries, sensors, power generation, aeronautic industry, building/construction industry, automotive engineering, consumer electronics, thermoelectric devices, pharmaceuticals, and cosmetic industry. Clean energy and environmental applications often demand the development of novel nanomaterials that can provide shortest reaction pathways for the enhancement of reaction kinetics. Understanding the physicochemical, structural, microstructural, surface, and interface properties of nanomaterials is vital for achieving the required efficiency, cycle life, and sustainability in various technological applications. Nanomaterials with specific size and shape such as nanotubes, nanofibers, nanowires, nanocones, nanocomposites, nanorods, nanoislands, nanoparticles, nanospheres, and nanoshells to provide unique properties can be synthesized by tuning the process conditions.

Urban water systems face sustainability and resiliency challenges including water leaks, over-use, quality issues, and response to drought and natural disasters. Information and communications technology (ICT) could help address these challenges through the development of smart water grids that network and automate monitoring and control devices. While progress is being made on technology elements, as a system, the smart water grid has received scant attention. This article aims to raise awareness of the systems-level idea of smart water grids by reviewing the technology elements and their integration into smart water systems, discussing potential sustainability and resiliency benefits, and challenges relating to the adoption of smart water grids. Water losses and inefficient use stand out as promising areas for applications of smart water grids. Potential barriers to the adoption of smart water grids include lack of funding for research and development, economic disincentives as well as institutional and political structures that favor the current system. It is our hope that future work can clarify the benefits of smart water grids and address challenges to their further development.

Every year, flood disasters are responsible for widespread destruction and loss of human life. Remote sensing data are capable of providing valuable, synoptic coverage of flood events but are not always available because of satellite revisit limitations, obstructions from cloud cover or vegetation canopy, or expense. In addition, knowledge of road accessibility is imperative during all phases of a flood event. In June 2013, the City of Calgary experienced sudden and extensive flooding but lacked comprehensive remote sensing coverage. Using this event as a case study, this work illustrates how data from non-authoritative sources are used to augment traditional data and methods to estimate flood extent and identify affected roads during a flood disaster. The application of these data, which may have varying resolutions and uncertainities, provide an estimation of flood extent when traditional data and methods are lacking or incomplete. When flooding occurs over multiple days, it is possible to construct an estimate of the advancement and recession of the flood event. Non-authoritative sources also provide flood information at the micro-level, which can be difficult to capture from remote sensing data; however, the distibution and quantity of data collected from these sources will affect the quality of the flood estimations.