Comparing Infrared Star-Formation Rate Indicators with Optically-Derived Quantities

We examine the UV reprocessing efficiencies of warm dust and polycyclic aromatic hydrocarbons (PAHs) through an analysis of the mid- and far-infrared surface luminosity densities of 85 nearby H$\alpha$-selected star-forming galaxies detected by the volume-limited KPNO International Spectroscopic Survey (KISS). Because H$\alpha$ selection is not biased toward continuum-bright objects, the KISS sample spans a wide range in stellar masses ($10^8$-$10^{12}\rm{M}_\odot$), as well as H$\alpha$ luminosity ($10^{39}$-$10^{43}\rm{ergs/s}$), mid-infrared 8.0$\mu$m luminosity ($10^{41}$-$10^{44}\rm{ergs/s}$), and [Bw-R] color (-.1-2.2). We find that mid-infrared polycyclic aromatic hydrocarbon (PAH) emission in the Spitzer IRAC 8.0$\mu$m band correlates with star formation, and that the efficiency with which galaxies reprocess UV energy into PAH emission depends on metallicity. We also find that the relationship between far-infrared luminosity in the Spitzer MIPS 24$\mu$m band pass and H$\alpha$-measured star-formation rate varies from galaxy to galaxy within our sample; we do not observe a metallicity dependence in this relationship. We use optical colors and established mass-to-light relationships to determine stellar masses for the KISS galaxies; we compare these masses to those of nearby galaxies as a confirmation that the volume-limited nature of KISS avoids strong biases. We also examine the relationship between IRAC 3.6$\mu$m luminosity and galaxy stellar mass, and find a color-dependent correlation between the two.Comment: 15 pages, 10 figure

Enabling III-V-based optoelectronics with low-cost dynamic hydride vapor phase epitaxy

Silicon is the dominant semiconductor in many semiconductor device applications for a variety of reasons, including both performance and cost. III-V materials have improved performance compared to silicon, but currently they are relegated to applications in high-value or niche markets due to the absence of a low-cost, high-quality production technique. Here we present an advance in III-V materials synthesis using hydride vapor phase epitaxy that has the potential to lower III-V semiconductor deposition costs by orders of magnitude while maintaining the requisite optoelectronic material quality that enables III-V-based technologies to outperform Si. We demonstrate the impacts of this advance by addressing the use of III-Vs in terrestrial photovoltaics, a highly cost-constrained market. The emergence of a low-cost III-V deposition technique will enable III-V electronic and opto-electronic devices, with all the benefits that they bring, to permeate throughout modern society.Comment: pre-prin

Fabrication of Multilayered Structure for Coherent Random Lasing

High powered lasers have many applications, including medical treatment and surgery. However, these lasers are extremely expensive and are therefore not widely available. The aim of this study was to demonstrate a method to create such a laser with significantly decreased overall cost and increased efficiency. In order to do this, we explored a phenomenon called random lasing which is a light amplification process. To start with, a low-cost pumping laser is directed at normal incidence toward a multi-layered sample with two alternating layers. At first pearl, a naturally found material that has many organic nano-scale layers (similar to the wavelength of visible light) was utilized and later fabricated using a spin coating technique. For the fabrication, two polymers, SU-8 with Rhodamine 6G (a fluorescent laser dye) and PMMA, were tested at different concentrations and spin coating speeds. It was necessary dissolve both polymers in a solvent so toluene composed about 25% of each solution. The spin coating speeds ranged from 1500 to 3000 rpm for both polymers to achieve layers approximately 500 nm thick. After the fabrication process, the pumping laser was directed at normal incidence onto the sample which increased the noise level and subsequently increased the degree of light localization. Light localization increases the amplification of the pumping laser and non-uniformity of the alternating layers increases this effect. Therefore, the lasing threshold was decreased which increases the lasers efficiency

Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network

The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–20 3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea