Wolf-Rayet stars are massive stars whose high-intensity ultraviolet radiation drives a strong stellar wind, effectively pushing away its outer layers. This process forms an optically thick nebula around the star, making it difficult to obtain high-precision observations of the surface of the star. However, precise observations of the star’s brightness over time could reveal a large amount of information about the behavior of these stars beneath their winds. Our group has obtained high-cadence photometric data from Apache Point Observatory’s ARCTIC camera to construct figures of brightness vs. time (known as a lightcurves) for the Wolf-Rayet star WR124 to search for periodic changes is the star’s brightness. We developed code which reduces and processes images of WR124, extracts the brightness of WR124 in each image, eliminates systematic trends in data, and compiles each data point into a lightcurve. This processing has shown that WR124 exhibits variability, a change in brightness over time. We also search for signals which repeat with a regular period using a hybrid periodogram analysis. Although this periodogram analysis has proven inconclusive, planned future observations of WR124 and more advanced statistical analysis techniques may still yield important results in the study of these interesting objects.

As the Kepler Space Telescope's follow-up K2 mission enters its final campaigns of observation, the fuel powering the spacecraft's stabilizing thrusters is expected to begin to run out, causing thruster fires to sputter. Sputtering will cause higher magnitude and less predictable motion of stellar Point Spread Functions (PSFs) relative to the spacecraft detector, generating more noise in transiting exoplanet light curves. To understand this increased noise, I am creating a forward model of the Kepler detector, and simulating stellar targets traversing different regions of quantum sensitivity variation. Using these simulations, I am characterizing the contribution of detector sensitivity variation to the noise of K2 light curves and testing various models for thruster sputtering in preparation for identifying high motion in future K2 data. I am also testing methods to increase the effectiveness of existing noise-removal techniques for space telescope exoplanet targets, focusing my treatment on stars with bright neighbors or high motion relative to the detector. Using techniques tested on simulations, I am studying a population of exoplanet targets that has received less attention due to difficulties arising from contribution by bright nearby stars. In this talk I will demonstrate the potential value in continued observation during thruster sputtering and discuss the results of my follow-up study on crowded exoplanet targets. To ensure a productive legacy for the Kepler mission, it is essential to develop robust tools to analyze existing data after the spacecraft becomes defunct. My noise-removal methods can be applied to current and future K2 data, as well as data from future missions such as the Transiting Exoplanet Survey Satellite (TESS) and the James Webb Space Telescope (JWST).

Werk Student Quasar Absorption Disgnostisions (Werk SQuAD), a group of undergraduate students led by astronomy professor Jessica Werk, aims to assemble a database of identified absorption features present in 230 nearby quasars. The purpose of this database is to provide astronomers studying galaxy evolution more information about the circumgalactic medium (CGM) of galaxies. The CGM is a giant halo of matter gravitationally bound to dark matter surrounding a galaxy, acting as a recycling hub for galactic outflows and accreting material. A major limitation to observing the CGM is that it is so diffuse, it is impossible to observe directly via emission. In order to learn more about the CGM, we must rely on other light sources. As light is emitted from a background quasar, the light passes through the CGM of galaxies in its line of sight as it travels to us in the Milky Way. Every CGM the light passes through leaves a sort of fingerprint, as ions from the CGM absorb some of the original light from the quasar, leaving trenches in the data. By figuring out where those absorptions happened and what ions were present, we can gain insight into what systems of gas were encountered on the quasar’s journey to us. With the use of a specialized GUI, we are able to search for ion absorption features in the spectrum. We look for recognizable signatures such as the Hydrogen Lyman series, while checking for other ion absorbers as well. When there are multiple absorbers at a particular redshift, this is often an indication that we are viewing part of a nearby galaxy’s CGM. By identifying these absorptions and linking them to particular galaxies, we are able to better understand the cycle of galaxy evolution.

Polymer based fullerenes are used as photovoltaics in solar panels. Fullerene C60 molecules have icosahedral based structures resembling geodesic domes. Fullerenes have convex polyhedral shapes which obey Euler’s topological rules. Their novel structures involve Golden ratios. Here we use vector calculus methods to calculate bond lengths and bond angles and provide estimates for the volume and surface area of the molecule. The calculated average bond length (1.4320 Å), edge length (2.4252 Å), bond angle (116o) are in good agreement with reported experiments. The estimated fullerene molecularvolume is 788 Å3 and surface area is 426 Å2. To understand the critical effect of dimensionality on volume, we have studied the volume of a hypersphere in n-dimensions. The project provides hands on exploration of real world problems and data visualization.

Photovoltaic (PV) electricity generation has become much cheaper in recent years and as a result is becoming a larger percentage of total energy production. However, growth is limited due to the high capital expenditure (CAPEX) required to build new PV factories with current technologies. Solution processing techniques (spray coating, roll-to-roll, etc.) to deposit thin-film absorber materials such as CuIn(S,Se)₂ and Cu(In,Ga)(S,Se)₂ represent a much lower CAPEX alternative to current PV processes. Using simple metal chloride precursor salts dissolved in polar aprotic solvents, our group has shown solar power conversion efficiencies of 13.4%, which is a world-record for solution processed CIS. Understanding the complexation chemistry of precursor salts in solution is essential to making stable solutions which produce homogeneous absorber layers after thermal annealing. Using solubility experiments and calorimetry to examine interactions between the precursors in anhydrous dimethylformamide (DMF), we were able to infer participating molecules and stoichiometry of the complexes formed in solution between the metal chlorides, thiourea, and solvent molecules. We have also made CIS absorbers under various thermal annealing conditions, and studied the resulting changes in 1) elemental composition profiles using glow-discharge optical emission spectroscopy (GDOES) and energy-dispersive X-ray spectroscopy (EDX) and 2) film morphology using scanning electron microscopy (SEM). These results represent steps forward in improving solution processing techniques for low CAPEX solar cell manufacturing which will increase the prevalence of renewable energy to combat global warming.

Silica nanoparticles are extensively used in semi-conductor industry as abrasives in various polishing steps. It is important to be able to conduct rapid, robust surface area measurements of the dispersion that do not require dilution and drying. The focus of this research is to explore nuclear magnetic resonance (NMR) technique as a means for determining surface area of silica nanoparticles and its sensitivity to temperature and trace level contamination. NMR is a technique that can be used for determining the surface area of silica particles in dilute and concentrated solutions. After application of large magnetic field, water protons in the vicinity of nanoparticles relax faster than protons in the bulk liquid. Thus, the average relaxation rate of the sample is proportional to the particle loading, particle surface area, and a proportionality constant, specific surface relaxivity, that is unique for different materials. Silica nanoparticles of sub 100 nm size are studied. Specific surface relaxivities for the materials are found and the effect of various contaminants active in NMR are studied. The lowest limits of detection for possible industrial contaminants are obtained. The interaction of surfactants with silica particle surface are studied using NMR technique. The gelation process of silica nanoparticles and its relationship with relaxation time is investigated by time-resolved dynamic light scattering (DLS) and NMR. Only recently has NMR become available as a bench-top instrument targeting widespread adoption for process control and monitoring. This study advances the knowledge on the various ways this relatively new technique can be applied to the characterization of sub-100 nm silica particles, what is useful for semi-conductor industry and nanoparticle slurry manufacturers.