Alien Registration- Murphy, John E. (Drew Plantation, Aroostook County)

https://digitalmaine.com/alien_docs/32547/thumbnail.jp

Sub-2 cm/s passivation of silicon surfaces by aprotic solutions

Minimizing recombination at semiconductor surfaces is required for the accurate determination of the bulk carrier lifetime. Proton donors, such as hydrofluoric acid and superacids, are well known to provide highly effective short-term surface passivation. We demonstrate here that aprotic solutions based on bis(trifluoromethanesulfonyl)methane (TFSM) in hexane or pentane can also result in excellent passivation of (100)-orientation silicon surfaces. We show that the optimized TFSM-pentane passivation scheme can measure effective lifetimes up to 20 ms, with a surface recombination velocity of 1.7 cm s1 at an excess carrier density of 1015 cm3 . Fitting injection-dependent lifetime curves requires chemical passivation and field effect passivation from a negatively charged layer with a charge density of 1010–1011 q cm2 . The slightly higher recombination velocity of 2.3 cm s1 measured with TFSM-hexane can be explained by a lower charge density in the passivating layer, suggesting that the steric hindrance associated with the solvent size could play a role in the passivation mechanism. Finally, phosphorus nuclear magnetic resonance experiments confirm that TFSM-based solutions have Lewis acidity without being superacids, which opens up opportunities for them to be used in materials systems sensitive to superacidic environments

A Generalized Theory of Varying Alpha

In this paper, we formulate a generalization of the simple Bekenstein-Sandvik-Barrow-Magueijo (BSBM) theory of varying alpha by allowing the coupling constant, \omega, for the corresponding scalar field \psi\ to depend on \psi. We focus on the situation where \omega\ is exponential in \psi\ and find the late-time behaviours that occur in matter-dominated and dark-energy dominated cosmologies. We also consider the situation when the background expansion scale factor of the universe evolves in proportion to an arbitrary power of the cosmic time. We find the conditions under which the fine structure `constant' increases with time, as in the BSBM theory, and establish a cosmic no-hair behaviour for accelerating universes. We also find the conditions under which the fine structure `constant' can decrease with time and compare the whole family of models with astronomical data from quasar absorption spectra.Comment: 25 pages, 6 figures. Minor corrections and clarifications added. Final section on spatial variations removed so that the paper focuses exclusively on time-variatio

Developing Machine Learning Models for Space Based Edge AI Platforms

On September 3rd 2020, one of the first small satellites equipped with Edge AI hardware was launched. The inclusion of a UB0100 board on PhiSat-1 enabled the use of deep neural networks to provide real-time image analysis on-board an Earth Observation satellite. The primary benefit of this was a 90% reduction in downlink data as the system only transmitted non-cloudy, and thus usable, data. PhiSat-1 and missions like it have started the revolution of satellite-based machine learning, leading ESA and other space agencies to further explore the in-situ deployment of machine-learning models. Other applications that can benefit from on-board space-based machine learning capabilities range from anomaly detection and prognostics to feature recognition and object detection. This paper focuses on the application of anomaly detection models on space-ready Edge AI hardware to detect and classify anomalous behaviour in telemetry data. The ability to accurately detect anomalies onboard satellite systems has the potential to both increase system lifetimes and reduce satellite operator workloads. The limitations of Edge AI boards and the space environment put restrictions on the models that can be used. Limited power and potential single event upsets constrain the complexity of the models that can be deployed. Therefore, this paper is targeted at models that will run efficiently within these constraints. We describe an experiment that evaluates the suitability of different anomaly detection approaches (multi-layer-perceptrons, auto-encoders, etc.) for space applications. These approaches are compared both in terms of their performance in the anomaly detection tasks and how well they run on “space ready” low-power hardware. We focus on the Intel Myriad chipset, the basis of the UB0100, which hosted the machine learning image analysis model on PhiSat-1. Our evaluations use both the MIMII machine audio dataset, a well-regarded anomaly detection dataset that is a good proxy for telemetry data, and a dataset generated using anonymized NASA mission telemetry data. The findings show how well basic models work when presented with anomalous satellite telemetry

Low-Power Boards Enabling ML-Based Approaches to FDIR in Space-Based Applications

Modern satellite complexity is increasing, thus requiring bespoke and expensive on-board solutions to provide a Failure Detection, Isolation and Recovery (FDIR) function. Although FDIR is vital in ensuring the safety, autonomy, and availability of satellite systems in flight, there is a clear need in the space industry for a more adaptable, scalable, and cost-effective solution. This paper explores the current state of the art for Machine Learning error detection and prognostic algorithms utilized by both the space sector and the commercial sector. Although work has previously been done in the commercial sector on error detection and prognostics, most commercial applications are not nearly as limited by the power, mass, and radiation tolerance constraints as for operation in a space environment. Therefore, this paper also discusses several Commercial Off-The-Shelf (COTS) multi-core micro-processors, small-footprint boards that will be explored as possible testbeds for future integration into a satellite in-orbit demonstrator

The MASSIVE Survey II: Stellar Population Trends Out to Large Radius in Massive Early Type Galaxies

We examine stellar population gradients in ~100 massive early type galaxies spanning 180 < sigma* < 370 km/s and M_K of -22.5 to -26.5 mag, observed as part of the MASSIVE survey (Ma et al. 2014). Using integral-field spectroscopy from the Mitchell Spectrograph on the 2.7m telescope at McDonald Observatory, we create stacked spectra as a function of radius for galaxies binned by their stellar velocity dispersion, stellar mass, and group richness. With excellent sampling at the highest stellar mass, we examine radial trends in stellar population properties extending to beyond twice the effective radius (~2.5 R_e). Specifically, we examine trends in age, metallicity, and abundance ratios of Mg, C, N, and Ca, and discuss the implications for star formation histories and elemental yields. At a fixed physical radius of 3-6 kpc (the likely size of the galaxy cores formed at high redshift) stellar age and [alpha/Fe] increase with increasing sigma* and depend only weakly on stellar mass, as we might expect if denser galaxies form their central cores earlier and faster. If we instead focus on 1-1.5 R_e, the trends in abundance and abundance ratio are washed out, as might be expected if the stars at large radius were accreted by smaller galaxies. Finally, we show that when controlling for \sigmastar, there are only very subtle differences in stellar population properties or gradients as a function of group richness; even at large radius internal properties matter more than environment in determining star formation history.Comment: 17 pages, 9 figures, accepted by ApJ; resubmitted with updated reference

The MASSIVE Survey - I. A Volume-Limited Integral-Field Spectroscopic Study of the Most Massive Early-Type Galaxies within 108 Mpc

Massive early-type galaxies represent the modern-day remnants of the earliest major star formation episodes in the history of the universe. These galaxies are central to our understanding of the evolution of cosmic structure, stellar populations, and supermassive black holes, but the details of their complex formation histories remain uncertain. To address this situation, we have initiated the MASSIVE Survey, a volume-limited, multi-wavelength, integral-field spectroscopic (IFS) and photometric survey of the structure and dynamics of the ~100 most massive early-type galaxies within a distance of 108 Mpc. This survey probes a stellar mass range M* > 10^{11.5} Msun and diverse galaxy environments that have not been systematically studied to date. Our wide-field IFS data cover about two effective radii of individual galaxies, and for a subset of them, we are acquiring additional IFS observations on sub-arcsecond scales with adaptive optics. We are also acquiring deep K-band imaging to trace the extended halos of the galaxies and measure accurate total magnitudes. Dynamical orbit modeling of the combined data will allow us to simultaneously determine the stellar, black hole, and dark matter halo masses. The primary goals of the project are to constrain the black hole scaling relations at high masses, investigate systematically the stellar initial mass function and dark matter distribution in massive galaxies, and probe the late-time assembly of ellipticals through stellar population and kinematical gradients. In this paper, we describe the MASSIVE sample selection, discuss the distinct demographics and structural and environmental properties of the selected galaxies, and provide an overview of our basic observational program, science goals and early survey results.Comment: 19 pages, 14 figures. ApJ (2014) vol. 795, in pres

Low-temperature saw damage gettering to improve minority carrier lifetime in multicrystalline silicon

The minority carrier lifetime in multicrystalline silicon − a material used in the majority of today's manufactured solar cells − is limited by defects within the material, including metallic impurities which are relatively mobile at low temperatures (≤700 °C). Addition of an optimised thermal process which can facilitate impurity diffusion to the saw damage at the wafer surfaces can result in permanent removal of the impurities when the saw damage is etched away. We demonstrate that this saw damage gettering is effective at 500 to 700 °C and, when combined with subsequent low-temperature processing, lifetimes are improved by a factor of more than four relative to the as-grown state. The simple method has the potential to be a low thermal budget process for the improvement of low-lifetime “red zone” wafers

Research Experiences and Research‐Related Coursework in the Education of Doctors of Pharmacy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90119/1/phco.19.3.213.30931.pd

A Group of Consumers Who Have Bought Merchandise under Installment Contracts May Maintain a Class Action Seeking Recission of the Contracts for Fraudulent Misrepresentations on Behalf of Themselves and Others Similarly Situated.

Abstract Forthcoming