Publications

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The magnetoresistance, R{sub xx}, at even-denominator fractional fillings, of an ultra high quality two-dimensional electron system at T {approx} 35 mK is observed to be strictly linear in magnetic field, B. While at 35 mK R{sub xx} is dominated by the integer and fractional quantum Hall states, at T {approx_equal} 1.2 K an almost perfect linear relationship between R{sub xx} and B emerges over the whole magnetic field range except for spikes at the integer quantum Hall states. This linear R{sub xx} cannot be understood within the Composite Fermion model, but can be explained through the existence of a density gradient in our sample.

We report on our studies of the structural properties of a hydrogen molecule dissolved in liquid water. The radial distribution function, coordination number and coordination number distribution are calculated using different representations of the interatomic forces within molecular dynamics (MD), Monte Carlo (MC) and ab initio molecular dynamics (AIMD) simulation frameworks. Although structural details differ in the radial distribution functions generated from the different force fields, all approaches agree that the average and most probable number of water molecules occupying the inner hydration sphere around hydrogen is 16. Furthermore, all results exclude the possibility of clathrate-like organization of water molecules around the hydrophobic molecular hydrogen solute.

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Strategies and decisions to protect emergency responders, the public, and critical infrastructure against the effects of a radiological dispersal device detonated outdoors must be made in the planning stage, not in the early period just after an attack. This contrasts with planning for small-scale types of radiological or nuclear emergencies, or for a large-scale nuclear-power-type accident that evolves over many hours or days before radioactivity is released to the environment, such that its effects can be prospectively modeled and analyzed. By the time it is known an attack has occurred, most likely there will have been casualties, all the radioactive material will have been released, plume growth will be progressing, and there will be no time left for evaluating possible countermeasures. This paper offers guidance to planners, first responders, and senior decision makers to assist them in developing strategies for protective actions and operational procedures for the first 48 hours after an explosive radiological dispersal device has been detonated.

Structured adaptive mesh refinement methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioner's ability to efficiently use the underlying parallel computer's resources. Designed on sound SAMR principles, Nature+Fable is a hybrid, dedicated SAMR partitioning tool that brings together the advantages of both domain-based and patch-based techniques while avoiding their drawbacks. But the original bi-level partitioning approach in Nature+Fable is insufficient as it for realistic applications regards frequently occurring bi-levels as 'impossible' and fails. This document describes an improved bi-level partitioning algorithm that successfully copes with all possible hi-levels. The improved algorithm uses the original approach side-by-side with a new, complementing approach. By using a new, customized classification method, the improved algorithm switches automatically between the two approaches. This document describes the algorithms, discusses implementation issues, and presents experimental results. The improved version of Nature+Fable was found to be able to handle realistic applications and also to generate less imbalances, similar box count, but more communication as compared to the native, domain-based partitioner in the SAMR framework AMROC.

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Multiwall carbon nanotubes are grown via thermal chemical vapor deposition between temperatures of 630 and 830 C using acetylene in nitrogen as the carbon source. This process is modeled using classical thermodynamics to explain the total carbon deposition as a function of time and temperature. An activation energy of 1.60 eV is inferred for nanotube growth after considering the carbon solubility term. Scanning electron microscopy shows growth with diameters increasing linearly with time. Transmission electron microscopy and Raman spectroscopy show multiwall nanotubes surrounded by a glassy-carbon sheath, which grows with increasing wall thickness as growth temperatures and times rise.

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We present results from a hybrid simulation and integral equation approach to the calculation of polymer melt properties. The simulation consists of explicit Monte Carlo (MC) sampling of two polymer molecules, where the effect of the surrounding chains is accounted for by an HNC solvation potential. The solvation potential is determined from the Polymer Reference Interaction Site Model (PRISM) as a functional of the pair correlation function from simulation. This hybrid two-chain MC-PRISM approach was carried out on liquids of polyethylene chains of 24 and 66 CH{sub 2} units. The results are compared with MD simulation and self-consistent PRISM-PY theory under the same conditions, revealing that the two-chain calculation is close to MD, and able to overcome the defects of the PRISM-PY closure and predict more accurate structures of the liquid at both short and long range. The direct correlation function, for instance, has a tail at longer range which is consistent with MD simulation and avoids the short-range assumptions in PRISM-PY theory. As a result, the self-consistent two-chain MC-PRISM calculation predicts an isothermal compressibility closer to the MD results.

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Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

A 100-GW optical parametric chirped-pulse amplifier system is used to study nonlinear effects in the 1.54 {micro}m regime. When focusing this beam in air, strong third-harmonic generation (THG) is observed, and both the spectra and efficiency are measured. Broadening is observed on only the blue side of the third-harmonic signal and an energy conversion efficiency of 0.2% is achieved. When propagated through a 10-cm block of fused silica, a collimated beam is seen to collapse and form multiple filaments. The measured spectral features span 400-2100 nm. The spectrum is dominated by previously unobserved Stokes emissions and broad emissions in the visible.

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