DRUM Community: Chemistry & Biochemistry
http://hdl.handle.net/1903/11812
2015-04-19T04:35:46ZStructural Changes and the Nature of Superconductivity in Rare-earth Doped CaFe2As2
http://hdl.handle.net/1903/16255
Title: Structural Changes and the Nature of Superconductivity in Rare-earth Doped CaFe2As2
Authors: Drye, Tyler Brunson
Abstract: Chemical substitution into iron-pnictide parent compounds (e.g. AFe<sub>2<\sub>As<sub>2<\sub> where A=Ba, Sr, or Ca) has proven to be an effective means to induce bulk high-temperature superconductivity in these systems. By doping CaFe<sub>2<\sub>As<sub>2<\sub> with rare-earth lanthanides (La, Ce, Pr, and Nd), we have observed a 47 K superconducting phase coexisting with a lattice distorting “collapse” transition. Both of these effects have important ramifications: the collapse transition occurs when interlayer As atoms form a bond, shrinking the <italic>c-axis<\italic> lattice constant and simultaneously quenching the iron magnetic moment. This transition is further explored in context of a similar system, Sr-doped BaNi<sub>2<\sub>As<sub>2<\sub>. The superconducting phase, given the right combination of conditions, appears with a critical temperature as high as 49 K, but always in a very small volume of the sample (as determined by shielding effects). This has led to interesting theories about the nature of this superconductivity. A recently posited idea of “interfacial superconductivity” has been ruled out by our tests. Additionally, increasing the concentration of rare-earth atoms does not increase the superconducting volume fraction, but, in fact lowers the transition temperature, excluding the hypothesis that rare-earth defects are responsible for the minority superconducting phase. New pressure measurements have shown that the superconducting phase is stabilized when antiferromagnetic order is fully suppressed.2014-01-01T00:00:00ZDevelopment, enhancement, and evaluation of aircraft measurement techniques for criteria pollutants
http://hdl.handle.net/1903/16213
Title: Development, enhancement, and evaluation of aircraft measurement techniques for criteria pollutants
Authors: Brent, Lacey Cluff
Abstract: The atmospheric contaminants most harmful to human health are designated Criteria Pollutants. To help Maryland attain the national ambient air quality standards (NAAQS) for Criteria Pollutants, and to improve our fundamental understanding of atmospheric chemistry, I conducted aircraft measurements in the Regional Atmospheric Measurement Modeling Prediction Program (RAMMPP). These data are used to evaluate model simulations and satellite observations. I developed techniques for improving airborne observation of two NAAQS pollutants, particulate matter (PM) and nitrogen dioxide (NO2). While structure and composition of organic aerosol are important for understanding PM formation, the molecular speciation of organic ambient aerosol remains largely unknown. The spatial distribution of reactive nitrogen is likewise poorly constrained. To examine water-soluble organic aerosol (WSOA) during an air pollution episode, I designed and implemented a shrouded aerosol inlet system to collect PM onto quartz fiber filters from a Cessna 402 research aircraft. Inlet evaluation conducted during a side-by-side flight with the NASA P3 demonstrated agreement to within 30%. An ion chromatographic mass spectrometric method developed using the NIST Standard Reference Material (SRM) 1649b Urban Dust, as a surrogate material resulted in acidic class separation and resolution of at least 34 organic acids; detection limits approach pg/g concentrations. Analysis of aircraft filter samples resulted in detection of 8 inorganic species and 16 organic acids of which 12 were quantified. Aged, re-circulated metropolitan air showed a greater number of dicarboxylic acids compared to air recently transported from the west. While the NAAQS for NO2 is rarely exceeded, it is a precursor molecule for ozone, America's most recalcitrant pollutant. Using cavity ringdown spectroscopy employing a light emitting diode (LED), I measured vertical profiles of NO¬2 (surface to 2.5 km) west (upwind) of the Baltimore/Washington, area in the morning, and east (downwind) in the afternoon. Column contents (altitude integrals of concentration) were remarkably similar (≈3x1015 molecules cm−2). These measurements indicate that NO2 is widely distributed over the eastern US and help quantify the regional nature of smog events and prove extensive interstate transport of pollutants. These results were used to help shape air pollution control policy based on solid science.2014-01-01T00:00:00ZAPPLICATION OF FLUCTUATION ANALYSIS TO CHARACTERIZE MULTI-SCALE NATURE AND PREDICTABILITY OF COMPLEX SYSTEMS
http://hdl.handle.net/1903/16211
Title: APPLICATION OF FLUCTUATION ANALYSIS TO CHARACTERIZE MULTI-SCALE NATURE AND PREDICTABILITY OF COMPLEX SYSTEMS
Authors: Setty, Venkat Anurag
Abstract: Complexity is a result of interactions among individual components of a distributed
system, each with their own dynamical time scale. Statistical techniques
such as fluctuation analysis are used to quantify extent of long range correlations
within time series data by estimating a scaling exponent commonly known as Hurst
exponent. Data from magnetospheric dynamics, physiology and finance are known
to show multi-exponent nature (two exponents in particular) in their fluctuation
analysis with a crossover between the power laws. This correlation crossover can be seen due to the statistical approach taken in the analysis of a range of systems with differing dynamical time scales, particularly due to the nature of interactions with one another. We refer to this property as multi-scale nature in the time series data from complex systems. The main contributions of the thesis are as follows:
Study of crossover in fluctuation analysis of data from magnetosphere, physiology and finance:
We propose an innovative regression scheme, whose mathematical model well describes two exponent nature with an intermediate crossover regime seen in fluctuation analysis - the Hyperbolic regression. Slopes of the asymptotes of the hyperbola are the Hurst exponents, and, center of the resulting hyperbolic fit is an estimate of the correlation crossover time. It is key to note that in this regression, there are no assumptions made about the crossover time, unlike previous approach to crossover fitting. Different data sets corresponding to different
physical processes demonstrate multi-scale nature. However, each data presents
a unique challenge to be addressed, as a result of characterization of its scaling
crossover. Application of hyperbolic regression on the crossover seen in fluctuation
analysis of auroral electrojet index data from magnetosphere resulted in estimation
of Hurst exponents before and after the crossover. Also, the correlation crossover
time scale is now measured by improved modeling of such data using a stochastic
model that demonstrates crossover in fluctuation functions - the OU-Langevin
model. Characterization of nature of crossover seen in fluctuation analysis of generalized volatility within financial index data has shown differing nature of financial markets. Such a study would help characterize individual markets utilizing features which were not used previously. Heart rate variability data from healthy patients and patients with congestive heart failure demonstrate differing extent of crossover within the crossover seen in fluctuation functions. This resulted in proposal of a parameter i.e., the extent of crossover parameter that can be used to distinguish patients with the congestive heart failure ailment from normal cases.
Quantifying predictability of complex systems using Hurst exponents:
Predictability of complex systems suffers due to noise in the data. Long range correlations in noise are seen to cause extreme events or build ups leading to
extreme events in such data. The increased probability of extreme event occurrence makes prediction of resulting time series data difficult. Tail exponent is an exponent resulting out of power laws seen in heavy tailed distributions and is used as a measure of the probability of extreme events in such data. The Hurst exponent which measures the extent of long range correlations using fluctuation analysis has a known relationship with the tail exponent through Taqqu's theorem. Fluctuation analysis of time series data is oftentimes complicated due to existence of trends in the time series data. Dynamical features in data commonly reflect as trends, and, as a result nonlinear dynamical time series prediction techniques can be used to measure these trends. We refer to this method as Fluctuation Analysis after Trend Elimination (FATE) and apply it to data from space weather and finance. Hurst exponent estimated from FATE and its relationship with tail exponent measured by a commonly used Hill estimator technique are shown. Insufficient data sizes limit our ability to robustly estimate the tail exponent from observational data as extreme events are usually rare. This forms the motivation to use Hurst exponent obtained from FATE as a measure of predictability of complex systems demonstrated by application on auroral electrojet index data. Conversely, Hurst exponent can be used to quantify the ability of a technique to predict time series data as demonstrated by application of FATE.2014-01-01T00:00:00ZA TEMPERATURE-CONTROLLED ELECTROCHEMICAL MICROSCALE PLATFORM FOR BIOMOLEMULAR BINDING STUDIES
http://hdl.handle.net/1903/16192
Title: A TEMPERATURE-CONTROLLED ELECTROCHEMICAL MICROSCALE PLATFORM FOR BIOMOLEMULAR BINDING STUDIES
Authors: Shen, Zuliang
Abstract: Electrochemical detection of nucleic acids has been a very important research area in the past several decades. In this research field, the stability of the nucleic acid structure is important and crucial for many aspects of nucleic acid metabolism. Also the binding of small molecule ligands to nucleic acids and resulting increase in stability of the nucleic acids can play a key role in many context including DNA-targeted therapy against various cancers, bacteria or viruses. Melting curve analysis using electrochemical detection, as a new method to characterize nucleic acids' stability and interactions between small molecules, provides high sensitivity and is also well suited for high-throughput formats. This thesis describes efforts to develop melting curve analysis using electrochemical detection method on a temperature-controlled microscale platform.2014-01-01T00:00:00Z