First-principles quantum simulations of dissociation of molecular condensates: Atom correlations in momentum space

We investigate the quantum many-body dynamics of dissociation of a Bose-Einstein condensate of molecular dimers into pairs of constituent bosonic atoms and analyze the resulting atom-atom correlations. The quantum fields of both the molecules and atoms are simulated from first principles in three dimensions using the positive-P representation method. This allows us to provide an exact treatment of the molecular field depletion and s-wave scattering interactions between the particles, as well as to extend the analysis to nonuniform systems. In the simplest uniform case, we find that the major source of atom-atom decorrelation is atom-atom recombination which produces molecules outside the initially occupied condensate mode. The unwanted molecules are formed from dissociated atom pairs with nonopposite momenta. The net effect of this process-which becomes increasingly significant for dissociation durations corresponding to more than about 40% conversion-is to reduce the atom-atom correlations. In addition, for nonuniform systems we find that mode mixing due to inhomogeneity can result in further degradation of the correlation signal. We characterize the correlation strength via the degree of squeezing of particle number-difference fluctuations in a certain momentum-space volume and show that the correlation strength can be increased if the signals are binned into larger counting volumes.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

Determination of muscle fatigue in clinical practices using dynamically embedded signals

This paper explores a new method of analysing muscle fatigue within the muscles predominantly used during microsurgery. The captured electromyographic (EMG) data retrieved from these muscles are analysed for any defining patterns relating to muscle fatigue. The analysis consists of dynamically embedding the EMG signals from a single muscle channel into an embedded matrix. The muscle fatigue is determined by defining its entropy characterized by the singular values of the dynamically embedded (DE) matrix. The paper compares this new method with the traditional method of using mean frequency shifts in the EMG signal's power spectral density. Linear regressions are fitted to the results from both methods, and the coefficients of variation of both their slope and point of intercept are determined. It is shown that the complexity method is slightly more robust in that the coefficient of variation for the DE method has lower variability than the conventional method of mean frequency analysis.

The pH-induced swelling and collapse of a polybase brush synthesized by atom transfer radical polymerization

We have used neutron reflectometry to characterize the swelling behaviour of brushes of poly[2-(diethyl amino)ethyl methacrylate], a polybase, as a function of pH. The brushes, synthesized by the "grafting from" method of atom transfer radical polymerization, were observed to approximately double their thickness in low pH solutions, although the pK is shifted to a lower pH than in dilute solution. The composition-depth profile obtained from the reflectometry experiments for the swollen brushes reveals a region depleted in polymer between the substrate and the extended part of the brush.

Influence of La-doping on phase transformation and photocatalytic properties of ZnTiO3 nanoparticles synthesized via modified sol-gel method

Non-doped and La-doped ZnTiO3 nanoparticles were successfully synthesized via a modified sol–gel method. The synthesized nanoparticles were structurally characterized by PXRD, UV-vis DRS, FT-IR, SEM-EDS, TEM, Raman and photoluminescence spectroscopy. The results show that doping of La into the framework of ZnTiO3 has a strong influence on the physico-chemical properties of the synthesized nanoparticles. XRD results clearly show that the non-doped ZnTiO3 exhibits a hexagonal phase at 800 °C, whereas the La-doped ZnTiO3 exhibits a cubic phase under similar experimental conditions. In spite of the fact that it has a large ionic radius, the La is efficiently involved in the evolution process by blocking the crystal growth and the cubic to hexagonal transformation in ZnTiO3. Interestingly the absorption edge of the La-doped ZnTiO3 nanoparticles shifted from the UV region to the visible region. The photocatalytic activity of the La-doped ZnTiO3 nanoparticles was evaluated for the degradation of Rhodamine B under sunlight irradiation. The optimum photocatalytic activity was obtained for 2 atom% La-doped ZnTiO3, which is much higher than that of the non-doped ZnTiO3 as well as commercial N-TiO2. A possible mechanism for the degradation of Rhodamine B over La-doped ZnTiO3 was also discussed by trapping experiments. More importantly, the reusability of these nanoparticles is high. Hence La-doped ZnTiO3 nanoparticles can be used as efficient photocatalysts for environmental applications.

Monitoring of deployment process of shape memory polymers for morphing structures with embedded fibre Bragg grating sensors

This article demonstrates the use of embedded fibre Bragg gratings as vector bending sensor to monitor two-dimensional shape deformation of a shape memory polymer plate. The shape memory polymer plate was made by using thermal-responsive epoxy-based shape memory polymer materials, and the two fibre Bragg grating sensors were orthogonally embedded, one on the top and the other on the bottom layer of the plate, in order to measure the strain distribution in both longitudinal and transverse directions separately and also with temperature reference. When the shape memory polymer plate was bent at different angles, the Bragg wavelengths of the embedded fibre Bragg gratings showed a red-shift of 50 pm/°caused by the bent-induced tensile strain on the plate surface. The finite element method was used to analyse the stress distribution for the whole shape recovery process. The strain transfer rate between the shape memory polymer and optical fibre was also calculated from the finite element method and determined by experimental results, which was around 0.25. During the experiment, the embedded fibre Bragg gratings showed very high temperature sensitivity due to the high thermal expansion coefficient of the shape memory polymer, which was around 108.24 pm/°C below the glass transition temperature (Tg) and 47.29 pm/°C above Tg. Therefore, the orthogonal arrangement of the two fibre Bragg grating sensors could provide a temperature compensation function, as one of the fibre Bragg gratings only measures the temperature while the other is subjected to the directional deformation. © The Author(s) 2013.

Ag alloyed Pd single-atom catalysts for efficient selective hydrogenation of acetylene to ethylene in excess ethylene

Semihydrogenation of acetylene in an ethylene-rich stream is an industrially important process. Conventional supported monometallic Pd catalysts offer high acetylene conversion, but they suffer from very low selectivity to ethylene due to overhydrogenation and the formation of carbonaceous deposits. Herein, a series of Ag alloyed Pd single-atom catalysts, possessing only ppm levels of Pd, supported on silica gel were prepared by a simple incipient wetness coimpregnation method and applied to the selective hydrogenation of acetylene in an ethylene-rich stream under conditions close to the front-end employed by industry. High acetylene conversion and simultaneous selectivity to ethylene was attained over a wide temperature window, surpassing an analogous Au alloyed Pd single-atom system we previously reported. Restructuring of AgPd nanoparticles and electron transfer from Ag to Pd were evidenced by in situ FTIR and in situ XPS as a function of increasing reduction temperature. Microcalorimetry and XANES measurements support both geometric and electronic synergetic effects between the alloyed Pd and Ag. Kinetic studies provide valuable insight into the nature of the active sites within these AgPd/SiO2 catalysts, and hence, they provide evidence for the key factors underpinning the excellent performance of these bimetallic catalysts toward the selective hydrogenation of acetylene under ethylene-rich conditions while minimizing precious metal usage.

Determination of recombination coefficients for nanocrystalline silicon embedded in hydrogenated amorphous silicon

The spectroscopic pump-probe reflectance method was used to investigate recombination dynamics in samples of nanocrystalline silicon embedded in a matrix of hydrogenated amorphous silicon. We found that the dynamics can be described by a rate equation including linear and quadratic terms corresponding to recombination processes associated with impurities and impurity-assisted Auger ionization, respectively. We determined the values of the recombination coefficients using the initial concentrations method. We report the coefficients of 1.5 × 1011 s-1 and 1.1 × 10-10 cm3 s-1 for the impurity-assisted recombination and Auger ionization, respectively.

Real-time scheduling of embedded applications on multi-core platforms

For the past several decades, we have experienced the tremendous growth, in both scale and scope, of real-time embedded systems, thanks largely to the advances in IC technology. However, the traditional approach to get performance boost by increasing CPU frequency has been a way of past. Researchers from both industry and academia are turning their focus to multi-core architectures for continuous improvement of computing performance. In our research, we seek to develop efficient scheduling algorithms and analysis methods in the design of real-time embedded systems on multi-core platforms. Real-time systems are the ones with the response time as critical as the logical correctness of computational results. In addition, a variety of stringent constraints such as power/energy consumption, peak temperature and reliability are also imposed to these systems. Therefore, real-time scheduling plays a critical role in design of such computing systems at the system level. We started our research by addressing timing constraints for real-time applications on multi-core platforms, and developed both partitioned and semi-partitioned scheduling algorithms to schedule fixed priority, periodic, and hard real-time tasks on multi-core platforms. Then we extended our research by taking temperature constraints into consideration. We developed a closed-form solution to capture temperature dynamics for a given periodic voltage schedule on multi-core platforms, and also developed three methods to check the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research by incorporating the power/energy constraint with thermal awareness into our research problem. We investigated the energy estimation problem on multi-core platforms, and developed a computation efficient method to calculate the energy consumption for a given voltage schedule on a multi-core platform. In this dissertation, we present our research in details and demonstrate the effectiveness and efficiency of our approaches with extensive experimental results.

Design and analysis of micro-channel heat-exchanger embedded in Low Temperature Co-fire Ceramic (LTCC)

Increased device density, switching speeds of integrated circuits and decrease in package size is placing new demands for high power thermal-management. The convectional method of forced air cooling with passive heat sink can handle heat fluxes up-to 3-5W/cm2; however current microprocessors are operating at levels of 100W/cm2, This demands the usage of novel thermal-management systems. In this work, water-cooling systems with active heat sink are embedded in the substrate. The research involved fabricating LTCC substrates of various configurations - an open-duct substrate, the second with thermal vias and the third with thermal vias and free-standing metal columns and metal foil. Thermal testing was performed experimentally and these results are compared with CFD results. An overall thermal resistance for the base substrate is demonstrated to be 3.4oC/W-cm2. Addition of thermal vias reduces the effective resistance of the system by 7times and further addition of free standing columns reduced it by 20times.

Solid-state synthesis of embedded single-crystal metal oxide and phosphate nanoparticles and in situ crystallization

A new solid state organometallic route to embedded nanoparticle-containing inorganic materials is shown, through pyrolysis of metal-containing derivatives of cyclotriphosphazenes. Pyrolysis in air and at 800 °C of new molecular precursors gives individual single-crystal nanoparticles of SiP2O7, TiO2, P4O7, WP2O7 and SiO2, depending on the precursor used. High resolution transmission electron microscopy investigations reveal, in most cases, perfect single crystals of metal oxides and the first nanostructures of negative thermal expansion metal phosphates with diameters in the range 2–6 nm for all products. While all nanoparticles are new by this method, WP2O7 and SiP2O7 nanoparticles are reported for the first time. In situ recrystallization formation of nanocrystals of SiP2O7 was also observed due to electron beam induced reactions during measurements of the nanoparticulate pyrolytic products SiO2 and P4O7. The possible mechanism for the formation of the nanoparticles at much lower temperatures than their bulk counterparts in both cases is discussed. Degrees of stabilization from the formation of P4O7 affects the nanocrystalline products: nanoparticles are observed for WP2O7, with coalescing crystallization occurring for the amorphous host in which SiP2O7 crystals form as a solid within a solid. The approach allows the simple formation of multimetallic, monometallic, metal-oxide and metal phosphate nanocrystals embedded in an amorphous dielectric. The method and can be extended to nearly any metal capable of successful coordination as an organometallic to allow embedded nanoparticle layers and features to be deposited or written on surfaces for application as high mobility pyrophosphate lithium–ion cathode materials, catalysis and nanocrystal embedded dielectric layers.

Multimode Atomic Pattern Formation via Enhanced Light-atom Interactions

The nonlinear interaction between light and atoms is an extensive field of study with a broad range of applications in quantum information science and condensed matter physics. Nonlinear optical phenomena occurring in cold atoms are particularly interesting because such slowly moving atoms can spatially organize into density gratings, which allows for studies involving optical interactions with structured materials. In this thesis, I describe a novel nonlinear optical effect that arises when cold atoms spatially bunch in an optical lattice. I show that employing this spatial atomic bunching provides access to a unique physical regime with reduced thresholds for nonlinear optical processes and enhanced material properties. Using this method, I observe the nonlinear optical phenomenon of transverse optical pattern formation at record-low powers. These transverse optical patterns are generated by a wave- mixing process that is mediated by the cold atomic vapor. The optical patterns are highly multimode and induce rich non-equilibrium atomic dynamics. In particular, I find that there exists a synergistic interplay between the generated optical pat- terns and the atoms, wherein the scattered fields help the atoms to self-organize into new, multimode structures that are not externally imposed on the atomic sample. These self-organized structures in turn enhance the power in the optical patterns. I provide the first detailed investigation of the motional dynamics of atoms that have self-organized in a multimode geometry. I also show that the transverse optical patterns induce Sisyphus cooling in all three spatial dimensions, which is the first observation of spontaneous three-dimensional cooling. My experiment represents a unique means by which to study nonlinear optics and non-equilibrium dynamics at ultra-low required powers.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Photoionization of Co+ and electron-impact excitation of Co2 + using the Dirac R-matrix method

Modelling of massive stars and supernovae (SNe) plays a crucial role in understanding galaxies. From this modelling we can derive fundamental constraints on stellar evolution, mass-loss processes, mixing, and the products of nucleosynthesis. Proper account must be taken of all important processes that populate and depopulate the levels (collisional excitation, de-excitation, ionization, recombination, photoionization, bound–bound processes). For the analysis of Type Ia SNe and core collapse SNe (Types Ib, Ic and II) Fe group elements are particularly important. Unfortunately little data is currently available and most noticeably absent are the photoionization cross-sections for the Fe-peaks which have high abundances in SNe. Important interactions for both photoionization and electron-impact excitation are calculated using the relativistic Dirac atomic R-matrix codes (DARC) for low-ionization stages of Cobalt. All results are calculated up to photon energies of 45 eV and electron energies up to 20 eV. The wavefunction representation of Co III has been generated using GRASP0 by including the dominant 3d⁷, 3d⁶[4s, 4p], 3p⁴3d⁹ and 3p⁶3d⁹ configurations, resulting in 292 fine structure levels. Electron-impact collision strengths and Maxwellian averaged effective collision strengths across a wide range of astrophysically relevant temperatures are computed for Co III. In addition, statistically weighted level-resolved ground and metastable photoionization cross-sections are presented for Co II and compared directly with existing work.

Development of a Wireless MEMS Multifunction Sensor System and Field Demonstration of Embedded Sensors for Monitoring Concrete Pavements, TR-637, 2016

Pavements tend to deteriorate with time under repeated traffic and/or environmental loading. By detecting pavement distresses and damage early enough, it is possible for transportation agencies to develop more effective pavement maintenance and rehabilitation programs and thereby achieve significant cost and time savings. The structural health monitoring (SHM) concept can be considered as a systematic method for assessing the structural state of pavement infrastructure systems and documenting their condition. Over the past several years, this process has traditionally been accomplished through the use of wired sensors embedded in bridge and highway pavement. However, the use of wired sensors has limitations for long-term SHM and presents other associated cost and safety concerns. Recently, micro-electromechanical sensors and systems (MEMS) and nano-electromechanical systems (NEMS) have emerged as advanced/smart-sensing technologies with potential for cost-effective and long-term SHM. This two-pronged study evaluated the performance of commercial off-the-shelf (COTS) MEMS sensors embedded in concrete pavement (Final Report Volume I) and developed a wireless MEMS multifunctional sensor system for health monitoring of concrete pavement (Final Report Volume II).