The National Spent Nuclear Fuel Program, located at the Idaho National Laboratory (INL), coordinates and integrates national efforts in management and disposal of US Department of Energy (DOE)-owned spent nuclear fuel. These management functions include development of standardised systems for long-term disposal in the proposed Yucca Mountain repository. Nuclear criticality control measures are needed in these systems to avoid restrictive fissile loading limits because of the enrichment and total quantity of fissile material in some types of the DOE spent nuclear fuel. This need is being addressed by development of corrosion-resistant, neutron-absorbing structural alloys for nuclear criticality control. This paper outlines results of a metallurgical development programme that is investigating the alloying of gadolinium into a nickel-chromium-molybdenum alloy matrix. Gadolinium has been chosen as the neutron absorption alloying element due to its high thermal neutron absorption cross section and low solubility in the expected repository environment. The nickel-chromium-molybdenum alloy family was chosen for its known corrosion performance, mechanical properties, and weldability. The workflow of this programme includes chemical composition definition, primary and secondary melting studies, ingot conversion processes, properties testing, and national consensus codes and standards work. The microstructural investigation of these alloys shows that the gadolinium addition is present in the alloy as a gadolinium-rich second phase. The mechanical strength values are similar to those expected for commercial Ni-Cr-Mo alloys. The alloys have been corrosion tested with acceptable results. The initial results of weldability tests have also been acceptable. Neutronic testing in a moderated critical array has generated favourable results. An American Society for Testing and Materials material specification has been issued for the alloy and a Code Case has been submitted to the American Society of Mechanical Engineers for code qualification.
Techniques for mitigating the adsorption of {sup 137}Cs and {sup 60}Co on metal surfaces (e.g. RAM packages) exposed to contaminated water (e.g. spent-fuel pools) have been developed and experimentally verified. The techniques are also effective in removing some of the {sup 60}Co and {sup 137}Cs that may have been adsorbed on the surfaces after removal from the contaminated water. The principle for the {sup 137}Cs mitigation technique is based upon ion-exchange processes. In contrast, {sup 60}Co contamination primarily resides in minute particles of crud that become lodged on cask surfaces. Crud is an insoluble Fe-Ni-Cr oxide that forms colloidal-sized particles as reactor cooling systems corrode. Because of the similarity between Ni{sup 2+} and Co{sup 2+}, crud is able to scavenge and retain traces of cobalt as it forms. A number of organic compounds have a great specificity for combining with nickel and cobalt. Ongoing research is investigating the effectiveness of chemical complexing agent EDTA with regard to its ability to dissolve the host phase (crud) thereby liberating the entrained {sup 60}Co into a solution where it can be rinsed away.
Using a magnetic pressure drive, an absolute measurement of stress and density along the principal compression isentrope is obtained for solid aluminum to 240 GPa. Reduction of the free-surface velocity data relies on a backward integration technique, with approximate accounting for unknown systematic errors in experimental timing. Maximum experimental uncertainties are {+-}4.7% in stress and {+-}1.4% in density, small enough to distinguish between different equation-of-state (EOS) models. The result agrees well with a tabular EOS that uses an empirical universal zero-temperature isotherm.
Spectral imaging where a complete spectrum is collected from each of a series of spatial locations (1D lines, 2D images or 3D volumes) is now available on a wide range of analytical tools - from electron and x-ray to ion beam instruments. With this capability to collect extremely large spectral images comes the need for automated data analysis tools that can rapidly and without bias reduce a large number of raw spectra to a compact, chemically relevant, and easily interpreted representation. It is clear that manual interrogation of individual spectra is impractical even for very small spectral images (< 5000 spectra). More typical spectral images can contain tens of thousands to millions of spectra, which given the constraint of acquisition time may contain between 5 and 300 counts per 1000-channel spectrum. Conventional manual approaches to spectral image analysis such as summing spectra from regions or constructing x-ray maps are prone to bias and possibly error. One way to comprehensively analyze spectral image data, which has been automated, is to utilize an unsupervised self-modeling multivariate statistical analysis method such as multivariate curve resolution (MCR). This approach has proven capable of solving a wide range of analytical problems based upon the counting of x-rays (SEM/STEM-EDX, XRF, PIXE), electrons (EELS, XPS) and ions (TOF-SIMS). As an example of the MCR approach, a STEM x-ray spectral image from a ZrB2-SiC composite was acquired and analyzed. The data were generated in a FEI Tecnai F30-ST TEM/STEM operated at 300kV, equipped with an EDAX SUTW x-ray detector. The spectral image was acquired with the TIA software on the STEM at 128 by 128 pixels (12nm/pixel) for 100msec dwell per pixel (total acquisition time was 30 minutes) with a probe of approximately the same size as each pixel. Each spectrum in the image had, on average, 500 counts. The calculation took 5 seconds on a PC workstation with dual 2.4GHz PentiumIV Xeon processors and 2Gbytes of RAM and resulted in four chemically relevant components, which are shown in Figure 1. The analysis region was at a triple junction of three ZrB2 grains that contained zirconium oxide, aluminum oxide and a glass phase. The power of unbiased statistical methods, such as MCR as applied here, is that no a priori knowledge of the material's chemistry is required. The algorithms, in this case, effectively reduced over 16,000 2000-channel spectra (64Mbytes) to four images and four spectral shapes (72kbytes), which in this case represent chemical phases. This three order of magnitude compression is achieved rapidly with no loss of chemical information. There is also the potential to correlate multiple analytical techniques like, for example, EELS and EDS in the STEM adding sensitivity to light elements as well as bonding information for EELS to the more comprehensive spectral coverage of EDS.
Wear is a critical factor in determining the durability of microelectromechanical systems (MEMS). While the reliability of polysilicon MEMS has received extensive attention, the mechanisms responsible for this failure mode at the microscale have yet to be conclusively determined. We have used on-chip polycrystalline silicon side-wall friction MEMS specimens to study active mechanisms during sliding wear in ambient air. Worn parts were examined by analytical scanning and transmission electron microscopy, while local temperature changes were monitored using advanced infrared microscopy. Observations show that small amorphous debris particles ({approx}50-100 nm) are removed by fracture through the silicon grains ({approx}500 nm) and are oxidized during this process. Agglomeration of such debris particles into larger clusters also occurs. Some of these debris particles/clusters create plowing tracks on the beam surface. A nano-crystalline surface layer ({approx}20-200 nm), with higher oxygen content, forms during wear at and below regions of the worn surface; its formation is likely aided by high local stresses. No evidence of dislocation plasticity or of extreme local temperature increases was found, ruling out the possibility of high temperature-assisted wear mechanisms.
Microanalysis is typically performed to analyze the near surface of materials. There are many instances where chemical information about the third spatial dimension is essential to the solution of materials analyses. The majority of 3D analyses however focus on limited spectral acquisition and/or analysis. For truly comprehensive 3D chemical characterization, 4D spectral images (a complete spectrum from each volume element of a region of a specimen) are needed. Furthermore, a robust statistical method is needed to extract the maximum amount of chemical information from that extremely large amount of data. In this paper, an example of the acquisition and multivariate statistical analysis of 4D (3-spatial and 1-spectral dimension) x-ray spectral images is described. The method of utilizing a single- or dual-beam FIB (w/o or w/SEM) to get at 3D chemistry has been described by others with respect to secondary-ion mass spectrometry. The basic methodology described in those works has been modified for comprehensive x-ray microanalysis in a dual-beam FIB/SEM (FEI Co. DB-235). In brief, the FIB is used to serially section a site-specific region of a sample and then the electron beam is rastered over the exposed surfaces with x-ray spectral images being acquired at each section. All this is performed without rotating or tilting the specimen between FIB cutting and SEM imaging/x-ray spectral image acquisition. The resultant 4D spectral image is then unfolded (number of volume elements by number of channels) and subjected to the same multivariate curve resolution (MCR) approach that has proven successful for the analysis of lower-dimension x-ray spectral images. The TSI data sets can be in excess of 4Gbytes. This problem has been overcome (for now) and images up to 6Gbytes have been analyzed in this work. The method for analyzing such large spectral images will be described in this presentation. A comprehensive 3D chemical analysis was performed on several corrosion specimens of Cu electroplated with various metals. Figure 1A shows the top view of the localized corrosion region prepared for FIB sectioning. The TSI region has been coated with Pt and a trench has been milled along the bottom edge of the region, exposing it to the electron beam as seen in Figure 1B. The TSI consisted of 25 sections and was approximately 6Gbytes. Figure 1C shows several of the components rendered in 3D: Green is Cu; blue is Pb; cyan represents one of the corrosion products that contains Cu, Zn, O, S, and C; and orange represents the other corrosion product with Zn, O, S and C. Figure 1 D shows all of the component spectral shapes from the analysis. There is severe pathological overlap of the spectra from Ni, Cu and Zn as well as Pb and S. in spite of this clean spectral shapes have been extracted from the TSI. This powerful TSI technique could be applied to other sectioning methods well.
Analyzing the performance of a complex System of Systems (SoS) requires a systems engineering approach. Many such SoS exist in the Military domain. Examples include the Army's next generation Future Combat Systems 'Unit of Action' or the Navy's Aircraft Carrier Battle Group. In the case of a Unit of Action, a system of combat vehicles, support vehicles and equipment are organized in an efficient configuration that minimizes logistics footprint while still maintaining the required performance characteristics (e.g., operational availability). In this context, systems engineering means developing a global model of the entire SoS and all component systems and interrelationships. This global model supports analyses that result in an understanding of the interdependencies and emergent behaviors of the SoS. Sandia National Laboratories will present a robust toolset that includes methodologies for developing a SoS model, defining state models and simulating a system of state models over time. This toolset is currently used to perform logistics supportability and performance assessments of the set of Future Combat Systems (FCS) for the U.S. Army's Program Manager Unit of Action.
Reducing agricultural water use in arid regions while maintaining or improving economic productivity of the agriculture sector is a major challenge. Controlled environment agriculture (CEA, or, greenhouse agriculture) affords advantages in direct resource use (less land and water required) and productivity (i.e., much higher product yield and quality per unit of resources used) relative to conventional open-field practices. These advantages come at the price of higher operating complexity and costs per acre. The challenge is to implement and apply CEA such that the productivity and resource use advantages will sufficiently outweigh the higher operating costs to provide for overall benefit and viability. This project undertook an investigation of CEA for livestock forage production as a water-saving alternative to open-field forage production in arid regions. Forage production is a large consumer of fresh water in many arid regions of the world, including the southwestern U.S. and northern Mexico. With increasing competition among uses (agriculture, municipalities, industry, recreation, ecosystems, etc.) for limited fresh water supplies, agricultural practice alternatives that can potentially maintain or enhance productivity while reducing water use warrant consideration. The project established a pilot forage production greenhouse facility in southern New Mexico based on a relatively modest and passive (no active heating or cooling) system design pioneered in Chihuahua, Mexico. Experimental operations were initiated in August 2004 and carried over into early-FY05 to collect data and make initial assessments of operational and technical system performance, assess forage nutrition content and suitability for livestock, identify areas needing improvement, and make initial assessment of overall feasibility. The effort was supported through the joint leveraging of late-start FY04 LDRD funds and bundled CY2004 project funding from the New Mexico Small Business Technical Assistance program at Sandia. Despite lack of optimization with the project system, initial results show the dramatic water savings potential of hydroponic forage production compared with traditional irrigated open field practice. This project produced forage using only about 4.5% of the water required for equivalent open field production. Improved operation could bring water use to 2% or less. The hydroponic forage production system and process used in this project are labor intensive and not optimized for minimum water usage. Freshly harvested hydroponic forage has high moisture content that dilutes its nutritional value by requiring that livestock consume more of it to get the same nutritional content as conventional forage. In most other aspects the nutritional content compares well on a dry weight equivalent basis with other conventional forage. More work is needed to further explore and quantify the opportunities, limitations, and viability of this technique for broader use. Collection of greenhouse environmental data in this project was uniquely facilitated through the implementation and use of a self-organizing, wirelessly networked, multi-modal sensor system array with remote cell phone data link capability. Applications of wirelessly networked sensing with improved modeling/simulation and other Sandia technologies (e.g., advanced sensing and control, embedded reasoning, modeling and simulation, materials, robotics, etc.) can potentially contribute to significant improvement across a broad range of CEA applications.
Video and image data are knowledge-rich sources of information, but their utility for current and future systems is limited without autonomous methods for understanding and characterizing their content. Semantic-based video understanding may benefit systems dedicated to the detection of insiders, alarm patterns, unauthorized activities in material monitoring applications, etc. A direct benefit of this technology is not only intelligent alarm analysis, but the ability to browse and perform query-based searches for useful and interesting information after video data has been acquired and stored. These searches can provide a tremendous benefit for use in intelligence agency, government, military, and DOE site investigations. This report provides an initial investigation into the algorithms and methods needed to characterize and understand video content. Such algorithms include background modeling, detecting dynamic image regions, grouping dynamic pixels into coherent objects, and robust tracking strategies. With solid approaches for addressing these problems, analysis can be performed seeking to recognize distinctive objects and their motions leading to semantic-based video searches.
This SAND report provides the technical progress through October 2004 of the Sandia-led project, %22Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling,%22 funded by the DOE Office of Science Genomes to Life Program. Understanding, predicting, and perhaps manipulating carbon fixation in the oceans has long been a major focus of biological oceanography and has more recently been of interest to a broader audience of scientists and policy makers. It is clear that the oceanic sinks and sources of CO2 are important terms in the global environmental response to anthropogenic atmospheric inputs of CO2 and that oceanic microorganisms play a key role in this response. However, the relationship between this global phenomenon and the biochemical mechanisms of carbon fixation in these microorganisms is poorly understood. In this project, we will investigate the carbon sequestration behavior of Synechococcus Sp., an abundant marine cyanobacteria known to be important to environmental responses to carbon dioxide levels, through experimental and computational methods. This project is a combined experimental and computational effort with emphasis on developing and applying new computational tools and methods. Our experimental effort will provide the biology and data to drive the computational efforts and include significant investment in developing new experimental methods for uncovering protein partners, characterizing protein complexes, identifying new binding domains. We will also develop and apply new data measurement and statistical methods for analyzing microarray experiments. Computational tools will be essential to our efforts to discover and characterize the function of the molecular machines of Synechococcus. To this end, molecular simulation methods will be coupled with knowledge discovery from diverse biological data sets for high-throughput discovery and characterization of protein-protein complexes. In addition, we will develop a set of novel capabilities for inference of regulatory pathways in microbial genomes across multiple sources of information through the integration of computational and experimental technologies. These capabilities will be applied to Synechococcus regulatory pathways to characterize their interaction map and identify component proteins in these - 4 - pathways. We will also investigate methods for combining experimental and computational results with visualization and natural language tools to accelerate discovery of regulatory pathways. The ultimate goal of this effort is develop and apply new experimental and computational methods needed to generate a new level of understanding of how the Synechococcus genome affects carbon fixation at the global scale. Anticipated experimental and computational methods will provide ever-increasing insight about the individual elements and steps in the carbon fixation process, however relating an organism's genome to its cellular response in the presence of varying environments will require systems biology approaches. Thus a primary goal for this effort is to integrate the genomic data generated from experiments and lower level simulations with data from the existing body of literature into a whole cell model. We plan to accomplish this by developing and applying a set of tools for capturing the carbon fixation behavior of complex of Synechococcus at different levels of resolution. Finally, the explosion of data being produced by high-throughput experiments requires data analysis and models which are more computationally complex, more heterogeneous, and require coupling to ever increasing amounts of experimentally obtained data in varying formats. These challenges are unprecedented in high performance scientific computing and necessitate the development of a companion computational infrastructure to support this effort. More information about this project, including a copy of the original proposal, can be found at www.genomes-to-life.org Acknowledgment We want to gratefully acknowledge the contributions of the GTL Project Team as follows: Grant S. Heffelfinger1*, Anthony Martino2, Andrey Gorin3, Ying Xu10,3, Mark D. Rintoul1, Al Geist3, Matthew Ennis1, Hashimi Al-Hashimi8, Nikita Arnold3, Andrei Borziak3, Bianca Brahamsha6, Andrea Belgrano12, Praveen Chandramohan3, Xin Chen9, Pan Chongle3, Paul Crozier1, PguongAn Dam10, George S. Davidson1, Robert Day3, Jean Loup Faulon2, Damian Gessler12, Arlene Gonzalez2, David Haaland1, William Hart1, Victor Havin3, Tao Jiang9, Howland Jones1, David Jung3, Ramya Krishnamurthy3, Yooli Light2, Shawn Martin1, Rajesh Munavalli3, Vijaya Natarajan3, Victor Olman10, Frank Olken4, Brian Palenik6, Byung Park3, Steven Plimpton1, Diana Roe2, Nagiza Samatova3, Arie Shoshani4, Michael Sinclair1, Alex Slepoy1, Shawn Stevens8, Chris Stork1, Charlie Strauss5, Zhengchang Su10, Edward Thomas1, Jerilyn A. Timlin1, Xiufeng Wan11, HongWei Wu10, Dong Xu11, Gong-Xin Yu3, Grover Yip8, Zhaoduo Zhang2, Erik Zuiderweg8 *Author to whom correspondence should be addressed (gsheffe%40sandia.gov) 1. Sandia National Laboratories, Albuquerque, NM 2. Sandia National Laboratories, Livermore, CA 3. Oak Ridge National Laboratory, Oak Ridge, TN 4. Lawrence Berkeley National Laboratory, Berkeley, CA 5. Los Alamos National Laboratory, Los Alamos, NM 6. University of California, San Diego 7. University of Illinois, Urbana/Champaign 8. University of Michigan, Ann Arbor 9. University of California, Riverside 10. University of Georgia, Athens 11. University of Missouri, Columbia 12. National Center for Genome Resources, Santa Fe, NM Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Local topological modification is widely used to improve mesh quality after automatic generation of tetrahedral and quadrilateral meshes. These same techniques are also used to support adaptive refinement of these meshes. In contrast, few methods are known for locally modifying the topology of hexahedral meshes. Most efforts to do this have been based on fixed transition templates or global refinement. In contrast, a dual-based 'pillowing' method has been used which, while local, is still quite restricted in its application, and is typically applied in a template-based fashion. In this presentation, I will describe the generalization of a dual-based approach to the local topological modification of hex meshes and its application to clean up hexahedral meshes. A set of three operations for locally modifying hex mesh topology has been shown to reproduce the so-called 'flipping' operations described by Bern et. al as well as other commonly-used refinement templates. I will describe the implementation of these operators and their application to real meshes. Challenging aspects of this work have included visualization of a hex mesh and its dual (especially for poor-quality meshes); the incremental modification of both the primal (i.e. the mesh) and the dual simultaneously; and the interactive steering of these operations with the goal of improving hex meshes which would otherwise have unacceptable quality. These aspects will be discussed in the context of improving hex meshes generated by curve contraction-based whisker weaving. Application of these techniques for improving other hexahedral mesh types, for example those resulting from tetrahedral subdivision, will also be discussed.
We design a density-functional-theory (DFT) exchange-correlation functional that enables an accurate treatment of systems with electronic surfaces. Surface-specific approximations for both exchange and correlation energies are developed. A subsystem functional approach is then used: an interpolation index combines the surface functional with a functional for interior regions. When the local density approximation is used in the interior, the result is a straightforward functional for use in self-consistent DFT. The functional is validated for two metals (Al, Pt) and one semiconductor (Si) by calculations of (i) established bulk properties (lattice constants and bulk moduli) and (ii) a property where surface effects exist (the vacancy formation energy). Good and coherent results indicate that this functional may serve well as a universal first choice for solid-state systems and that yet improved functionals can be constructed by this approach.
Many highly oscillatory circuits have a wide separation of time scales between the underlying oscillation and the behavior of interest. This is particularly true of communication circuits. Multiple-time Partial Differential Equation (MPDE) methods offer substantial speed-up for these circuits by introducing a periodic artificial time variable that represents the highly oscillatory behavior. This leaves just the slowly changing behavior of interest, which can be integrated with much larger steps. One problem of particular interest is the larger initial condition that must be specified for this periodic artificial time variable. One possible solution is to formulate an optimization problem in the hopes of increasing the step sizes taken in the slow time direction. This talk will discuss one possible unconstrained optimization problem for determining this initial condition. Numerical results and comparisons to several other initial condition strategies will be presented in addition to MPDE background research and implementation issues.
In this paper, we explore the stability properties of time-domain numerical methods for multitime partial differential equations (MPDEs) in detail. We demonstrate that simple techniques for numerical discretization can lead easily to instability. By investigating the underlying eigenstructure of several discretization techniques along different artificial time scales, we show that not all combinations of techniques are stable. We identify choices of discretization method and step size, along fast and slow time scales, that lead to robust, stable time-domain integration methods for the MPDE. One of our results is that applying overstable methods along one time-scale can compensate for unstable discretization along others. Our novel integration schemes bring robustness to time-domain MPDE solution methods, as we demonstrate with examples.
Experimental evidence and corresponding theoretical analyses have led to the conclusion that the system composed of Xe hollow atom states, that produce a characteristic Xe(L) spontaneous emission spectrum at 1 {at} 2.9 {angstrom} and arise from the excitation of Xe clusters with an intense pulse of 248 nm radiation propagating in a self-trapped plasma channel, closely represents the ideal situation sought for amplification in the multikilovolt region. The key innovation that is central to all aspects of the proposed work is the controlled compression of power to the level ({approx} 10{sup 20} W/cm{sup 3}) corresponding to the maximum achieved by thermonuclear events. Furthermore, since the x-ray power that is produced appears in a coherent form, an entirely new domain of physical interaction is encountered that involves states of matter that are both highly excited and highly ordered. Moreover, these findings lead to the concept of 'photonstaging', an idea which offers the possibility of advancing the power compression by an additional factor of {approx} 10{sup 9} to {approx} 10{sup 29} W/cm{sup 3}. In this completely unexplored regime, g-ray production ({h_bar}{omega}{sub {gamma}} {approx} 1 MeV) is expected to be a leading process. A new technology for the production of very highly penetrating radiation would then be available. The Xe(L) source at {h_bar}{omega}{sub x} {approx} 4.5 keV can be applied immediately to the experimental study of many aspects of the coupling of intense femtosecond x-ray pulses to materials. In a joint collaboration, the UIC group and Sandia plan to explore the following areas. These are specifically, (1) anomalous electromagnetic coupling to solid state materials, (2) 3D nanoimaging of solid matter and hydrated biological materials (e.g. interchromosomal linkers and actin filaments in muscle), and (3) EMP generation with attosecond x-rays.
Because many solid objects, both stationary and mobile, will be present in an indoor environment, the design of an indoor aerosol cloud finding lidar (light detection and ranging) instrument presents a number of challenges. The cloud finder must be able to discriminate between these solid objects and aerosol clouds as small as 1-meter in depth in order to probe suspect clouds. While a near IR ({approx}1.5-{micro}m) laser is desirable for eye-safety, aerosol scattering cross sections are significantly lower in the near-IR than at visible or W wavelengths. The receiver must deal with a large dynamic range since the backscatter from solid object will be orders of magnitude larger than for aerosol clouds. Fast electronics with significant noise contributions will be required to obtain the necessary temporal resolution. We have developed a laboratory instrument to detect aerosol clouds in the presence of solid objects. In parallel, we have developed a lidar performance model for performing trade studies. Careful attention was paid to component details so that results obtained in this study could be applied towards the development of a practical instrument. The amplitude and temporal shape of the signal return are analyzed for discrimination of aerosol clouds in an indoor environment. We have assessed the feasibility and performance of candidate approaches for a fieldable instrument. With the near-IR PMT and a 1.5-{micro}m laser source providing 20-{micro}J pulses, we estimate a bio-aerosol detection limit of 3000 particles/l.
Solution-based synthesis is a powerful approach for creating nano-structured materials. Although there have been significant recent successes in its application to fabricating nanomaterials, the general principles that control solution synthesis are not well understood. The purpose of this LDRD project was to develop the scientific principles required to design and build unique nanostructures in crystalline oxides and II/VI semiconductors using solution-based molecular self-assembly techniques. The ability to synthesize these materials in a range of different nano-architectures (from controlled morphology nanocrystals to surface templated 3-D structures) has provided the foundation for new opportunities in such areas as interactive interfaces for optics, electronics, and sensors. The homogeneous precipitation of ZnO in aqueous solution was used primarily as the model system for the project. We developed a low temperature, aqueous solution synthesis route for preparation of large arrays of oriented ZnO nanostructures. Through control of heterogeneous nucleation and growth, methods to predicatively alter the ZnO microstructures by tailoring the surface chemistry of the crystals were established. Molecular mechanics simulations, involving single point energy calculations and full geometry optimizations, were developed to assist in selecting appropriate chemical systems and understanding physical adsorption and ultimately growth mechanisms in the design of oxide nanoarrays. The versatility of peptide chemistry in controlling the formation of cadmium sulfide nanoparticles and zinc oxide/cadmium sulfide heterostructures was also demonstrated.
Solid-state {sup 1}H magic angle spinning (MAS) NMR was used to investigate sulfonated Diels-Alder poly(phenlylene) polymer membranes. Under high spinning speed {sup 1}H MAS conditions, the proton environments of the sulfonic acid and phenylene polymer backbone are resolved. A double-quantum (DQ) filter using the rotor-synchronized back-to-back (BABA) NMR multiple-pulse sequence allowed the selective suppression of the sulfonic proton environment in the {sup 1}H MAS NMR spectra. This DQ filter in conjunction with a spin diffusion NMR experiment was then used to measure the domain size of the sulfonic acid component within the membrane. In addition, the temperature dependence of the sulfonic acid spin-spin relaxation time (T{sub 2}) was determined, providing an estimate of the activation energy for the proton dynamics of the dehydrated membrane.
The fundamental chemical behavior of the AlCl{sub 3}/SO{sub 2}Cl{sub 2} catholyte system was investigated using {sup 27}Al NMR spectroscopy, Raman spectroscopy, and single-crystal X-ray diffraction. Three major Al-containing species were found to be present in this catholyte system, where the ratio of each was dependent upon aging time, concentration, and/or storage temperature. The first species was identified as [Cl{sub 2}Al({mu}-Cl)]{sub 2} in equilibrium with AlCl{sub 3}. The second species results from the decomposition of SO{sub 2}Cl{sub 2} which forms Cl{sub 2}(g) and SO{sub 2}(g). The SO{sub 2}(g) is readily consumed in the presence of AlCl{sub 3} to form the crystallographically characterized species [Cl{sub 2}Al({mu}-O{sub 2}SCl)]{sub 2} (1). For 1, each Al is tetrahedrally (T{sub d}) bound by two terminal Cl and two {mu}-O ligands whereas, the S is three-coordinated by two {mu}-O ligands and one terminal Cl. The third molecular species also has T{sub d}-coordinated Al metal centers but with increased oxygen coordination. Over time it was noted that a precipitate formed from the catholyte solutions. Raman spectroscopic studies show that this gel or precipitate has a component that was consistent with thionyl chloride. We have proposed a polymerization scheme that accounts for the precipitate formation. Further NMR studies indicate that the precipitate is in equilibrium with the solution.
There is a general lack of compact electromagnetic radiation sources between 1 and 10 terahertz (THz). This a challenging spectral region lying between optical devices at high frequencies and electronic devices at low frequencies. While technologically very underdeveloped the THz region has the promise to be of significant technological importance, yet demonstrating its relevance has proven difficult due to the immaturity of the area. While the last decade has seen much experimental work in ultra-short pulsed terahertz sources, many applications will require continuous wave (cw) sources, which are just beginning to demonstrate adequate performance for application use. In this project, we proposed examination of two potential THz sources based on intersubband semiconductor transitions, which were as yet unproven. In particular we wished to explore quantum cascade lasers based sources and electronic based harmonic generators. Shortly after the beginning of the project, we shifted our emphasis to the quantum cascade lasers due to two events; the publication of the first THz quantum cascade laser by another group thereby proving feasibility, and the temporary shut down of the UC Santa Barbara free-electron lasers which were to be used as the pump source for the harmonic generation. The development efforts focused on two separate cascade laser thrusts. The ultimate goal of the first thrust was for a quantum cascade laser to simultaneously emit two mid-infrared frequencies differing by a few THz and to use these to pump a non-linear optical material to generate THz radiation via parametric interactions in a specifically engineered intersubband transition. While the final goal was not realized by the end of the project, many of the completed steps leading to the goal will be described in the report. The second thrust was to develop direct THz QC lasers operating at terahertz frequencies. This is simpler than a mixing approach, and has now been demonstrated by a few groups with wavelengths spanning 65-150 microns. We developed and refined the MBE growth for THz for both internally and externally designed QC lasers. Processing related issues continued to plague many of our demonstration efforts and will also be addressed in this report.
We demonstrate direct diode-bar side pumping of a Yb-doped fiber laser using embedded-mirror side pumping (EMSP). In this method, the pump beam is launched by reflection from a micro-mirror embedded in a channel polished into the inner cladding of a double-clad fiber (DCF). The amplifier employed an unformatted, non-lensed, ten-emitter diode bar (20 W) and glass-clad, polarization-maintaining, large-mode-area fiber. Measurements with passive fiber showed that the coupling efficiency of the raw diode-bar output into the DCF (ten launch sites) was {approx}84%; for comparison, the net coupling efficiency using a conventional, formatted, fiber-coupled diode bar is typically 50-70%, i.e., EMSP results in a factor of 2-3 less wasted pump power. The slope efficiency of the side-pumped fiber laser was {approx}80% with respect to launched pump power and 24% with respect to electrical power consumption of the diode bar; at a fiber-laser output power of 7.5 W, the EMSP diode bar consumed 41 W of electrical power (18% electrical-to-optical efficiency). When end pumped using a formatted diode bar, the fiber laser consumed 96 W at 7.5 W output power, a factor of 2.3 less efficient, and the electrical-to-optical slope efficiency was lower by a factor of 2.0. Passive-fiber measurements showed that the EMSP alignment sensitivity is nearly identical for a single emitter as for the ten-emitter bar. EMSP is the only method capable of directly launching the unformatted output of a diode bar directly into DCF (including glass-clad DCF), enabling fabrication of low-cost, simple, and compact, diode-bar-pumped fiber lasers and amplifiers.
Spreading of bacteria in a highly advective, disordered environment is examined. Predictions of super-diffusive spreading for a simplified reaction-diffusion equation are tested. Concentration profiles display anomalous growth and super-diffusive spreading. A perturbation analysis yields a crossover time between diffusive and super-diffusive behavior. The time's dependence on the convection velocity and disorder is tested. Like the simplified equation, the full linear reaction-diffusion equation displays super-diffusive spreading perpendicular to the convection. However, for mean positive growth rates the full nonlinear reaction-diffusion equation produces symmetric spreading with a Fisher wavefront, whereas net negative growth rates cause an asymmetry, with a slower wavefront velocity perpendicular to the convection.
Chemical crosslinking is an important tool for probing protein structure and protein-protein interactions. The approach usually involves crosslinking of specific amino acids within a folded protein or protein complex, enzymatic digestion of the crosslinked protein(s), and identification of the resulting crosslinked peptides by liquid chromatography/mass spectrometry (LC/MS). In this manner, distance constraints are obtained for residues that must be in close proximity to one another in the native structure or complex. As the complexity of the system under study increases, for example, a large multi-protein complex, simply measuring the mass of a crosslinked species will not always be sufficient to determine the identity of the crosslinked peptides. In such a case, tandem mass spectrometry (MS/MS) could provide the required information if the data can be properly interpreted. In MS/MS, a species of interest is isolated in the gas phase and allowed to undergo collision induced dissociation (CID). Because the gas-phase dissociation pathways of peptides have been well studied, methods are established for determining peptide sequence by MS/MS. However, although crosslinked peptides dissociate through some of the same pathways as isolated peptides, the additional dissociation pathways available to the former have not been studied in detail. Software such as MS2Assign has been written to assist in the interpretation of MS/MS from crosslinked peptide species, but it would be greatly enhanced by a more thorough understanding of how these species dissociate. We are thus systematically investigating the dissociation pathways open to crosslinked peptide species. A series of polyalanine and polyglycine model peptides have been synthesized containing one or two lysine residues to generate defined inter- and intra-molecular crosslinked species, respectively. Each peptide contains 11 total residues, and one arginine residue is present at the carboxy terminus to mimic species generated by tryptic digestion. The peptides have been allowed to react with a series of commonly used crosslinkers such as DSS, DSG, and DST. The tandem mass spectra acquired for these crosslinked species are being examined as a function of crosslinker identity, site(s) of crosslinking, and precursor charge state. Results from these model studies and observations from actual experimental systems are being incorporated into the MS2Assign software to enhance our ability to effectively use chemical crosslinking in protein complex determination.
A numerical screening study of the interaction between a penetrator and a geological target with a preformed hole has been carried out to identify the main parameters affecting the penetration event. The planning of the numerical experiment was based on the orthogonal array OA(18,7,3,2), which allows 18 simulation runs with 7 parameters at 3 levels each. The strength of 2 of the array allows also for two-factor interaction studies. The seven parameters chosen for this study are: penetrator offset, hole diameter, hole taper, vertical and horizontal velocity of the penetrator, angle of attack of the penetrator and target material. The analysis of the simulation results has been based on main effects plots and analysis of variance (ANOVA), and it has been performed using three metrics: the maximum values of the penetration depth, penetrator deceleration and plastic strain in the penetrator case. This screening study shows that target material has a major influence on penetration depth and penetrator deceleration, while penetrator offset has the strongest effect on the maximum plastic strain.
The Surface Evolver was used to compute the equilibrium microstructure of random soap foams with bidisperse cell-size distributions and to evaluate topological and geometric properties of the foams and individual cells. The simulations agree with the experimental data of Matzke and Nestler for the probability {rho}(F) of finding cells with F faces and its dependence on the fraction of large cells. The simulations also agree with the theory for isotropic Plateau polyhedra (IPP), which describes the F-dependence of cell geometric properties, such as surface area, edge length, and mean curvature (diffusive growth rate); this is consistent with results for polydisperse foams. Cell surface areas are about 10% greater than spheres of equal volume, which leads to a simple but accurate relation for the surface free energy density of foams. The Aboav-Weaire law is not valid for bidisperse foams.
Bulk migration of particles towards regions of lower shear occurs in suspensions of neutrally buoyant spheres in Newtonian fluids undergoing creeping flow in the annular region between two rotating, coaxial cylinders (a wide-gap Couette). For a monomodal suspension of spheres in a viscous fluid, dimensional analysis indicates that the rate of migration at a given concentration should scale with the square of the sphere radius. However, a previous experimental study showed that the rate of migration of spherical particles at 50% volume concentration actually scaled with the sphere radius to approximately the 2.9 power.
Three nested molybdenum wire arrays with initial outer diameters of 45, 50, and 55 mm were imploded by the - 20 MA, 90 ns rise-time current pulse of Sandia's Z accelerator. The implosions generated Mo plasmas with {approx} 10% of the array's initial mass reaching Ne-like and nearby ionization stages. These ions emitted 2-4 keV L-shell x rays with radiative powers approaching 10 TW. Mo L-shell spectra with axial and temporal resolution were captured and have been analyzed using a collisional-radiative model. The measured spectra indicate significant axial variation in the electron density, which increases from a few times 10{sup 20} cm{sup -3} at the cathode up to - 3 x 10{sup 21} cm{sup -3} near the middle of the 20 mm plasma column (8 mm from the anode). Time-resolved spectra indicate that the peak electron density is reached before the peak of the L-shell emission and decreases with time, while the electron temperature remains within 10% of 1.7 keV over the 20-30 ns L-shell radiation pulse. Finally, while the total yield, peak total power, and peak L-shell power all tended to decrease with increasing initial wire array diameters, the L-shell yield and the average plasma conditions varied little with the initial wire array diameter.
The proposed Yucca Mountain repository is anticipated to be the first facility for long-term disposal of commercial spent nuclear fuel and high-level radioactive waste in the United States. The facility, located in the southern Nevada desert, is currently in the planning stages with initial exploratory excavations completed. It is an underground facility mined into the tuffaceous volcanic rocks that sit above the local water table. The focus of the work described in this paper is the development of radionuclide absorbers or 'getter' materials for neptunium (Np), iodine (I), and technetium (Tc) for potential deployment in the repository. 'Getter' materials retard the migration of radionuclides through sorption, reduction, or other chemical and physical processes, thereby slowing or preventing the release and transport of radionuclides. An overview of the objectives and approaches utilized in this work with respect to materials selection and modeling of ion 'getters' is presented. The benefits of the 'getter' development program to the United States Department of Energy (US DOE) are outlined.
We have investigated the potential for intense particle beam surface modification to improve the mechanical properties of materials commonly used in the human body for contact surfaces in, for example, hip and knee implants. The materials studied include Ultra-High Molecular Weight Polyethylene (UHMWPE), Ti-6Al-4Al (titanium alloy), and Co-Cr-Mo alloy. Samples in flat form were exposed to both ion and electron beams (UHMWPE), and to ion beam treatment (metals). Post-analysis indicated a degradation in bulk properties of the UHMWPE, except in the case of the lightest ion fluence tested. A surface-alloyed Hf/Ti layer on the Ti-6Al-4V is found to improve surface wear durability, and have favorable biocompatibility. A promising nanolaminate ceramic coating is applied to the Co-Cr-Mo to improve surface hardness.
Proposed for publication in Association for Computing Machinery Transactions on Mathematical Software.
ODRPAC (TOMS Algorithm 676) has provided a complete package for weighted orthogonal distance regression for many years. The code is complete with user selectable reporting facilities, numerical and analytic derivatives, derivative checking, and many more features. The foundation for the algorithm is a stable and efficient trust region Levenberg-Marquardt minimizer that exploits the structure of the orthogonal distance regression problem. ODRPAC95 is a modification of the original ODRPAC code that adds support for bound constraints, uses the newer Fortran 95 language, and simplifies the interface to the user called subroutine.
We consider the accuracy of predictions made by integer programming (IP) models of sensor placement for water security applications. We have recently shown that IP models can be used to find optimal sensor placements for a variety of different performance criteria (e.g. minimize health impacts and minimize time to detection). However, these models make a variety of simplifying assumptions that might bias the final solution. We show that our IP modeling assumptions are similar to models developed for other sensor placement methodologies, and thus IP models should give similar predictions. However, this discussion highlights that there are significant differences in how temporal effects are modeled for sensor placement. We describe how these modeling assumptions can impact sensor placements.
A focused ion beam (FIB) is used to accurately sculpt predetermined micron-scale, curved shapes in a number of solids. Using a digitally scanned ion beam system, various features are sputtered including hemispheres and sine waves having dimensions from 1-50 {micro}m. Ion sculpting is accomplished by changing pixel dwell time within individual boustrophedonic scans. The pixel dwell times used to sculpt a given shape are determined prior to milling and account for the material-specific, angle-dependent sputter yield, Y({theta}), as well as the amount of beam overlap in adjacent pixels. A number of target materials, including C, Au and Si, are accurately sculpted using this method. For several target materials, the curved feature shape closely matches the intended shape with milled feature depths within 5% of intended values.
Ccaffeine is a Common Component Architecture (CCA) framework devoted to high-performance computing. In this note we give an overview of the system features of Ccaffeine and CCA that support component-based HPC application development. Object-oriented, single-threaded and lightweight, Ccaffeine is designed to get completely out of the way of the running application after it has been composed from components. Ccaffeine is one of the few frameworks, CCA or otherwise, that can compose and run applications on a parallel machine interactively and then automatically generate a static, possibly self-tuning, executable for production runs. Users can experiment with and debug applications interactively, improving their productivity. When the application is ready, a script is automatically generated, parsed and turned into a static executable for production runs. Within this static executable, dynamic replacement of components can be performed by self-tuning applications.
Large-scale three dimensional Discrete Element simulations of granular flow in a modified split-bottom Couette cell for packs of up to 180,000 mono-disperse spheres are presented and compared with experiments. We find that the velocity profiles collapse onto a universal curve not only at the surface but also in the bulk of the pack until slip between layers becomes significant. In agreement with experiment, we find similar relations between the cell geometry and parameters involved in rescaling the velocities at the surface and in the bulk. Likewise, a change in the shape of the shear zone is observed as predicted for tall packs once the center of the shear zone is correctly defined; although the transition does not appear to be first order. Finally, the effect of cohesion is considered as a means to test the theoretical predictions.
In recent years, several integer programming models have been proposed to place sensors in municipal water networks in order to detect intentional or accidental contamination. Although these initial models assumed that it is equally costly to place a sensor at any place in the network, there clearly are practical cost constraints that would impact a sensor placement decision. Such constraints include not only labor costs but also the general accessibility of a sensor placement location. In this paper, we extend our integer program to explicitly model the cost of sensor placement. We partition network locations into groups of varying placement cost, and we consider the public health impacts of contamination events under varying budget constraints. Thus our models permit cost/benefit analyses for differing sensor placement designs. As a control for our optimization experiments, we compare the set of sensor locations selected by the optimization models to a set of manually-selected sensor locations.
Electrical operation of III-Nitride light emitting diodes (LEDs) with photonic crystal structures is demonstrated. Employing photonic crystal structures in III-Nitride LEDs is a method to increase light extraction efficiency and directionality. The photonic crystal is a triangular lattice formed by dry etching into the III-Nitride LED. A range of lattice constants is considered (a {approx} 270-340nm). The III-Nitride LED layers include a tunnel junction providing good lateral current spreading without a semi-absorbing metal current spreader as is typically done in conventional III-Nitride LEDs. These photonic crystal III-Nitride LED structures are unique because they allow for carrier recombination and light generation proximal to the photonic crystal (light extraction area) yet displaced from the absorbing metal contact. The photonic crystal Bragg scatters what would have otherwise been guided modes out of the LED, increasing the extraction efficiency. The far-field light radiation patterns are heavily modified compared to the typical III-Nitride LED's Lambertian output. The photonic crystal affects the light propagation out of the LED surface, and the radiation pattern changes with lattice size. LEDs with photonic crystals are compared to similar III-Nitride LEDs without the photonic crystal in terms of extraction, directionality, and emission spectra.
Experimental evidence suggests that the energy balance between processes in play during wire array implosions is not well understood. In fact the radiative yields can exceed by several times the implosion kinetic energy. A possible explanation is that the coupling from magnetic energy to kinetic energy as magnetohydrodynamic plasma instabilities develop provides additional energy. It is thus important to model the instabilities produced in the after implosion stage of the wire array in order to determine how the stored magnetic energy can be connected with the radiative yields. To this aim three-dimensional hybrid simulations have been performed. They are initialized with plasma radial density profiles, deduced in recent experiments [C. Deeney et al., Phys. Plasmas 6, 3576 (1999)] that exhibited large x-ray yields, together with the corresponding magnetic field profiles. Unlike previous work, these profiles do not satisfy pressure balance and differ substantially from those of a Bennett equilibrium. They result in faster growth with an associated transfer of magnetic energy to plasma motion and hence kinetic energy.
Pulsed power driven metallic wire-array Z pinches are the most powerful and efficient laboratory x-ray sources. Furthermore, under certain conditions the soft x-ray energy radiated in a 5 ns pulse at stagnation can exceed the estimated kinetic energy of the radial implosion phase by a factor of 3 to 4. A theoretical model is developed here to explain this, allowing the rapid conversion of magnetic energy to a very high ion temperature plasma through the generation of fine scale, fast-growing m=0 interchange MHD instabilities at stagnation. These saturate nonlinearly and provide associated ion viscous heating. Next the ion energy is transferred by equipartition to the electrons and thus to soft x-ray radiation. Recent time-resolved iron spectra at Sandia confirm an ion temperature T{sub i} of over 200 keV (2 x 10{sup 9} degrees), as predicted by theory. These are believed to be record temperatures for a magnetically confined plasma.
Bayesian medical monitoring is a concept based on using real-time performance-related data to make statistical predictions about a patient's future health. The following paper discusses the fundamentals behind the medical monitoring concept and the application to monitoring the health of nuclear reactors. Necessary assumptions are discussed regarding distributions and failure-rate calculations. A simple example is performed to illustrate the effectiveness of the methods. The methods perform very well for the thirteen subjects in the example, with a clear failure sequence identified for eleven of the subjects.