Publications

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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.

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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.

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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.

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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.

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This report summarizes the results of a five-year effort to understand the mechanisms and develop models that predict the corrosion of refractories in oxygen-fuel glass-melting furnaces. Thermodynamic data for the Si-O-(Na or K) and Al-O-(Na or K) systems are reported, allowing equilibrium calculations to be performed to evaluate corrosion of silica- and alumina-based refractories under typical furnace operating conditions. A detailed analysis of processes contributing to corrosion is also presented. Using this analysis, a model of the corrosion process was developed and used to predict corrosion rates in an actual industrial glass furnace. The rate-limiting process is most likely the transport of NaOH(gas) through the mass-transport boundary layer from the furnace atmosphere to the crown surface. Corrosion rates predicted on this basis are in better agreement with observation than those produced by any other mechanism, although the absolute values are highly sensitive to the crown temperature and the NaOH(gas) concentration at equilibrium and at the edge of the boundary layer. Finally, the project explored the development of excimer laser induced fragmentation (ELIF) fluorescence spectroscopy for the detection of gas-phase alkali hydroxides (e.g., NaOH) that are predicted to be the key species causing accelerated corrosion in these furnaces. The development of ELIF and the construction of field-portable instrumentation for glass furnace applications are reported and the method is shown to be effective in industrial settings.

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The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.

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This paper describes the development of a set of software tools useful for analyzing ultra-wideband (UWB) antennas and structures. These tools are used to perform finite difference time domain (FDTD) simulation of a conical antenna with continuous wave (CW) and UWB pulsed excitations. The antenna is analyzed using spherical coordinate-based FDTD equations that are derived from first principles. The simulation results for CW excitation are compared to simulation and measured results from published sources; the results for UWB excitation are new.

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This document contains a description of the verification and validation process used for the RADTRAN 5.5 code. The verification and validation process ensured the proper calculational models and mathematical and numerical methods were used in the RADTRAN 5.5 code for the determination of risk and consequence assessments. The differences between RADTRAN 5 and RADTRAN 5.5 are the addition of tables, an expanded isotope library, and the additional User-Defined meteorological option for accident dispersion. 3

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