Publications

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The development of thin batteries has presented several interesting problems which are not seen in traditional battery sizes. As the size of a battery reaches a minimum, the usable capacity of the battery decreases due to the fact that the major constituent of the battery becomes the package and separator. As the size decreases, the volumetric contribution from the package and separator increases. This can result in a reduction of capacity from these types of batteries of nearly all of the available power. The development of a method for directly printing the battery layers, including the package, in place would help to alleviate this problem. The technology used in this paper to directly print battery components is known as robocasting and is capable of direct writing of slurries in complex geometries. This method is also capable of conformally printing on three dimensional surfaces, opening up the possibility of novel batteries based on tailoring battery footprints to conform to the available substrate geometry. Interfacial resistance can also be reduced by using the direct write method. Each layer is printed in place on the battery stack instead of being stacked one at a time. This ensures an intimate contact and seal at every interface within the cell. By limiting the resistance at these interfaces, we effectively help increase the useable capacity of our battery through increase transport capability. We have developed methodology for printing several different separator materials for use in a lithium cell. When combined with a printable cathode comprised of LiFePO{sub 4} (as seen in Figure 1) and a lithium anode, our battery is capable of delivering a theoretical capacity of 170 mAh g{sup -1}. This capacity is diminished by transport phenomena within the cell which limit the transport rate of the lithium ions during the discharge cycle. The material set chosen for the printable separator closely resemble those used in commercially available separators in order to keep the transport rates high within the cell during charge and discharge. In order to evaluate the effect of each layer being printed using the robocasting technique, coin cells using printed separator materials were assembled and cycled vs. Li/Li{sup +}. This allows for the standardization of a test procedure in order to evaluate each layer of a printed cell one layer at a time. A typical charge/discharge curve can be seen in Figure 2 using a printed LiFePO{sub 4} cathode and a printed separator with a commercial Celgard separator. This experiment was run to evaluate the loss in capacity and slowdown of transport within the cell due to the addition of the printed separator. This cell was cycled multiple times and showed a capacity of 75 mAh/g. The ability for this cell to cycle with good capacity indicates that a fully printable separator material is viable for use in a full lithium cell due to the retention of capacity. Most of the fully printed cathode and separator cells exhibit working capacities between 65 and 95 mAh/g up to this point. This capacity should increase as the efficiency of the printed separator increases. The ability to deposit each layer within the cell allows for intimate contact of each layer and ensures for a reduction of interfacial impedance of each layer within the cell. The overall effect of printing multiple layers within the cell will be an overall increase in the ionic conductivity during charge and discharge cycles. Several different polymer membranes have been investigated for use as a printed separator. The disadvantage of using polymer separators or solid electrolyte batteries is that they have relatively low conductivities at room temperature (10{sup -6} - 10{sup -8} S cm{sup -1}). This is orders of magnitude lower than the typically accepted 10{sup -3} S cm{sup -1} needed for proper ionic transport during battery discharge Because of their low conductivity, typical polymer separators such as polyethylene oxide (PEO) have a normal operational temperature well above ambient. At elevated temperature the conductivity of these polymers increases. These polymer membranes are, however, ideal for printable applications due to their ease of fabrication using the robocasting process and their ability to conform to surfaces uniformly. While the ability to print cathodes and separators is advantageous as a technology, several of the components still need to be fully optimized. The overall design for the full printed lithium cell can be seen in Figure 3. The printed cathode and separator will interface with a printed anode and current collector, using the LiFePO{sub 4} cycling to plate out a metallic lithium anode on the current collector during cycling. The ability to print every layer of the cell conformally using the robocasting technique will allow for ultimate flexibility in the application of a printed battery.

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Analysts working at the International Data Centre in support of treaty monitoring through the Comprehensive Nuclear-Test-Ban Treaty Organization spend a significant amount of time reviewing hypothesized seismic events produced by an automatic processing system. When reviewing these events to determine their legitimacy, analysts take a variety of approaches that rely heavily on training and past experience. One method used by analysts to gauge the validity of an event involves examining the set of stations involved in the detection of an event. In particular, leveraging past experience, an analyst can say that an event located in a certain part of the world is expected to be detected by Stations A, B, and C. Implicit in this statement is that such an event would usually not be detected by Stations X, Y, or Z. For some well understood parts of the world, the absence of one or more 'expected' stations - or the presence of one or more 'unexpected' stations - is correlated with a hypothesized event's legitimacy and to its survival to the event bulletin. The primary objective of this research is to formalize and quantify the difference between the observed set of stations detecting some hypothesized event, versus the expected set of stations historically associated with detecting similar nearby events close in magnitude. This Station Set Residual can be quantified in many ways, some of which are correlated with the analysts determination of whether or not the event is valid. We propose that this Station Set Residual score can be used to screen out certain classes of 'false' events produced by automatic processing with a high degree of confidence, reducing the analyst burden. Moreover, we propose that the visualization of the historically expected distribution of detecting stations can be immediately useful as an analyst aid during their review process.

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To test the hypothesis that high quality 3D Earth models will produce seismic event locations which are more accurate and more precise, we are developing a global 3D P wave velocity model of the Earth's crust and mantle using seismic tomography. In this paper, we present the most recent version of our model, SALSA3D (SAndia LoS Alamos) version 1.4, and demonstrate its ability to reduce mislocations for a large set of realizations derived from a carefully chosen set of globally-distributed ground truth events. Our model is derived from the latest version of the Ground Truth (GT) catalog of P and Pn travel time picks assembled by Los Alamos National Laboratory. To prevent over-weighting due to ray path redundancy and to reduce the computational burden, we cluster rays to produce representative rays. Reduction in the total number of ray paths is > 55%. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified two layer crustal model derived from the Crust 2.0 model over a uniform AK135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only around areas with significant velocity changes from the starting model. At each grid refinement level except the last one we limit the number of iterations to prevent convergence thereby preserving aspects of broad features resolved at coarser resolutions. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data. This scheme is computationally expensive, so we use a distributed computing framework based on the Java Parallel Processing Framework, providing us with {approx}400 processors. Resolution of our model is assessed using a variation of the standard checkerboard method, as well as by directly estimating the diagonal of the model resolution matrix based on the technique developed by Bekas, et al. We compare the travel-time prediction and location capabilities of this model over standard 1D models. We perform location tests on a global, geographically-distributed event set with ground truth levels of 5 km or better. These events generally possess hundreds of Pn and P phases from which we can generate different realizations of station distributions, yielding a range of azimuthal coverage and proportions of teleseismic to regional arrivals, with which we test the robustness and quality of relocation. The SALSA3D model reduces mislocation over standard 1D ak135, especially with increasing azimuthal gap. The 3D model appears to perform better for locations based solely or dominantly on regional arrivals, which is not unexpected given that ak135 represents a global average and cannot therefore capture local and regional variations.

Recently, Sandia National Laboratories and General Motors cooperated on the development of the Biofuels Deployment Model (BDM) to assess the feasibility, implications, limitations, and enablers of producing 90 billion gallons of ethanol per year by 2030. Leveraging the past investment, a decision support model based on the BDM is being developed to assist investors, entrepreneurs, and decision makers in evaluating the costs and benefits associated with biofuels development in the U.S.-Mexico border region. Specifically, the model is designed to assist investors and entrepreneurs in assessing the risks and opportunities associated with alternative biofuels development strategies along the U.S.-Mexico border, as well as, assist local and regional decision makers in understanding the tradeoffs such development poses to their communities. The decision support model is developed in a system dynamics framework utilizing a modular architecture that integrates the key systems of feedstock production, transportation, and conversion. The model adopts a 30-year planning horizon, operating on an annual time step. Spatially the model is disaggregated at the county level on the U.S. side of the border and at the municipos level on the Mexican side. The model extent includes Luna, Hildalgo, Dona Anna, and Otero counties in New Mexico, El Paso and Hudspeth counties in Texas, and the four munipos along the U.S. border in Chihuahua. The model considers a variety of feedstocks; specifically, algae, gitropha, castor oil, and agricultural waste products from chili and pecans - identifying suitable lands for these feedstocks, possible yields, and required water use. The model also evaluates the carbon balance for each crop and provides insight into production costs including labor demands. Finally, the model is fitted with an interactive user interface comprised of a variety of controls (e.g., slider bars, radio buttons), descriptive text, and output graphics allowing stakeholders to directly explore the tradeoffs between alternative biofuels development scenarios.

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