Sewer System Management Plan

The focus of this document is to record the learning and process development achieved by the completion of the Nano-Engineering of Detector Surfaces to Offer Unprecedented Imager Sensitivity to Soft X-rays and Low Energy Electrons LDRD. The goal of this effort was to study different silicon detector surface preparation methods such as ion implant parameters, and the addition of a quantum 2-layer superlattice. Enabling the preparation of the surface of silicon detectors (front side illuminated or bonded backside illuminated) increases the responsivity of the diode to shallowly absorbed photons. This increased sensitivity in turn allows for greater fidelity in imaging events that emit low soft X-rays or low energy electrons. Prior work has focused on passivating the surface of a silicon detectors with thin layers (tens of nm thick) of materials to reduce surface recombination sites. Measurements of visible light quantum efficiency, electron responsivity, and pulsed x-ray response indicate that detectors with a 2- layer superlattice enjoy a significant benefit over equivalent detectors using an ion implant at the illuminated surface. ACKNOWLEDGEMENTS The research described in this LDRD was carried out at Sandia National Laboratories, under a contract with the Department of Energy, and at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Finite-element model to predict roll-separation force and defects during rolling of U-10Mo alloys

Simulations of ion transport in ion-conducting polymers such as ionomers are challenging because dynamical processes relevant to the ion transport occur across many orders of magnitude in time. Additionally, designing improved ionomers requires an understanding of how both polymer architecture and ionomer morphology affect ion dynamics. To build a better understanding of the relationships among ionomer chemistry, morphology, and ion transport, we have performed a series of molecular dynamics simulations and connected aspects of these simulations with experiment. In this talk I will describe our recent results on two different ionic polymers. The first is a series of precise poly(ethylene-co-acrylic acid) ionomers, which have acid groups precisely spaced along the polymer backbone. These ionomers form nanoscale ionic aggregates with morphologies dependent on the spacer length between acid groups on the polymer backbone and on mobile ion concentration. Recent atomistic MD simulations of these ionomers are in good agreement with quasi-elastic neutron scattering data at short time scales. The comparison with experiment validates the dynamics in the simulations, which we then use to probe ion dynamics at longer time scales. We also performed coarse-grained simulations to provide insight into ion transport mechanisms at longer times. The second system is a sulfonated poly(phenylene), which conducts protons when hydrated. Atomistic simulations of the structure are in good agreement with NMR spin diffusion measurements of domain sizes and with X-ray scattering. At low sulfonation and hydration levels, clusters are more elongated in shape and poorly connected throughout the system. As the degree of sulfonation and water content are increased, the clusters became more spherical, and a fully percolated ionic domain is formed. I will discuss the connections among the hydrophilic domain morphology, the state of the hydrogen bonding network, and the conductivity in these polymers. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. Figure 1

This presentation explores the acoustic black hole (ABH) effect achieved through variation of duct wall impedance. Unlike the method of Mironov and Pislyakov, which utilizes tapered annular rings within the duct to achieve the ABH effect, this approach leverages mechanical impedance variation to create the desired acoustic behavior. By engineering the impedance profile along the duct wall, an axially decreasing local phase speed results that mimics the event horizon of a black hole, causing sound waves to be significantly attenuated and trapped. Governing equations are derived and solved using both the WKB approximation and numerical methods. The solutions reveal that specific impedance profiles can effectively decelerate and absorb acoustic waves, resulting in substantial reduction in sound transmission. Verification is performed using the fully coupled structural acoustic finite element algorithm Sierra/SD. This research further paves the way for the development of innovative acoustic materials and devices which utilize ABH principles to achieve enhanced noise control and acoustic wave manipulation. [Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE-NA-0003525.]

Lithium metal anodes are considered a direct upgrade to commercial anode materials due to their high gravimetric density and low coulombic efficiency. However, their implementation into crucial applications such as electric vehicles has been hindered by safety issues due to long-term cell degradation. Repeated plating and stripping of the lithium anode encourages dendrite growth and the formation of dead lithium, which eventually lead to capacity loss, cell failure, and fire. Application of stack pressure during cell manufacturing has been shown to mitigate dendrite growth and increase cell stability; however, the simultaneous impacts of pressure application on lithium deposition and plastic deformation of the anode surface are not well understood. In this work, we present a novel method for coupling the mechanical deformation and electrochemical deposition across a lithium anode impacted by external pressure. We develop a 3D, transient, finite-element model of lithium plating and stripping at the mesoscale. Application of stack pressure introduces a nonconformal, highly stressed contact interface between the anode and polymer separator, which induces local ion transport limitations. The electrochemical response across this interface is evaluated, and the lithium protrusion is incrementally adjusted to model plating or stripping. Cumulative interfacial movement over a full charge-discharge cycle is thus tracked. The interfacial response is studied with respect to applied stack pressure and assumed lithium yield strength. Lithium plastic deformation and separator pore closure are shown to greatly affect the propensity of stripping/plating across the anode surface. The lithium yield strength assumption is found to be crucial for accurately predicting deposition behavior. Through this work, the electrochemical and mechanical impacts of stack pressure on mitigation of dendrite growth are revealed.Supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.

Additive manufacturing (AM) is a cost-effective and versatile method for rapid prototyping and manufacturing flexible electronics components. Aerosol jet printing (AJP) is a direct write AM technique that can print features down to 10 microns. The benefits of manufacturing with AJP can be deepened when combined with electrodeposition, unlocking the ability to pattern materials that are not directly printable. In quantum computing systems, superconductivity is a crucial aspect in many areas. Superconducting interconnects allow for low loss and detection of low power signals coming in and out of cryosystems, and for low loss communications between quantum components inside cryosystems. Current quantum systems are limited by rigid cables that are configured in low densities, suffer from joule heating, and are hard to reform once placed. Some preliminary superconducting coaxial cables that exist suffer from extreme fragility and are not easily bent to shape. Rhenium (Re) exhibits superconductivity below its critical temperature of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6 K}$</tex> and can be electrodeposited onto conductive materials. In this work, we investigate the electrodeposition of Re onto aerosol jet-printed structures for applications in quantum systems. Herein, we demonstrate the AJP of gold (Au) and silver (Ag) nanoparticle inks onto flexible polyimide substrates succeeded by the electrochemical deposition of Re. The adhesion of the polyimide-Au/Ag-Re material stack was evaluated. The electrical properties and superconductivity of the films was evaluated to identify a repeatable and stable electrochemical deposition process. Given Re can corrode easily in the presence of oxygen and water, passivation of the Re coated traces is explored. Additively deposited SU8 and Norland Optical Adhesive (NOA) and electrodeposited tin (Sn) were evaluated for their ability to passivate the Re and maintain its superconductivity following both environmental and flexibility testing. This work demonstrates a promising approach for future fabrication of superconducting flexible interconnects for use in quantum computing applications to advance densification and reliability of quantum systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2025-04281A.

Regulating cation transmission at electrode interfaces is an essential function required for realizing storage based on multivalent working ions, including Mg and Ca. Cation transmission regulating interphases are believed to exist at both anode and cathodes surfaces for a host of electrolytes based on ethereal solvents, contributing to energetic barriers to cation accommodation at metal deposits and (de)insertion into cathodes. These interphases are derived from supporting electrolyte anion, solvent or impurity decomposition or more complex synergistic reactions. Weakly coordinating anions, of defined reductive/oxidative stability in highly purified form, provide an opportunity to explore the origin and consequences of reactivity and interphase formation. In this presentation, we describe several examples where origin of reactivity has been successfully probed through electrolyte constituent control and application of operando (e.g., electrochemical X-ray absorption) and ex situ (e.g., analytical transmission electron microscopy) methods. Results highlight critical phases and distributions responsible for cation transport and provide new insight into directing interphase formation to facilitate cation transport enhancing electrode performance. This work was supported as part of the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the Prime Contract and oversees contractor operations at Sandia National Laboratories, California. Activities at this multi-program engineering and science laboratory support the nuclear weapons stockpile program, energy and environmental research, homeland security, micro-and nanotechnologies, and basic science and engineering research. The U.S. Department of Energy’s National Nuclear Security Administration and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report provides a summary of environmental monitoring of information and compliance activities that occurred at Sandia National Laboratories, California during calendar year 2023 unless noted otherwise. General site and environmental program information is also included. This report was prepared in accordance with DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting.

Harsh shock and vibration environments are common in engineering applications. Mechanical metamaterials are showing significant potential as candidates for controlling wave propagation and isolating sensitive structural components, but require proper design of their complex microstructures. In this talk we will present time and frequency-domain strategies for Partial Differential Constrained (PDE)-constrained design optimization of locally resonant elastic/acoustic metamaterials. We will present a variety of notch filter resonators and split ring cylinder/sphere geometries that can be easily optimized for wave control applications, along with fabrication details involving multi-material additive manufacturing. A frequency-domain approach will be presented for band-gap or notch filter materials, and a time-domain strategy for transient shock environments. As the metamaterial structures typically involve concentrated masses and elastic connections, an optimization strategy involving 3D simple shapes will be presented. [Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. With main facilities in Albuquerque, N.M., and Livermore, C.A., Sandia has major R&amp;D responsibilities in national security, energy and environmental technologies, and economic competitiveness.]

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, Tonopah Test Range (SNL/TTR) in Nevada and Sandia National Laboratories, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Activities at SNL/TTR are conducted in support of U.S. Department of Energy weapons programs and have operated at the site since 1957. SNL/KTF has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection, restoration, and monitoring programs in place at SNL/TTR and SNL/KTF during calendar year 2020. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting, and has been approved for public distribution.

Municipalities across the United States face the challenge of sanitary sewer overflows (SSOs), events which pose serious public health and environmental problems. SSOs are unintentional discharges of untreated sewage from the sewer system that can occur as a result of rain derived infiltration and inflow (RDII). SSOs can be reduced by decreasing RDII into the collection system, increasing conveyance capacity, and lessening peak flow through detention storage facilities. However, the sheer length of sanitary sewer systems makes the implementation of these controls very costly. Thus, a novel approach is required to a posteriori design cost-effective rehabilitation options. This study describes a multiobjective evolutionary optimization approach to design a rehabilitation strategy for SSOs reduction in the eastern subsewershed of the San Antonio Water System (SAWS) sewer network. The subsewershed consists of 3,304 conduits connected via 3,155 manholes to form a network that is 160.8 miles long and services an area covering 20.4 square miles with an approximate population of 36,000 inhabitants. The hydraulic behavior of the system is simulated using the EPA Storm Water Management Model (EPA-SWMM) hydraulic model, and the number of SSOs is calculated as the number of nodes that oveflow during the 5 year–6 hours design storm. The optimization method utilized was the Nondominated Sorting Genetic Algorithm (NSGA II) to generate near Pareto-optimal solutions that express tradeoffs between the number of SSOs and cost. The NSGA II was implemented in JAVA, where each individual is represented as a set of vectors that is composed of three sets of genes. The decision variables include the number of pipe segments to be replaced, the location of the first link to be replaced, and the amount of commercial diameter increase from existing pipe diameter. The use of the optimization approach is expected to generate more efficient solutions in comparison to typical engineering approaches that look into solving a localized SSOs problems in sanitary sewer networks.

The annual program report provides detailed information about all aspects of the Sandia National Laboratories, California (SNL/CA) Chemical Management Program. It functions as supporting documentation to the SNL/CA Environmental Management System Program Manual. This program annual report describes the activities undertaken during the calender past year, and activities planned in future years to implement the Chemical Management Program, one of six programs that supports environmental management at SNL/CA. SNL/CA is responsible for tracking chemicals (chemical and biological materials), providing Material Safety Data Sheets (MSDS) and for regulatory compliance reporting according to a variety of chemical regulations. The principal regulations for chemical tracking are the Emergency Planning Community Right-to-Know Act (EPCRA) and the California Right-to-Know regulations. The regulations, the Hazard Communication/Lab Standard of the Occupational Safety and Health Administration (OSHA) are also key to the CM Program. The CM Program is also responsible for supporting chemical safety and information requirements for a variety of Integrated Enabling Services (IMS) programs primarily the Industrial Hygiene, Waste Management, Fire Protection, Air Quality, Emergency Management, Environmental Monitoring and Pollution Prevention programs. The principal program tool is the Chemical Information System (CIS). The system contains two key elements: the MSDS library and the chemical container-tracking database that is readily accessible to all Members of the Sandia Workforce. The primary goal of the CM Program is to ensure safe and effective chemical management at Sandia/CA. This is done by efficiently collecting and managing chemical information for our customers who include Line, regulators, DOE and ES and H programs to ensure compliance with regulations and to streamline customer business processes that require chemical information.

We study the use of nanoelectrode arrays (NEAs), consisting of billions/cm2 of ~ 75 nm diameter electrodes, for the electrochemical analysis of ionic halogen species in water. Such NEA sensors were previously demonstrated to detect part-per-billion (ppb) levels of Pb-ions in aqueous solutions without supporting electrolytes. Briefly, the individual electrodes in the NEA can be tailored with sufficient separation coupled with pore-depth control so that each experiences non-overlapping hemispherical diffusion zones within which the ionic flux of an analyte is independent of time. This geometry is well-suited for trace-level detection, as fast voltage sweeps result in a large and steady-state current density. With optimized design, the additive response from the plethora of nanoelectrodes leads to an orders-of-magnitude analytical advantage for electrochemical detection compared to conventional (mm) sized disc electrodes using sweep or pulse voltammetric techniques. NEAs are fabricated by anodizing RF-sputter deposited Al films on a substrate-of-choice, resulting in billions/cm2 tailored with controllable pore diameters. Each nanopore is partially filled via electrochemical plating with an appropriate working electrode material, such as Au, Pt or Ni. A thin W film is beneath the nanopore template for both processing assistance and to provide a backside electrical contact in parallel to every nanoelectrode. In the case that the NEA is recessed within the porous alumina, a thin conducting film can be added to the topside to function as a counter/pseudo-reference electrode. In some situations, the counter electrode can also serve as an ion collector, preconcentrating ionic species near the pore openings prior to beginning an electrochemical measurement. Using such NEA sensors, we will demonstrate trace detection levels for both Cl and I ionic species in water, and compare the limits-of-detection with conventional electrodes. In addition, we explore the possibility of using NEA sensors to detect halogens in the gas phase. By manipulating the NEA structure, the monitoring capability may be extended to gas phase detection of Cl2 or I2. Such gas-phase detection is possible by utilizing the natural humidity in air condensing on the nanopore walls above the recessed working electrodes. Indirect sensing of such gases occurs after they dissolve in the pore water to form electrochemically detectable halogen species. Notably, the electrochemical measurement is achieved with simple, condensed humidity as the sole ionically conducting phase, without the need for a supporting electrolyte. This is because the high resistivity of water† is mitigated by the short ionic path length: the net solution resistance is small because of the sub-micron distance separating the NEA electrodes from the counter/pseudo-reference electrode sputtered upon the surface of the opposite (open) end of the pore. †The conductivity of humidity levels we consider in this study range from 10-6 S/m (humidity from DI water) to 10-3-10-4 S/m (conductivity range of natural humidity across the USA as monitored by the National Atmospheric Deposition Program’s National Trend Network). This work is supported by the Laboratory Directed Research and Development program at Sandia National Laboratories. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Binary-discrimination tasks useful to arms-control-treaty verification were performed by applying mathematical observer models used by the medical-imaging community. It is a difficult task, as the monitor needs to verify a measured object is a warhead while the host wants to prevent dissemination of sensitive information on their weapons. Inspection objects were classified by their projection data, without reconstructing an image, which often contains sensitive information. Furthermore, the models process data event-by-event, with only a scalar test statistic being updated before the observed data is purged from memory, preventing the aggregation of information which would be sensitive. Template matching models were developed from a set of calibration data on these objects, with the ultimate goal being to develop an observer model that stores only non-sensitive information sufficient for confirmation. These models were also analyzed in the presence of nuisance parameters — unknowns in the objects or imaging system that affect the projection data but aren't of interest to the discrimination task. Examples of these include object location and orientation. The Hotelling observer and channelized Hotelling observer were modeled and their benefits to information security analyzed. The Hotelling observer-the ideal linear observer when the statistics of the data are Gaussian-stores only a set of weights which are the product of the inverse average covariance matrix and difference in mean data between the two objects in the discrimination task. When testing a source, an inner product of the Hotelling weights and binned testing data is taken, resulting in a scalar that is thresholded to make a decision. If nuisance parameters are present, the mean and covariance matrix are found by averaging not only over the always present Poisson noise, but the nuisance parameter distributions as well. Hence, even if detector data is gathered from multiple realizations of an object, the Hotelling weights will be a single smeared out data set the size of the measured data. The Hotelling weights also sifts out all information other than the differences between the two objects. Hence, if the monitor was to gain access to the weights and apply the inverse to their test statistic, they could only back out a scaled version of the template, not the image. The channelized Hotelling observer-a common tool used in medical image quality assessment-was also investigated. This method drastically reduces the size of the data by applying a channeiizing matrix to the binned testing data set. An optimal set of weights for the channelized data can then be found, and the inner product between these weights and the channelized vector results in the scalar test statistic. Optimal performance is retained by optimizing the matrix to maximize the SNR2 between the test-statistic distributions for the two sources in the task. The channelized Hotelling observer gives the monitor access to multiple non-sensitive test statistics. In practice, the channelizing matrix could be implemented in hardware or software behind an information barrier. The addition of penalty terms to the channelized Hotelling observer offers further potential for this method. Individual channel performance could be penalized, leading to a large number of non-sensitive channels that the monitor can use to verify the channelization routine is working as described without gaining access to sensitive information. Noise could be added to the resulting channels, causing additional reduction of the total stored information. Finally, if the host can define what information in its object geometries is sensitive in advance, they could optimize the differences between the two objects in the task while penalizing out the sensitive information, creating a non-sensitive channeiizing matrix that could be shared with the monitor. To test these models, Monte Carlo simulations were performed with the GEANT4 toolkit. Photons were tracked from plutonium inspection objects developed by Idaho National Laboratory. We simulated the Fast-Neutron Imaging system designed by Oak Ridge National Laboratory and Sandia National Laboratories, which consists of 40×40 1cm2 liquid scintillator pixels with a plastic coded aperture. Observer models were evaluated using the area under the ROC curve. This work is supported by the Office of Defense Nuclear Nonproliferation Research and Development, Nuclear Weapon and Material Security Team. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. (SAND2015-10391A).

This SAND report provides the technical progress through April 2005 of the Sandia-led project, "Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling," funded by the DOE Office of Science Genomics:GTL 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 can be found at www.genomes-to-life.org Acknowledgment We want to gratefully acknowledge the contributions of: Grant Heffelfinger1*, Anthony Martino2, Brian Palenik6, Andrey Gorin3, Ying Xu10,3, Mark Daniel Rintoul1, Al Geist3, Matthew Ennis1, with Pratul Agrawal3, Hashim Al-Hashimi8, Andrea Belgrano12, Mike Brown1, Xin Chen9, Paul Crozier1, PguongAn Dam10, Jean-Loup Faulon2, Damian Gessler12, David Haaland1, Victor Havin4, C.F. Huang5, Tao Jiang9, Howland Jones1, David Jung3, Katherine Kang14, Michael Langston15, Shawn Martin1, Shawn Means1, Vijaya Natarajan4, Roy Nielson5, Frank Olken4, Victor Olman10, Ian Paulsen14, Steve Plimpton1, Andreas Reichsteiner5, Nagiza Samatova3, Arie Shoshani4, Michael Sinclair1, Alex Slepoy1, Shawn Stevens8, Charlie Strauss5, Zhengchang Su10, Ed Thomas1, Jerilyn Timlin1, WimVermaas13, Xiufeng Wan11, HongWei Wu10, Dong Xu11, Grover Yip8, Erik Zuiderweg8 *Author to whom correspondence should be addressed (gsheffe@sandia.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 13. Arizona State University 14. The Institute for Genomic Research 15. University of Tennessee 5 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-AC04-94AL8500.