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Results for “Lee Allen”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Basin and Range Investigation for Developing Geothermal Energy: Exploration Data

This data package includes exploration material from the Basin & Range Investigation for Developing Geothermal Energy [in Hidden Systems] project (BRIDGE), which is part of a broader initiative to advance the exploration of hidden geothermal resources in the Basin & Range Province of the western U.S. Data modalities include a helicopter-borne time-domain electromagnetic survey, magnetotellurics, 2-meter temperature measurements, ground-based gravity and legacy aeromagnetic surveys, geochemistry, geologic mapping, LiDAR analysis, 3D models, associated geospatial data, and a bibliography of existing data and references utilized in prospect characterization and conceptual modeling. Key files are in CSV, Geosoft, and Geotools formats. Please refer to READMEs for dataset-specific information. Where applicable, acquisition data and inversion models for a particular prospect or area of interest are organized separately. This BRIDGE data package is the product of a collaboration led by Sandia National Laboratories with partners from Geologica Geothermal Group, Inc., the U.S. Navy Geothermal Program Office, and consultants Steven Sewell (Australis Geoscience Ltd) and William Cumming (Cumming Geoscience). The project's areas of interest (AOIs) are based off priority areas of interest in the southwestern portion of the Nevada Play Fairway map, distribution across tectonic provinces, accessibility, and the project team's extensive experience in the region. AOIs cover about a dozen basins that include unexplored prospects, partially explored prospects, and some developed analogue resources that provide validation cases. Many unexplored and partially explored prospects are on U.S. Department of Defense (DoD) land, though adjacent lands are included as well.

15 GEOTHERMAL ENERGY↗

A New Theoretical Framework for Designing Ion Transport Pathways

The rapid transport of specific ions through matter is critical to energy storage, membrane separations, and health. However, commercial materials resist ion transport, lack specificity, or both, making ion transport costly and ineffective. Inspiration for new material designs can be taken from biology, where membrane transport proteins exert exquisite control over the specificity and rate of ion transport. The challenge in understanding and designing transport pathways is that ions often exchange their hydrating waters for direct contacts with atoms in the transport pathway. Despite intense study over decades, no theory exists to explain local ion binding and transport mechanisms and experiments cannot differentiate reliably between ions and water in binding sites. Here, we developed a new approach, based on quantum methods and extension of the quasi-chemical free energy theory, to understand and design pathways through materials for rapid transport of specific ions. Understanding ion transport mechanisms will significantly advance our nation’s ability to develop cost-effective materials for energy sustainability and therapeutics for health.

36 MATERIALS SCIENCE↗

Miscanthus × giganteus Responses to Nitrogen Fertilization and Harvest Timing in Illinois, USA

Renewable energy continues to be of interest in the USA due to concerns about the long-termed availability and the environmental impact of fossil fuels. Miscanthus × giganteus is a warm-season perennial bioenergy feedstock grass that has a long growing season, is high yielding, requires limited inputs, and will likely become an important renewable energy crop in the USA. This research studied the effects of N application rates and harvest timings on yields and biomass quality of a 4-year-old stand of M. × giganteus in Urbana, IL, USA. Plots received 0, 56, 112, 156, or 224 kg N ha –1 , and harvests were conducted at five dates between August and March in the 2009, 2010, and 2011 growing seasons. Miscanthus × giganteus production increased with N applications up to 112 kg ha –1 . Harvesting biomass before senescence, August through November, produced significantly more biomass compared to harvesting biomass after senescence. However, early harvest reduced biomass yields in the following years. Here, nitrogen fertilization compensated for the yield losses, but the yield gap between early and late harvest continually increased. Harvesting M. × giganteus after senescence optimized long-term productivity, reduced the need for N fertilization, and increased carbon and ash content in the harvested biomass, while harvesting before senescence not only removes N from the plant but also reduces remobilization of other nutrients and carbohydrates in autumn.

09 BIOMASS FUELS↗

Structural metamaterials with innate capacitive and resistive sensing

Interpenetrating lattices consist of two or more interwoven but physically separate sub-lattices with unique behaviors derived from their multi-body construction. If the sublattices are constructed or coated with an electrically conducting material, the close proximity and high surface area of the electrically isolated conductors allow the two lattices to interact electromagnetically either across the initial dielectric filled gap or through physical contact. Furthermore, changes in the size of the dielectric gap between the sub-lattices induced by deformation can be measured via capacitance or resistance, allowing a structurally competent lattice to operate as a force or deformation sensor. In addition to resistive and capacitive deformation sensing, this work explores capacitance as a fundamental metamaterial property and the environmental sensing behaviors of interpenetrating lattices.

Computational Solid Mechanics↗

Direct Mapping of Fluorine in Cation Disordered Rocksalt Cathodes

Cation-disordered rocksalt (DRX) oxides are promising candidates as next-generation cathodes for lithium-ion batteries. Partial fluorination of the DRX oxides enhances their cyclability. However, the lattice position, concentration, and spatial distribution of fluorine within DRX lattices remain elusive. Here, in this work, we use atom location by channeling-enhanced microanalysis, energy-dispersive X-ray spectroscopy, electron energy loss spectroscopy, and integrated differential phase contrast imaging in a scanning transmission electron microscope to gain atomic-level insights into DRX with nominal composition of Li 1.2 Mn 0.7 Ti 0.1 O 1.7 F 0.3 and Li 1.15 Ni 0.45 Ti 0.3 Mo 0.1 O 1.85 F 0.15 . We reveal that fluorine substitutes oxygen in the DRX lattices. The O/F ratio in terms of O+F = 2 is in the range from 1.92:0.08 to 1.82:0.18. Spatially, fluorine is distributed in the proximity of the Li-rich regions but distinct from lithium fluoride. Additionally, we observe that incorporation of fluorine in the DRX lattice induces a larger variation in cation–anion separation. These observations provide insight into the guided design of oxyfluoride DRX cathodes for high-performance batteries.

(S)TEM↗

A dataset of recorded electricity outages by United States county 2014–2022

In this Data Descriptor, we present county-level electricity outage estimates at 15-minute intervals from 2014 to 2022. By 2022 92% of customers in the 50 US States, Washington DC, and Puerto Rico are represented. These data have been produced by the Environment for Analysis of Geo-Located Energy Information (EAGLE-I TM ), a geographic information system and data visualization platform created at Oak Ridge National Laboratory to map the population experiencing electricity outages every 15 minutes at the county level. Although these data do not cover every US customer, they represent the most comprehensive outage information ever compiled for the United States. The rate of coverage increases through time between 2014 and 2022. We present a quantitative Data Quality Index for these data for the years 2018–2022 to demonstrate temporal changes in customer coverage rates by FEMA region and indicators of data collection gaps or other errors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Targeted engineering of camelina and pennycress seeds for ultrahigh accumulation of acetyl-TAG

Acetyl-TAG (3-acetyl-1,2-diacylglycerol), unique triacylglycerols (TAG) possessing an acetate group at the sn -3 position, exhibit valuable properties, such as reduced viscosity and freezing points. Previous attempts to engineer acetyl-TAG production in oilseed crops did not achieve the high levels found in naturally producing Euonymus seeds. Here, we demonstrate the successful generation of camelina and pennycress transgenic lines accumulating nearly pure acetyl-TAG at 93 mol% and 98 mol%, respectively. These ultrahigh acetyl-TAG synthesizing lines were created using gene-edited FATTY ACID ELONGASE1 ( FAE1 ) mutant lines as an improved genetic background to increase levels of acetyl-CoA available for acetyl-TAG synthesis mediated by the expression of EfDAcT, a high-activity diacylglycerol acetyltransferase isolated from Euonymus fortunei . Combining EfDAcT expression with suppression of the competing TAG-synthesizing enzyme DGAT1 further enhanced acetyl-TAG accumulation. These ultrahigh levels of acetyl-TAG exceed those in earlier engineered oilseeds and are equivalent or greater than those in Euonymus seeds. Imaging of lipid localization in transgenic seeds revealed that the low amounts of residual TAG were mostly confined to the embryonic axis. Similar spatial distributions of specific TAG and acetyl-TAG molecular species, as well as their probable diacylglycerol (DAG) precursors, provide additional evidence that acetyl-TAG and TAG are both synthesized from the same tissue-specific DAG pools. Remarkably, this ultrahigh production of acetyl-TAG in transgenic seeds exhibited minimal negative effects on seed properties, highlighting the potential for production of designer oils required for economical biofuel industries.

09 BIOMASS FUELS↗

Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms

Accelerator-based heterogeneous computing is the de facto standard in current and upcoming exascale machines. These heterogeneous resources empower computational scientists to select a machine or platform well-suited to their domain or applications. However, this diversity of machines also poses challenges related to programming model selection: inconsistent availability of programming models across different exascale systems, lack of performance portability for those programming models that do span several systems, and inconsistent performance between different models on a single platform. We explore these challenges on exascale-similar hardware, including AMD MI100 and NVIDIA A100 GPUs. By extending the sourceto-source compiler OpenARC, we demonstrate the power of automated translation of applications written in a single frontend programming model (OpenACC) into a variety of backend models (OpenMP, OpenCL, CUDA, HIP) that span the upcoming exascale environments. This translation enables us to compare performance within and across devices and to analyze programming model behavior with profiling tools.

Lambert, Jacob↗

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗

Artificial Intelligence-Enhanced, Multi-Level, Modular System Design

As Moore’s Law and Dennard Scaling come to an end, it is becoming increasingly important to develop non-von Neumann computing architectures that can perform low-power computing in the domains of scientific computing, artificial intelligence, embedded systems, and edge computing. Next-generation computing technologies, such as neuromorphic computing and quantum computing, have the potential to revolutionize computing. However, in order to make progress in these fields, it is necessary to fundamentally change the current computing paradigm by codesigning systems across all system level, from materials to software. Because skilled labor is limited in the field of next-generation computing, we are developing artificial intelligence-enhanced tools to automate the codesign and co-discovery of next-generation computers. Here, we develop a method called Modular and Multi-level MAchine Learning (MAMMAL) which is able to perform analog codesign and co-discovery across multiple system levels, spanning devices to circuits. We prototype MAMMAL by using it to design simple passive analog low-pass filters. We also explore methods to incorporate uncertainty quantification into MAMMAL and to accelerate MAMMAL by using emerging technologies, such as crossbar arrays. Ultimately, we believe that MAMMAL will enable rapid progress in developing next-generation computers by automating the codesign and co-discovery of electronic systems.

97 MATHEMATICS AND COMPUTING↗

A Theoretical Analysis on the Dynamic Behavior and Electromechanical Response of PZT

Piezoelectric materials are used as a power source in stockpile components for safety and reliability assurances. The objective of this project is to gain insights into the fundamental pressure-induced behavior and electromechanical response of lead zirconate titanate (PZT). Specifically, to establish the basis for an accurate, physics-based material model for robust model-based design to rapidly optimize PZT-based materials and components for performance studies. Established ab-initio methods are used to interrogate and understand the dynamic behavior of PZT as a function of composition (50/50, 65/35, 80/20, 95/5) and dopants (La, Nb) to overcome the costly and time-consuming experimental methodologies. New cold curves for pure and doped single-crystal PZT are obtained as the reference equation-of-state (EOS). A negligible change in the pressure responses was observed for the systems and strains studied. Dielectric and piezoelectric responses of pure and doped single-crystal PZT were also calculated as a function of pressure. For undoped PZT, there is a clear and orderly pressure and composition dependence. For doped PZT, there is a significant increase in the responses, but the behavior is very disordered and inconclusive.

36 MATERIALS SCIENCE↗

Density functional theory (DFT) study of UF 6 hydrolysis: reaction pathways, spectroscopy, and chemical kinetics

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the gas-phase reaction mechanism and associated chemical kinetics are poorly understood. During the performance period we undertook development of a state-of-the-art ab initio gas-phase chemical kinetics simulation workflow to model the hydrolysis of uranium hexafluroride (UF 6 ). In doing so, we addressed several outstanding issues in the theoretical treatment of uranium-containing systems. At the outset it was unclear how to generate accurate estimates of kinetic and thermodynamic data for U-containing chemical reactions. Generation of such data has been made routine. Prior to our work, the literature associated with UF 6 hydrolysis were disparate and inaccurate. This body of work provides a modern and comprehensive theoretical assessment of the reaction mechanism, molecular clustering towards deposition, and chemical kinetics. New methodological implementations and software integrations resulting from this work are also highlighted. As much as possible, our predictions were validated against experimental data including particle morphologies, vibrational spectroscopy, atomization enthalpies, and kinetic rate constants. Nevertheless, we were unable to reconcile kinetic measurements with high-accuracy simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Effect of Adsorbed Volatile Organic Compounds on an Ultrathin Water Film Measurement

Using surface plasmon resonance imaging (SPRi), we have recently shown for the first time the existence of a monolayer water film between droplets during dropwise condensation. This study examines the effect of adsorbed volatile organic compounds (VOCs) on the ultrathin film measurement using SPRi. Further, the work presents the proper surface-treatment process that enables measurements of the ultrathin water layer during high-speed imaging of dropwise condensation at 3000 frame per second. In this study, two methods were applied for cleaning the surface (gold-coated glass)—(1) standard cleaning procedure (SCP) using acetone, isopropyl alcohol, and deionized water and (2) SCP followed by air plasma cleaning. This work discusses the effect of the cleaning procedures on surface roughness, contact angle, and surface chemistry using atomic force microscopy, optical microscopy, and an X-ray photoelectron spectroscope meter. The results showed that SCP before the SPRi is a proper surface-treatment method. The effect of adsorbed VOCs during dropwise condensation on a surface treated with SCP was measured to be 0.0025 (reflectivity unit), which was 70% smaller than the reflectance associated with a monolayer water film. The results of this work confirm a monolayer water film observation during the dropwise condensation, which has been reported before.

36 MATERIALS SCIENCE↗