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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 685 records · Page 38

An Industry/Academe Consortium for Achieving 20% wind by 2030 through Cutting-Edge Research and Workforce Training

In January 2010, the University of Minnesota, along with academic and industry project partners, began work on a four year project to establish new facilities and research in strategic areas of wind energy necessary to move the nation towards a goal of 20% wind energy by 2030. The project was funded by the U.S. Department of Energy with funds made available through the American Recovery and Reinvestment Act of 2009. $7.9M of funds were provided by DOE and $3.1M was provided through matching funds. The project was organized into three Project Areas. Project Area 1 focused on design and development of a utility scale wind energy research facility to support research and innovation. The project commissioned the Eolos Wind Research Field Station in November of 2011. The site, located 20 miles from St. Paul, MN operates a 2.5MW Clipper Liberty C-96 wind turbine, a 130-ft tall sensored meteorological tower and a robust sensor and data acquisition network. The site is operational and will continue to serve as a site for innovation in wind energy for the next 15 years. Project Areas 2 involved research on six distinct research projects critical to the 20% Wind Energy by 2030 goals. The research collaborations involved faculty from two universities, over nine industry partners and two national laboratories. Research outcomes include new knowledge, patents, journal articles, technology advancements, new computational models and establishment of new collaborative relationships between university and industry. Project Area 3 focused on developing educational opportunities in wind energy for engineering and science students. The primary outcome is establishment of a new graduate level course at the University of Minnesota called Wind Engineering Essentials. The seminar style course provides a comprehensive analysis of wind energy technology, economics, and operation. The course is highly successful and will continue to be offered at the University. The vision of U.S. DOE to establish unique, open-access research facilities and creation of university-industry research collaborations in wind energy were achieved through this project. The University of Minnesota, through the establishment of the Eolos Wind Energy Consortium and the Eolos Wind Research Field Station continue to develop new research collaborations with industry partners.

17 WIND ENERGY↗

Deep Space navigation for the BioSentinel spacecraft science orbit

BioSentinel is an astrobiology small spacecraft mission. The payload consists of two parts, the first has optical and microfluidics sensors, and the second is a Linear Energy Transfer spectrometer that has the objective to measure deep space radiation from events such as coronal mass ejections. The goal of the mission is to observe potential DNA damage due to the radiation in heliocentric space on the living organism Saccharomyces cerevisiae, which is a budding yeast. Two types of this living organism are included in the payload. The first is a natural type that is more radiation tolerant, while the second is a mutant strain that has a deficiency in a gene that allows DNA repair once damage occurs. The impact caused by the radiation on the DNA is compared to an identical sample aboard the International Space Station, as well as another identical sample at a laboratory on the ground. The BioSentinel mission consists of a 6U CubeSat currently ,as of January 2024, active in heliocentric orbit. The spacecraft was launched aboard the first SLS flight as part of the Artemis-I campaign in November 2022. After successful deployment from the launch vehicle, it performed a lunar flyby with an altitude of 406 km. The delta-V imparted by the flyby provided the necessary energy to achieve a heliocentric orbit, in an Earth-trailing pattern. The navigation analysis consisted of a Kalman-filter that utilized data from the Deep Space Network and the ESA Estrack network. All those antennas were needed since the Artemis-1 campaign included the deployment of several other cubesats, therefore the scheduling process required more antenna assets than usual due to simultaneous demands from various missions. The processed tracking data was later also refined with a smoother in order to obtain a more accurate solution. The type of tracking data included TCP, Sequential Range, Doppler and Range formats. The solar radiation pressure coefficient, as well as the delta-V from the deployment and the flyby were modeled to obtain suitable solutions that could decrease the position and velocity uncertainties at several steps along the mission concept of operations. The final product each time resulted in updated ephemeris files that were used by the mission and the antenna networks as the mission progressed. Once in the final science orbit, the utilized antennas are only from the DSN network and the data format is bounded to just TCP. Regular orbit determination is performed, every two weeks. The spacecraft is in a nominal well-known orbit, performing regular operations. This paper includes an analysis of the final science orbit, the techniques and procedures utilized to perform orbit determination and a description of the overall navigation campaign produced during the mission and, more specifically, during the final science operations in Deep Space.

BioSentinel↗

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The real world and lunar base activation scenarios

A lunar base or a network of lunar bases may have highly desirable support functions in a national or international program to explore and settle Mars. In addition, He-3 exported from the Moon could be the basis for providing much of the energy needs of humankind in the twenty-first century. Both technical and managerial issues must be addressed when considering the establishment of a lunar base that can serve the needs of human civilization in space. Many of the technical issues become evident in the consideration of hypothetical scenarios for the activation of a network of lunar bases. Specific and realistic assumptions must be made about the conduct of various types of activities in addition to the general assumptions given above. These activities include landings, crew consumables, power production, crew selection, risk management, habitation, science station placement, base planning, science, agriculture, resource evaluation, readaptation, plant activation and test, storage module landings, resource transport module landings, integrated operations, maintenance, Base 2 activation, and management. The development of scenarios for the activation of a lunar base or network of bases will require close attention to the 'real world' of space operations. That world is defined by the natural environment, available technology, realistic objectives, and common sense.

Schmitt, Harrison H.↗

Spectrum of embrittling potencies and relation to properties of symmetric-tilt grain boundaries

Grain boundaries in metallic materials can exist in a wide range of stable and metastable structures. In addition, the properties of a grain boundary may be altered through solute segregation. In this work, we present a formulation that combines the spectrum of embrittling potencies associated with solute segregation with site-occupancy statistics. As a prototype problem, we illustrate the relation between segregation and embrittlement in the case of S segregation to grain boundaries in Ni. To obtain a population of site segregation energies, we perform molecular statics calculations on 378 different symmetric-tilt grain boundaries and their free surface equivalents, using an embedded-atom method interatomic potential developed specifically for studying embrittlement. Our results show that it is important to consider both the energies associated with embrittlement and the probability of occupancy to describe the general embrittling nature of a grain boundary. When analyzed in isolation, certain grain boundaries show large embrittling potencies; however, that effect is diminished when the probability of S segregation to that grain boundary is considered within a polycrystal. We propose a new quantity, the embrittling estimator, which not only categorizes grain boundaries as embrittling or strengthening, but also considers site occupancy probabilities, so that the embrittlement behavior of grain boundaries within a network of grain boundaries can be compared. Finally, we examine the relationship between embrittlement behavior and innate grain boundary properties, such as the free volume, and find statistical evidence that the complex nature of embrittlement cannot be explained by linear correlations with excess volumes or energies. Ultimately, this combined approach provides a theoretical tool to assist grain boundary engineering of metastable alloys.

36 MATERIALS SCIENCE↗

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗

Defect reaction network in Si-doped InAs. Numerical predictions.

This Report characterizes the defects in the defect reaction network in silicon-doped, n-type InAs predicted with first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si-doped InAs, until culminating in immobile reaction products. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon-related defects in the reaction network. This Report serves to extend the results for the properties of intrinsic defects in bulk InAs as collated in SAND 2013 - 2477: ''Simple intrinsic defects in InAs : numerical predictions'' to include Si-containing simple defects likely to be present in a radiation-induced defect reaction sequence.

36 MATERIALS SCIENCE↗

Advancing Terrestrial Ecosystem Science With a Novel Automated Measurement System for Sun‐Induced Chlorophyll Fluorescence for Integration With Eddy Covariance Flux Networks

Abstract Sun‐induced chlorophyll fluorescence (SIF) provides critical information on the dynamics of gross primary productivity, a unique role not readily achievable using other methods. Long‐term continuous SIF observations have the potential to advance terrestrial ecosystem science. Realizing this potential, however, requires synergistic implementation of SIF measurements within eddy covariance (EC) flux networks. There is a need for SIF systems that can integrate seamlessly with EC instrumentation to maximize synergistic use of obtained data. Here we introduce the Fluorescence Auto‐Measurement Equipment (FAME) and protocol that fulfill such a purpose. FAME is designed specifically for plug‐and‐play integration with existing EC data acquisition systems. Its innovative hardware and software designs provide versatility, extensibility, autonomous operation, and ease of maintenance for acquiring SIF data of high quality and quantity. A major novel feature of FAME is its synchronized sampling of spectral irradiance and environmental variables, allowing for more precise interpretation of the SIF signal. FAME has been deployed since September 2016 at the Missouri Ozark AmeriFlux site, providing high‐quality measurements even when air temperatures approached 40 °C. Results reveal that canopy SIF saturated or even slightly decreased at high light, similar to leaf‐level photosynthesis. Clear diurnal hysteresis was observed: For the same light, morning SIF was higher than afternoon. Dynamic energy dissipation processes and stress‐induced movements of chloroplasts and leaves may explain the observed pattern. The technology and measurement protocol introduced here advances the coordinated observation of SIF and EC fluxes and represents a step change in observational ecosystem and carbon cycle science research.

54 ENVIRONMENTAL SCIENCES↗

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Flowable conducting particle networks in redox-active electrolytes for grid energy storage

This paper reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO 2+ /VO 2 + redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage. Charge storage contributions (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO 2+ /VO 2 + redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s -1 ) than one based on a non-redox active electrolyte. Additionally, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.

25 ENERGY STORAGE↗

Star/galaxy separation at faint magnitudes: application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper. We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information. We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SExtractor), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23.

79 ASTRONOMY AND ASTROPHYSICS↗

Developing a Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Signalized Intersections.

This study develops an eco-driving strategy for hybrid electric vehicles (HEVs) in the vicinity of signalized intersections, entitled HEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The proposed system computes real-time, energy-optimized vehicle trajectories using HEV vehicle dynamics and energy consumption models. In the proposed system, a simple HEV energy model is used to compute the instantaneous fuel consumption. This HEV energy model is selected since it is general, transferable, and can be easily used to compute instantaneous energy consumption levels for HEVs without the additional input of vehicle engine data or complicated power control strategies. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The energy-optimum problem is formulated as an optimization problem with constraints, which is solved using a moving-horizon dynamic programming approach. The proposed HEV Eco-CACC-I system was tested to evaluate its performance for various speed limits, roadway grades, and signal timings. Lastly, the proposed HEV controller was implemented in a microscopic traffic simulation software to test its network-wide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed system can effectively reduce stop-and-go traffic in the vicinity of signalized intersections producing savings of 7.4% in energy consumption, 5.8% in traffic delay and 23% vehicle stops, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Synchrotron X-ray nanotomographic and spectromicroscopic study of the tricalcium aluminate hydration in the presence of gypsum

The rheology of modern Portland cement (PC) concrete critically depends on the correct dosage of gypsum (calcium sulfate hydrate) to control the hydration of the most reactive phase - tricalcium aluminate (C{sub 3}A). The underlying physio-chemical mechanism, however, remains unsolved mainly due to the lack of high-spatial-resolved and chemistry-sensitive characterization of the C{sub 3}A dissolution frontier. Here, we fill this gap by integrating synchrotron-radiation based crystallographic, photon-energy-dependent spectroscopic and high-resolution morphological studies of the C{sub 3}A hydration product layer. We propose that ettringite (6CaO·Al{sub 2}O{sub 3}·SO{sub 3}·32H{sub 2}O) is the only hydration product after the initial reaction period and before complete gypsum dissolution. We quantify the 2D and 3D morphology of the ettringite network, e.g. the packing density of ettringite at various surface locations and the surface dissolution heterogeneity. Our results show no trace of a rate-controlling diffusion barrier. We expect our work to have significant impact on modeling the kinetics and morphological evolution of PC hydration.

36 MATERIALS SCIENCE↗

Casting Nanoporous Platinum in Metal–Organic Frameworks

Nanocasting based on porous templates is a powerful strategy in accessing materials and structures that are difficult to form by bottom-up syntheses in a controlled fashion. A facile synthetic strategy for casting ordered, nanoporous platinum (NP-Pt) networks with a high degree of control by using metal-organic frameworks (MOFs) as templates is reported here. The Pt precursor is first infiltrated into zirconium-based MOFs and subsequently transformed to 3D metallic networks via a chemical reduction process. It is demonstrated that the dimensions and topologies of the cast NP-Pt networks can be accurately controlled by using different MOFs as templates. The Brunauer-Emmett-Teller surface areas of the NP-Pt networks are estimated to be >100 m 2 g -1 and they exhibit excellent catalytic activities in the methanol electrooxidation reaction (MEOR). Finally, this new methodology presents an attractive route to prepare well-defined nanoporous materials for diverse applications ranging from energy to sensing and biotechnology.

36 MATERIALS SCIENCE↗

Relaxation, Structure and Properties of Semi-coherent Interfaces

Materials containing high density of interfaces are promising candidates for future energy technologies, because interfaces acting as sources, sinks, and barriers for defects can improve mechanical and irradiation properties of materials. Semi-coherent interface widely occurring in various materials is composed of a network of misfit dislocations and coherent regions separated by misfit dislocations. Lastly, in this article, we review relaxation mechanisms, structure and properties of (111) semi-coherent interfaces in face centered cubic structures.

36 MATERIALS SCIENCE↗

An evolutionarily conserved RNase-based mechanism for repression of transcriptional positive autoregulation

It is known that environmental context influences the degree of regulation at the transcriptional and post-transcriptional levels. However, the principles governing the differential usage and interplay of regulation at these two levels are not clear. Here, we show that the integration of transcriptional and post-transcriptional regulatory mechanisms in a characteristic network motif drives efficient environment-dependent state transitions. Through phenotypic screening, systems analysis, and rigorous experimental validation, we discovered an RNase (VNG2099C) in Halobacterium salinarum that is transcriptionally co-regulated with genes of the aerobic physiologic state but acts on transcripts of the anaerobic state. Through modelling and experimentation we show that this arrangement generates an efficient state-transition switch, within which RNase-repression of a transcriptional positive autoregulation (RPAR) loop is critical for shutting down ATP-consuming active potassium uptake to conserve energy required for salinity adaptation under aerobic, high potassium, or dark conditions. Subsequently, we discovered that many Escherichia coli operons with energy-associated functions are also putatively controlled by RPAR indicating that this network motif may have evolved independently in phylogenetically distant organisms. Thus, our data suggest that interplay of transcriptional and post-transcriptional regulation in the RPAR motif is a generalized principle for efficient environment-dependent state transitions across prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

The evolution of grain boundary energy in textured and untextured Ca–doped alumina during grain growth

The role of anisotropic grain boundary energy in grain growth is investigated using textured microstructures that contain a high proportion of special grain boundaries. Textured and untextured Ca–doped alumina was prepared by slip casting inside and outside a high magnetic field, respectively. At 1600°C, the textured microstructure exhibits faster growth than the untextured microstructure and its population of low–angle boundaries increases. Atomic force microscopy (AFM) is employed to measure the geometry of thermal grooves to assess the relative grain boundary energy of these systems before and after growth. In the textured microstructure, the grain boundary energy distribution narrows and shifts to a lower average energy. Conversely, the energy distribution broadens for the untextured microstructure as it grows and exhibits abnormal grain growth. Further analysis of the boundary networks neighboring abnormal grains reveals an energy incentive that facilitates their growth. These results suggest that coarsening is not the only dominant grain growth mechanism and that the system can lower its energy effectively by replacing high energy boundaries with those of low energy. The faster growth of lower energy boundaries suggests that isotropic simulations do not adequately account for anisotropic grain growth mechanisms or anisotropic mobility.

36 MATERIALS SCIENCE↗