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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Enabling high rate charge and discharge capability, low internal resistance, and excellent cycleability for Li-ion batteries utilizing graphene additives

A liquid-phase mixing method is adopted to uniformly disperse the graphene nanosheets onto LiNi 1/3 Co 1/3 Mn 1/3 O 2 cathode for high-performance Li-ion batteries (LIBs). The electrochemical performance was characterized using a full pouch cells with state-of-the-art electrode areal loading (compared to half coin cells). The addition of graphene sheets (i.e., only 1 wt%) significantly improves the high rate capability for charging and discharging operation. For example, 6 times improvement in 5 C charging was achieved providing further insights in enabling extreme fast charging for LIBs. Other benefits include longer cycleability, lower internal resistance, and higher lithium ion diffusion coefficient, demonstrated by charge-discharge cycling tests and electrochemical impedance spectroscopy. Higher capacity retention of 88.2% and decreased internal resistance of ~0.9 Ω are observed after 400 cycles. The diffusion coefficient of Li ions is 6.49 × 10 -8 cm 2 s -1 when charged to 4.2 V, which is approximately 1.37 times higher compared to the configuration with no graphene sheet (4.74 × 10 -8 cm 2 s -1 ). To conclude, the improved performance is ascribed to a robust network among the active materials formed by graphene sheets, which serves as an extended current conductor and facilitates charge transfer, ionic reversibility, and ionic transportation.

25 ENERGY STORAGE↗
DOE OSTI2019

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

Setting up a STAR Tier 2 Site at Golias/Prague Farm

High Energy Nuclear Physics (HENP) collaborations experience show that the computing resources available at a single site are often neither sufficient nor satisfy the need of remote collaborators eager to carry their analysis in the fastest and most convenient way. From latencies in the network connectivity to the lack of interactivity, work at distant computing centers is often inefficient. Having fully functional software stack on local resources is a strong enabler of science opportunities for any local group who can afford the time investment. The situation becomes more complex as vast amount of data are often needed to perform meaningful analysis. Prague's heavy-ions group participating in STAR experiment at RHIC has been a strong advocate of local computing as the most efficient means of data processing and physics analyses. To create an environment where science can freely thrive, a Tier 2 computing center was set up at a Regional Computing Center for Particle Physics called 'Golias'. It is the biggest farm in the Czech Republic fully dedicated for particle physics experiments. We report on our experience in setting up a fully functional Tier 2 center leveraging the minimal locally available human and financial resources. We discuss the solutions chosen to address storage space and analysis issues and the impact on the farms overall functionality. This includes a locally built STAR analysis framework, integration with a local DPM system (a cost effective storage solution), the influence of the availability and quality of the network connection to Tier 0 via a dedicated CESNET/ESnet link and the development of light-weight yet fully automated data transfer tools allowing the movement of entire datasets from BNL (Tier 0) to Golias (Tier 2). We will summarize the impact of the gained computing performance on the efficiency of the local physics group at offline physics analysis and show the feasibility of such a solution that can used by other groups as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Pore-lining composition and capillary breakthrough pressure of mudstone caprocks : sealing efficiency at geologic CO2 storage sites.

Subsurface containment of CO2 is predicated on effective caprock sealing. Many previous studies have relied on macroscopic measurements of capillary breakthrough pressure and other petrophysical properties without direct examination of solid phases that line pore networks and directly contact fluids. However, pore-lining phases strongly contribute to sealing behavior through interfacial interactions among CO2, brine, and the mineral or non-mineral phases. Our high resolution (i.e., sub-micron) examination of the composition of pore-lining phases of several continental and marine mudstones indicates that sealing efficiency (i.e., breakthrough pressure) is governed by pore shapes and pore-lining phases that are not identifiable except through direct characterization of pores. Bulk X-ray diffraction data does not indicate which phases line the pores and may be especially lacking for mudstones with organic material. Organics can line pores and may represent once-mobile phases that modify the wettability of an originally clay-lined pore network. For shallow formations (i.e., < {approx}800 m depth), interfacial tension and contact angles result in breakthrough pressures that may be as high as those needed to fracture the rock - thus, in the absence of fractures, capillary sealing efficiency is indicated. Deeper seals have poorer capillary sealing if mica-like wetting dominates the wettability. We thank the U.S. Department of Energy's National Energy Technology Laboratory and the Office of Basic Energy Sciences, and the Southeast and Southwest Carbon Sequestration Partnerships for supporting this work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDRs success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

accessibility↗
DOE OSTI2012

2012 Gordon Research Conference, Mitochondria and Chloroplasts, July 29 - Aug 3 2012

The 2012 Gordon Research Conference on Mitochondria and Chloroplasts will assemble an international group of scientists investigating fundamental properties of these organelles, and their integration into broader physiological processes. The conference will emphasize the many commonalities between mitochondria and chloroplasts: their evolution from bacterial endosymbionts, their genomes and gene expression systems, their energy transducing membranes whose proteins derive from both nuclear and organellar genes, the challenge of maintaining organelle integrity in the presence of the reactive oxygen species that are generated during energy transduction, their incorporation into organismal signaling pathways, and more. The conference will bring together investigators working in animal, plant, fungal and protozoan systems who specialize in cell biology, genetics, biochemistry, physiology, proteomics, genomics, and structural biology. As such, this conference will provide a unique forum that engenders cross-disciplinary discussions concerning the biogenesis, dynamics, and regulation of these key cellular structures. By fostering interactions among mammalian, fungal and plant organellar biologists, this conference also provides a conduit for the transmission of mechanistic insights obtained in model organisms to applications in medicine and agriculture. The 2012 conference will highlight areas that are moving rapidly and emerging themes. These include new insights into the ultrastructure and organization of the energy transducing membranes, the coupling of organellar gene expression with the assembly of photosynthetic and respiratory complexes, the regulatory networks that couple organelle biogenesis with developmental and physiological signals, the signaling events through which organellar physiology influences nuclear gene expression, and the roles of organelles in disease and development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Study on the Impact of Temperature-Dependent Ferroelectric Switching Behavior in 3D Memory Architecture

The flourishing development of neural networks that require exponentially growing amounts of data has presented an elevated demand for memory footprint. To address this, researchers have been exploring hardware accelerators with innovative memory architectures like 3D memory. These 3D memory architectures offer enhanced storage capacity and processing capabilities, at a cost of rising on-chip temperature during operation. Hafnium Zirconium Oxide (HZO) based Ferroelectric Random Access Memory (FeRAM) is a promising nonvolatile memory candidate in neural network hardware accelerators for its outstanding write performance and reliability. However, its implementation in the architecture regarding the temperature-dependent ferroelectric switching behavior has not been well studied. In this work, we study the thermal impacts on polarization switching through experimental devices and simulation results. We conduct the circuit and architecture-level simulations to showcase that one can exploit this temperature rise to reduce FeRAM's write voltage and write energy due to its unique temperature-activated polarization switching mechanisms. As the on-chip temperature increases to 351K (ambient temperature at 300K) due to neural network workloads, the access energy per bit can be reduced by 27.6% when a dynamic write voltage is applied.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Exploring the mobility and energy implications of shared versus private autonomous vehicles

The prevailing trend toward greater automation and connectivity requires modeling and analysis tools to explore connectivity, automation, decision science and other future mobility issues at multiple scales. This paper describes various modeling efforts in order to model the mobility and energy impact of autonomous and connected technologies; design of scenarios under different technological, behavioral, and socioeconomic assumptions; and finally, key findings from the scenario runs enabled by the advanced models developed. The integrated ABM-DTA software POLARIS has been extended to include transit, intra-household vehicle sharing, transportation network company (TNC) operations along with updates to the mesoscopic traffic models and value of time adjustments due to new technologies affecting the mode, destination, and route choice. The three scenarios are summarized as high sharing - low automation, high sharing - high automation, and low sharing - high automation, with VMT changes ranging from -13% to 42%.

Multi-autonomous Vehicle Studies, Models, Techniqu↗
DOE OSTI2016

First Steps Toward Incorporating Image Based Diagnostics Into Particle Accelerator Control Systems Using Convolutional Neural Networks

At present, a variety of image-based diagnostics are used in particle accelerator systems. Often times, these are viewed by a human operator who then makes appropriate adjustments to the machine. Given recent advances in using convolutional neural networks (CNNs) for image processing, it should be possible to use image diagnostics directly in control routines (NN-based or otherwise). This is especially appealing for non-intercepting diagnostics that could run continuously during beam operation. Here, we show results of a first step toward implementing such a controller: our trained CNN can predict multiple simulated downstream beam parameters at the Fermilab Accelerator Science and Technology (FAST) facility's low energy beamline using simulated virtual cathode laser images, gun phases, and solenoid strengths.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDR's success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

access↗
DOE OSTI2013

Nanostructure-enhanced Phase Change Materials (NePCM) and HRD

Development and characterization of high aspect-ratio nanostructures tailored for dramatic improvements of thermal conductivity of phase change materials is proposed. This DOE renewal project builds upon a proven research record on development of a number of stable and functionality-proven colloids of metal oxide and metallic nanoparticles (avg. diameters less than 10 nm). These efforts followed original conceptualization and synergistic activities on promoting nanostructure-enhanced phase change materials (NePCM) and their utilization for thermal energy storage, waste heat recovery, thermal comfort, etc. Given this background, availability of promising preliminary results for the proposed target materials and formation of a new team of researchers, the investigators will focus on development of nanoadditives of metallic nanorods, functionalized carbon nanotubes, Graphene, graphite nanoplatelets, nanocomposites combining graphene with metal/metal oxide nanostructures and self-assembling carbon nanofiber-based nanomaterials. Specifically, the chemical synthesis group will identify procedures leading to nanorods of copper, copper oxide, silver and graphitic carbon exhibiting long-term stability against precipitation when dispersed in hydrocarbon solvents suitable for PCM applications. Important goals are to achieve nanorods with dimensions, including aspect ratio, that induce significant enhancements in thermal conductivity and also to control instabilities against rod precipitation during solvent freezing and melting. Another group will focus on developing complex nanoarchitectured nanocomposites through utilizing heterostructures that combine graphene with metal or metal oxide nanostructures. These heterostructures will be mixed with paraffin, fatty acids, or stearyl alcohol to realize novel NePCM. Fundamental studies will be performed by conducting materials and thermal characterization methods and structure-processing-properties relationships will be derived. In addition, growth mechanisms for the proposed heterostructures will be evaluated. Another research team will undertake a variety of approaches to functionalize the surfaces of nanostructured carbon-based materials, i.e. carbon nanotubes, Graphene and graphite nanoplatelets. The proposed techniques include both surfactant- and polymer-assisted dispersion of carbon nanotubes, Graphene and graphite nanoplatelets, in addition to microwave-initiated carbon nanotube growth to produce 3-D nanocarbon fillers for NePCM. Functionalized and pristine carbon nanotubes will also be subjected to a strong magnetic field to explore the effect of controlled alignment on the improved thermal conductivity. Microwave-initiated nanotube growth on the surfaces of the voids of graphite foam will be attempted to extend the previous work on thermal conductivity improvement of PCM that are impregnated into porous highly-conductive structures. Refinements of continuum modeling of colloids and most importantly, molecular dynamics-based mechanistic studies for carbon nanotubes and Graphene-based multi-component systems will be pursued. Finally, self-assembling carbon nanofiber-based NePCM will be investigated by another group. A highly-conductive carbon nanofiber network, which is created by a self-assembling approach, will host the PCM and enhance the thermal conductivity by several folds. Furthermore, the inert and relatively stable carbon nanofiber will be further utilized for creating low-mid range temperature NePCM and high-temperature NePCM by filling the porous space inside the self-assembling carbon nanofiber network with paraffin-based or salt-based PCM, respectively. Improved thermal energy charge/discharge performance and stable phase change temperature control features exhibited by this new generation of self-assembling carbon nanofiber-based NePCM will potentially impact many applications including solar energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Incorporating PCM-enabled thermal energy storage into 3D printable cementitious composites

This paper delineates the feasibility of incorporating microencapsulated phase change materials (mPCM) into 3D printable cementitious composite materials. A comprehensive experimental program was carried out to evaluate the impacts of mPCM on the printability, microstructures, mechanical and thermal properties of cementitious 3D printing ‘inks’. Results showed that the mPCM affected the printability of the cementitious ink material based on its physical properties (e.g., particle size) and volume loading – at lower volume loadings, mPCM increased the flowability of the cementitious ink material while leading to increased compressive strength and thermal conductivity for the hardened printed material. However, further increase in mPCM dosage led to a decrease in printability and, therefore, decrease in compressive strength and thermal conductivity as compared to the reference mixture. Here the results also showed that the inclusion of mPCM influence the printing parameters. In general, the inclusion of higher volume contents of mPCM necessitates a higher extrusion rate to achieve a desirable extrudability. Lastly, a thermal network model was formulated for 3D printed mPCM charged building components (e.g., wall). The study shows that microencapsulated PCM materials have good potential to be used in 3D printable cementitious mixtures for improving the thermal and energy performance of 3D printed buildings.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Systems Level Regulation of Rhythmic Growth Rate and Biomass Accumulation in Grasses

Several breakthroughs have been recently made in our understanding of plant growth and biomass accumulation. It was found that plant growth is rhythmically controlled throughout the day by the circadian clock through a complex interplay of light and phytohormone signaling pathways. While plants such as the C4 energy crop sorghum (Sorghum bicolor (L.) Moench) and possibly the C3 grass (Brachypodium distachyon) also exhibit daily rhythms in growth rate, the molecular details of its regulation remain to be explored. A better understanding of diurnally regulated growth behavior in grasses may lead to species-specific mechanisms highly relevant to future strategies to optimize energy crop biomass yield. Here we propose to devise a systems approach to identify, in parallel, regulatory hubs associated with rhythmic growth in C3 and C4 plants. We propose to use rhythmicity in daily growth patterns to drive the discovery of regulatory network modules controlling biomass accumulation.

09 BIOMASS FUELS↗
DOE OSTI2016

Templating Routes to Supported Oxide Catalysts by Design

The rational design and understanding of supported oxide catalysts requires at least three advancements, in order of increasing complexity: the ability to quantify the number and nature of active sites in a catalytic material, the ability to place external controls on the number and structure of these active sites, and the ability to assemble these active sites so as to carry out more complex functions in tandem. As part of an individual investigator research program that is integrated with the Northwestern University Institute for Catalysis in Energy Processes (ICEP) as of 2015, significant advances were achieved in these three areas. First, phosphonic acids were utilized in the quantitative assessment of the number of active and geometrically-available sites in MO x -SiO 2 catalysts, including nanocrystalline composites, co-condensed materials, and grafted structures, for M=Ti, Zr, Hf, Nb, and Ta. That work built off progress in understanding supported Fe, Cu, and Co oxide catalysts from chelating and/or multinuclear precursors to maximize surface reactivity. Secondly, significant progress was made in the new area of using thin oxide overcoats containing ‘nanocavities’ from organic templates as a method to control the dispersion and thermal stability of subsequently deposited metal nanoparticles or other catalytic domains. Similar methods were used to control surface reactivity in SiO 2 -Al 2 O 3 acid catalysts and to control reactant selectivity in Al 2 O 3 -TiO 2 photocatalysts. Finally, knowledge gained from the first two areas has been combined to synthesize a tandem catalyst for hydrotreating reactions and an orthogonal tandem catalyst system where two subsequent reactions in a reaction network are independently controlled by light and heat. Overall, work carried out under this project significantly advanced the knowledge of synthesis-structure-function relationships in supported oxide catalysts for energy applications.

02 PETROLEUM↗
DOE OSTI2021

AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)

On April 6-8, 2021, Sandia National Laboratories hosted a virtual workshop to explore the potential for developing AI-Enhanced Co-Design for Next-Generation Microelectronics (AICoM). The workshop brought together two themes. The first theme was articulated in the 2018 Department of Energy Office of Science (DOE SC) “Basic Research Needs for Microelectronics” (BRN) report, which called for a “fundamental rethinking” of the traditional design approach to microelectronics, in which subject matter experts (SMEs) in each microelectronics discipline (materials, devices, circuits, algorithms, etc.) work near-independently. Instead, the BRN called for a non-hierarchical, egalitarian vision of co-design, wherein “each scientific discipline informs and engages the others” in “parallel but intimately networked efforts to create radically new capabilities.” The second theme was the recognition of the continuing breakthroughs in artificial intelligence (AI) that are currently enhancing and accelerating the solution of traditional design problems in materials science, circuit design, and electronic design automation (EDA).

36 MATERIALS SCIENCE↗
DOE OSTI2015

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Linking Hydrobiogeochemical Processes and Management Techniques to Close Nutrient Loops in an Arid River

In this study, we explore opportunities to optimize food-energy-water (FEW) resources by closing nutrient loops in arid-land rivers. Specifically, we evaluate source and sink behavior of nitrogen as nitrate (NO 3 -N) in three characteristic channels in the Middle Rio Grande Basin (Delivery and Drain channels associated with agriculture and the main channel of the Rio Grande). All three channels are located downstream of a large wastewater treatment plant that is the main contributor of nutrients to this reach of the Rio Grande. We used a mass balance approach paired with stable isotope analysis to determine sources and processing of NO 3 -N within the channels over time (a year) and through space (along ~15 to 50 km reaches). Results indicated the growing season was an important period of sink behavior for the Delivery channel and the Rio Grande, but the Drain channel was a year-round source. Stable isotope analysis of 15 N and 18 O found a distinct nitrate signature in the Drain associated with biological processing, as well as Rio Grande sites impacted by agricultural outflow, but no equivalent signature was present in the Delivery channel. Based on our findings, we provide recommendations to help close nutrient loops in the study system and analogous aridland irrigation networks by 1) minimizing loss during the transfer of nutrients from wastewater facilities to agricultural areas, and 2) minimizing enrichment to downstream aquatic ecosystems by sequestering nutrients that escape the nutrient loop.

54 ENVIRONMENTAL SCIENCES↗