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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 955 records · Page 53

Plant single-cell solutions for energy and the environment

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species’ cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward.

59 BASIC BIOLOGICAL SCIENCES↗

Contrasting Mixotrophic Lifestyles Reveal Different Ecological Niches in Two Closely Related Marine Protists

Many marine microbial eukaryotes combine photosynthetic with phagotrophic nutrition, but incomplete understanding of such mixotrophic protists, their functional diversity, and underlying physiological mechanisms limits the assessment and modeling of their roles in present and future ocean ecosystems. We developed an experimental system to study responses of mixotrophic protists to availability of living prey and light, and used it to characterize contrasting physiological strategies in two stramenopiles in the genus Ochromonas . We show that oceanic isolate CCMP 1393 is an obligate mixotroph, requiring both light and prey as complementary resources. Interdependence of photosynthesis and heterotrophy in CCMP 1393 comprises a significant role of mitochondrial respiration in photosynthetic electron transport. In contrast, coastal isolate CCMP 2951 is a facultative mixotroph that can substitute photosynthesis by phagotrophy and hence grow purely heterotrophically in darkness. In contrast to CCMP 1393, CCMP 2951 also exhibits a marked photoprotection response that integrates non‐photochemical quenching and mitochondrial respiration as electron sink for photosynthetically produced reducing equivalents. Facultative mixotrophs similar to CCMP 2951 might be well adapted to variable environments, while obligate mixotrophs similar to CCMP 1393 appear capable of resource efficient growth in oligotrophic ocean environments. Thus, the responses of these phylogenetically close protists to the availability of different resources reveals niche differentiation that influences impacts in food webs and leads to opposing carbon cycle roles.

Marine & Freshwater Biology↗

Modelling belowground plant acclimation to low soil nitrogen – a heuristic optimality-based approach

Increased root growth to access greater soil mineral nitrogen resources and increased root exudation to stimulate microbial mineralization of soil organic nitrogen are widely observed plant acclimations to nitrogen limitation. However, their quantitative contribution to plant growth and ecosystem productivity remains largely elusive. Here, we present a novel optimality-based eco-evolutionary model in which plants dynamically regulate carbon partitioning between root growth and exudation to maximize their aboveground growth. Our simulations indicated that the availability of soil mineral and organic nitrogen as well as plant nitrogen demand and nitrogen uptake capacity shape optimal carbon partitioning between root growth and exudation. The simulated carbon allocation patterns aligned with empirical studies on belowground plant responses to varying soil nitrogen resources. Our eco-evolutionary approach represents a paradigmatic change in modelling plant nitrogen foraging, which is essential to generate hypotheses on optimal plant acclimation in future soil environments characterized by more erratic nitrogen availability.

Chakrawal, Arjun (ORCID:0000000345724347)↗

Spectral response curve models applied to forest cover-type discrimination

The potential of remote sensing systems to provide a cost-effective inventory tool in the case of forest resources is currently of interest to a variety of natural resources management agencies. A number of studies have been performed regarding the use of Landsat data for mapping forest resources in Michigan. The present paper is concerned with current research, which has been directed toward the development and evaluation of computer-implemented classifications for the identification and characterization of coniferous forest types in Michigan's northern Lower Peninsula. Attention is given to the characteristic response curves from Landsat MSS data, spectral response curve models, and forest cover-type discrimination. It is found that spectral response curve models can be used to evaluate and explain the characteristic spectral responses of coniferous forest types on a snow-covered, winter Landsat scene.

Hudson, W. D.↗

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

Ransom, K. J.↗

Nanomaterial-Engineered Surfaces for Decontamination of Water Resources

Aggregation-dependent shifts in plasmon frequency (colorimetric sensor); • Local refractive index-dependent shifts in plasmon frequency; • Inelastic (surface-enhanced Raman) light scattering; • Elastic (Rayleigh) light scattering CONCLUSIONS Generate unique classes of nanoscale materials for environmental stewardship applications o Characterization of nanomaterials provides understanding of structural properties for sorption of contaminants o Surface charge influences interaction between nanomaterial and contaminant o Surface charge can be modified to allow for more contaminant sorption • Demonstrate innovative nanomaterial science and technology solutions that meet our environmental stewardship needs: • Detect contaminants • Sequester contaminants

Murph, Simona E. [Savannah River National Laborato↗

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗

Confirmation and Quantification of Gas Flow into Capsules

Inertial confinement fusion experiments require a fuel filled target. At the National Ignition Facility (NIF), these targets are filled through a capsule fill tube assembly (CFTA). While fabricating these assemblies, it is possible to plug the fill tube with glue, which would render the CFTA and eventual target unusable. Historically, this plugging was first detectable in a finished target after considerable resources had been expended. Herein, this paper presents a method for not only detecting a plug in the fill tube before the CFTA is assembled into a target, but also characterizing gas flow through the fill tube, which can help NIF operations prepare to expend each target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the Stability of Power Transmission Systems Under Persistent Inverter Attacks: A Bi-Linear Matrix Approach

We investigate the stability and robustness properties of a power transmission system under persistent deceiving attacks on inverter-interfaced energy resources. The attacks can corrupt the damping coefficients in the inverters' controllers and measurements of the frequency at the points of coupling. Leveraging tools from hybrid dynamical systems theory, we characterize a broad family of persistent (and not necessarily periodic) attacks acting on the inverters, under which the stability properties of the transmission system can be shown to not be compromised. To address potentially conservative conditions identified through conventional bounding techniques, sufficient conditions on the average activation time of the attacks are identified via Lyapunov theory, as well as the formulation and solution of a class of bilinear matrix inequalities (BMI). The results are obtained for constant and slowly time-varying loads via input-to-state stability (ISS) tools. Numerical simulations on the IEEE 39-bus test system are also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Utah FORGE: X-Ray Diffraction Data

This dataset contains X-ray diffraction (XRD) data taken from wells and outcrops as part of the DOE GTO supported Utah FORGE project located near Roosevelt Hot Springs. It contains an Excel spreadsheet with the XRD data, a text file with sample site names, types, and locations in UTM, Zone 12, NAD83 coordinates, and a GIS shapefile of the sample locations with attributes.

15 GEOTHERMAL ENERGY↗

Utah FORGE: GIS Well Temperature Data

This is a GIS point feature shapefile representing wells, and their temperatures, that are located in the general Utah FORGE area near Milford, Utah. There are also fields that represent interpolated temperature values at depths of 200 m, 1000 m, 2000 m, 3000 m, and 4000 m. in degrees Fahrenheit. The temperature values at specific depths as mentioned above were derived as follows. In cases where the well reached a given depth (200 m and 1, 2, 3, or 4 km), the temperature is the measured temperature. For the shallower wells (and at deeper depths in the wells reaching one or more of the target depths), temperatures were extrapolated from the temperature-depth profiles that appeared to have stable (re-equilibrated after drilling) and linear profiles within the conductive regime (i.e. below the water table or other convective influences such as shallow hydrothermal outflow from the Roosevelt Hydrothermal System). Measured temperatures/gradients from deeper wells (when available and reasonably close to a given well) were used to help constrain the extrapolation to greater depths. Most of the field names in the attribute table are intuitive, however HF = heat flow, intercept = the temperature at the surface (x-axis of the temperature-depth plots) based on the linear segment of the plot that was used to extrapolate the temperature profiles to greater depths, and depth_m is the total well depth. This information is also present in the shapefile metadata.

15 GEOTHERMAL ENERGY↗

Velocity and Turbulence Measurements at Three Locations in the Salish Sea, WA, 2017

This submission contains raw and processed datasets of water velocity and turbulence measurements from 3-day deployments of Deepwater Buoyancy StableMoor buoys carrying acoustic Doppler instrumentation at locations in Rosario Strait, Bellingham Channel, and Tacoma Narrows, WA in 2017. Two StableMoor buoy configurations were used at these sites. The StableMoor500 carried a nose-mounted acoustic doppler velocimeter (ADV) and a down-looking acoustic doppler current profiler (ADCP), and the StableMoor400 carried dual wing-mounted ADVs located on either side of the nose and a down-looking ADCP. Each StableMoor was designed to fly at an altitude of 10 m above the seafloor. The StableMoor500 was deployed in Bellingham Channel at 48.5601 N, 122.7501 W in 86 m of water from July 24, 2017 - July 27, 2017. The down-looking ADCP malfunctioned, and therefore there is no ADCP data at this site. The StableMoor400 was deployed in Rosario Strait mooring at 48.5800 N, 122.6597 W in 52 m of water from July 24, 2017 - July 27, 2017. Both buoys were deployed in Tacoma Narrows at 47.2766 N, 122.5466 W and 47.2769 N, 122.5471 W in 36 m of water from Nov 14, 2017 - Nov 17, 2017. Nortek Vector ADV measurements were recorded continuously at 16 Hz. Data was motion-corrected using the internal measurement unit (IMU) and external ADCP bottom-track data, bin-averaged into 10 minute bins, and then converted to the Principal (streamwise, cross-stream, vertical) coordinate system. Parameters include water velocity, turbulence intensity, turbulent kinetic energy (TKE) components, Reynolds shear stress components, TKE dissipation and production. Teledyne RDI Workhorse 1200 kHz ADCP measurements were recorded continuously at 2 Hz with bottom-track enabled. Water velocity was averaged into 10 minute bins and converted into the Principal coordinate system. One ADV with the highest quality motion-corrected was fully processed from each deployment site: the nose-mounted ADV at Bellingham Channel, the starboard-wing mounted ADV at Rosario Strait, and the port-wing mounted ADV at Tacoma Narrows. Raw data stored in this submission can be read using DOLfYN v1.3.1, available through the MHKiT python package, and was processed using Tsdat v0.7.5. Processed data are stored in netCDF4 format and can be easily viewed using the Linux "ncdump" command or read through the Xarray python package.

16 TIDAL AND WAVE POWER↗

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗

A space station Structures and Assembly Verification Experiment, SAVE

The Space Station structure has been baselined to be a 5 M (16.4 ft) erectable truss. This structure will provide the overall framework to attach laboratory modules and other systems, subsystems and utilities. The assembly of this structure represents a formidable EVA challenge. To validate this capability the Space Station Structures/Dynamics Technical Integration Panel (TIP) met to develop the necessary data for an integrated STS structures flight experiment. As a result of this meeting, the Langley Research Center initiated a joint Langley/Boeing Aerospace Company study which supported the structures/dynamics TIP in developing the preliminary definition and design of a 5 M erectable space station truss and the resources required for a proposed flight experiment. The purpose of the study was to: (1) devise methods of truss assembly by astronauts; (2) define a specific test matrix for dynamic characterization; (3) identify instrumentation and data system requirements; (4) determine the power, propulsion and control requirements for the truss on-orbit for 3 years; (5) study the packaging of the experiment in the orbiter cargo bay; (6) prepare a preliminary cost estimate and schedule for the experiment; and (7) provide a list of potential follow-on experiments using the structure as a free flyer. The results of this three month study are presented.

Russell, R. A.↗

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

Alexeev, Yuri↗

Host-specific and tissue-dependent orchestration of microbiome community structure in traditional rice paddy ecosystems

Abstract Background and aim Rice and duckweed are two monocotyledonous plants that naturally coexist in paddy fields. While the presence of duckweed in paddy fields significantly improves rice productivity, the interplay between soil microbes and the two plant hosts in this agroecosystem remains unexplored. Methods We compared the bacterial community structure between duckweed, rice and soil from multiple rice paddies. We also isolated bacteria from these communities and characterized their modes of bacterial colonization and plant growth-promotion using model plants. Results Our data indicate that host-specific and tissue-dependent factors reproducibly orchestrate the bacterial community structure associated with their plant hosts. This is corroborated by results from culture-dependent approaches in which the dominant genus Pantoea isolated from rice aerial tissues can strongly attach and colonize gnotobiotic duckweed in spite of the low representation of this bacterial genus in the natural duckweed microbiome. Our study identified a core of 254 bacterial taxa that are consistently found in all rice and duckweed tissue samples from rice paddy fields. Furthermore, characterizing auxin-producing bacteria isolates from both plant species identified potential plant growth-promoting bacteria that may improve growth for both duckweed and rice in paddy fields. Conclusions Results from this work provide evidence for the importance of the host tissue and species context in determining plant colonization by microbes in the paddy field system. The resources generated in this study could facilitate the agronomic deployment of microbes for more sustainable rice production.

Agriculture↗