SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
These data include raw scanning Doppler lidar measurements from the deployment of the ARM HALO XR+ (s/n 237) at the A7 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the LLNL HALO XR+ (s/n 190) at the A5 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the NREL HALO XR+ (s/n 235) at the A5 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the PNNL HALO XR+ (s/n 184) at the A7 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the NREL Halo XR+ (s/n 235) at WFIP3's SHIP. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the NREL Halo XR+ (s/n 235) at WFIP3's BARG. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. Note: the measurements have NOT been corrected for the motion of the barge.
These data include raw scanning Doppler lidar measurements from the deployment of the LLNL HALO XR+ (s/n 190) at the Rhode Island site for WFIP3. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
These data include raw scanning Doppler lidar measurements from the deployment of the NREL Halo XR+ (s/n 235) at WFIP3's NOAA ship. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. The location of the ship is provided separately.
These data include raw scanning Doppler lidar measurements from the deployment of the NREL HALO XR+ (s/n 235) at the A1 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.
The potential benefits of adding raw, non-food, lignocellulosic plant material as a carbon source for mixotrophic growth of microalgae have previously been demonstrated. This approach has advantages over using traditional carbon sources like glucose or acetate due to wide-spread plant biomass availability and substrate recalcitrance to bacterial contamination. Here, we report the overall growth characteristics and explore the metabolic patterns of Scenedesmus obliquus cultured in the presence raw plant substrate. An initial screen of plant substrate candidates showed an increase in specific growth rate and biomass accumulation when S. obliquus was cultured in the presence of switchgrass or yard waste compared to media alone. We observed a near doubling of microalgal dry weight when S. obliquus was grown with 0.2% ( w/v ) switchgrass under ambient CO 2 . Scanning electron microscopy (SEM) of corn stem after S. obliquus cultivation exhibited substantial phloem degradation. Transcriptomic analyses of S. obliquus during mid- and late-log phase growth revealed a dynamic metabolic landscape within many KEGG pathways. Notably, differential expression was observed for several potential glycosyl hydrolases. We also investigated the influence of switchgrass on the growth of S. obliquus at 50 L volume in mini raceway ponds to determine the scalability of this approach.
Electrocatalytic water splitting is a possible route to the expanded generation of green hydrogen; however, a long-term challenge is the requirement of fresh water as an electrolyzer feed. The use of seawater as a direct feed for electrolytic hydrogen production would alleviate fresh water needs and potentially open an avenue for locally generated hydrogen from marine hydrokinetic or off-shore power sources. One environmental limitation to seawater electrolysis is the generation of chlorine as a competitive anodic reaction. This work evaluates transition metal (W, Co, Fe, Sn, and Ru) doping of Mn-Mo-based catalysts as a strategy to suppress chlorine evolution while sustaining catalytic efficiency. Electrochemical evaluations in neutral chloride solution and raw seawater showed the promise of a novel Mn-Mo-Ru electrode system for oxygen evolution efficiency and enhanced catalytic activity. Subsequent stability testing in a flowing raw seawater flume highlighted the need for improved catalyst stability for long-term applications of Mn-Mo-Ru catalysts. This work highlights that elements known to be selective toward chlorine evolution in simple oxide form (e.g., RuO2) may display different trends in selectivity when used as isolated dopants, where Ru suppressed chlorine evolution in Mn-based catalysts.
The raw model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. The raw model output is in netCDF format as output by the WRF model, i.e., the “wrfout” files, with the files renamed for archival purposes.
The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the raw dataset type. These are unprocessed images from the LSST Commissioning Camera. This release contains 16,125 datasets of this type.
Disclosed herein are methods for preparing a hydraulic pre-concentrate enriched in rare earth elements and critical minerals, the method comprising: (a) contacting a raw material with a first base in an amount sufficient to adjust the pH to a value from about 4.0 to about 6.0, thereby forming a mixture comprising a first aqueous phase and a first solid concentrate; (b) separating the first aqueous phase from the first solid concentrate; (c) contacting the first aqueous phase with a second base in an amount sufficient to adjust the pH to a value from about 7.0 to about 9.0, thereby forming a mixture comprising a second aqueous phase and the hydraulic pre-concentrate; (d) removing the second aqueous phase and collecting the hydraulic pre-concentrate; wherein the raw material comprises rare earth elements; and wherein the hydraulic pre-concentrate is enriched in rare earth elements.
This is a composite raw gravity dataset of the Utah FORGE area taken over time from December 2018 to to June 2021. The data shows differences in local gravity at different location across Utah FORGE. Included with the gravity data is the NAD83 UTM coordinates of each station in meters. More detailed information can be found in the readme included in the data resource.
Noble gas raw data for the Hawaiian islands of Big Island, Maui, Oahu, Lanai, and Kauai. Based on results from prior phases of the Hawaii Play Fairway Analysis, this project targeted 66 wells on the islands of Hawaii, Maui, Lanai, Oahu, and Kauai for sampling of dissolved noble gases, trace metals, common ions, and the stable isotopes 2H and 18O. Ultimately, 23 of the 66 well targets were sampled. Noble gas data from this study is supplemented with data shared by the United States Geologic Survey for the summit of Kilauea, and by the geothermal energy company Ormat Technologies Inc. for their geothermal power plant Puna Geothermal Venture on the Lower East Rift of Kilauea, and for their exploration of Kona and Hualalai on Hawaii, as well as the Southwest Rift of Haleakala on Maui. The noble gas helium is used as an indicator of geothermal heat when excess 3He and/or 4He is present when compared to the atmospheric ratio of those isotopes (R/Ra). R/Ra is minimally affected by dilution and transport, allowing even those wells not perfectly situated over a geothermal system to indicate a geothermal anomaly. R/Ra anomalies are present on every island in this study. There is a strong correlation between R/Ra anomalies and proximity to rift zones and calderas. The Hawaii Play Fairway project was funded by the U.S. Department of Energy Geothermal Technologies Office (award DE-EE0006729). For more information, see Colin Ferguson's Master of Science thesis "Exploration for Blind Geothermal Resources in the State of Hawaii Utilizing Dissolved Noble Gasses in Well Waters."
Improving productivity and lipid concentration in microalgae is important for the economic success of both biofuel and microalgae coproducts production. Nannochloropsis spp. are marine microalgae currently being grown at large-scale for the production of biofuel and lipid coproducts. In this work, we demonstrate improvements of growth and omega-3 production in Nannochloropsis gaditana CCMP526 and Nannochloropsis oceanica CCAP849/10 with plant substrate addition, a potentially economical option for increasing microalgal productivity. Furthermore, we examine growth in the presence of corn stover, switchgrass, sugarcane bagasse, and yard waste. By examining the microbial ecology of N. gaditana cultures with and without plant substrate and with and without antibiotics, we discovered a potential bacterial interaction in these cultures, but its presence is not necessary for algal growth improvements in the presence of plant substrate. Analysis of plant substrate morphology by scanning electron microscopy (SEM) after cultivation in media with and without N. gaditana shows a degradation of specific plant structural features and a colonization of the plant phloem by N. gaditana. An examination of N. gaditana in a Congo red plate assay indicates potential cellulolytic activity, but a preliminary examination of the potential cellulase transcripts does not reveal differential expression of a candidate in the presence of plant. This evidence demonstrates potential raw plant utilization by a marine microalga for increased productivity and provides a potentially economical option for increasing coproduct concentration at industrial scale without genetic engineering.
Here, we investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.