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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A constraint on historic growth in global photosynthesis due to rising CO 2

Theory predicts that rising CO 2 increases global photosynthesis, a process known as CO 2 fertilization, and that this is responsible for much of the current terrestrial carbon sink. The estimated magnitude of the historic CO 2 fertilization, however, differs by an order of magnitude between long-term proxies, remote sensing-based estimates and terrestrial biosphere models. Here we constrain the likely historic effect of CO 2 on global photosynthesis by combining terrestrial biosphere models, ecological optimality theory, remote sensing approaches and an emergent constraint based on global carbon budget estimates. Our analysis suggests that CO 2 fertilization increased global annual terrestrial photosynthesis by 13.5 ± 3.5% or 15.9 ± 2.9 PgC (mean ± s.d.) between 1981 and 2020. Our results help resolve conflicting estimates of the historic sensitivity of global terrestrial photosynthesis to CO 2 and highlight the large impact anthropogenic emissions have had on ecosystems worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Air temperature optima of vegetation productivity across global biomes

The global distribution of the optimum air temperature for ecosystem-level gross primary productivity ( T $^{eco}_{opt}$) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. In this paper, we provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. T $^{eco}_{opt}$ is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average T $^{eco}_{opt}$ is estimated to be 23 ± 6 °C, with warmer regions having higher T $^{eco}_{opt}$ values than colder regions. In tropical forests in particular, T $^{eco}_{opt}$ is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning-accelerated discovery of heat-resistant polysulfates for electrostatic energy storage

The development of heat-resistant dielectric polymers that withstand intense electric fields at high temperatures is critical for electrification. Balancing thermal stability and electrical insulation, however, is exceptionally challenging as these properties are often inversely correlated. A traditional intuition-driven polymer design approach results in a slow discovery loop that limits breakthroughs. Here we present a machine learning-driven strategy to rapidly identify high-performance, heat-resistant polymers. A trustworthy feed-forward neural network is trained to predict key proxy parameters and down select polymer candidates from a library of nearly 50,000 polysulfates. The highly efficient and modular sulfur fluoride exchange click chemistry enables successful synthesis and validation of selected candidates. A polysulfate featuring a 9,9-di(naphthalene)-fluorene repeat unit exhibits excellent thermal resilience and achieves ultrahigh discharged energy density with over 90% efficiency at 200 °C. Its exceptional cycling stability underscores its promise for applications in demanding electrified environments.

Li, He↗
DOE OSTI2019

Glacially sourced dust as a potentially significant source of ice nucleating particles

Aeolian dusts serve as ice nucleating particles in mixed-phase clouds, and thereby alter the cloud properties and lifetime. Glacial outwash plains are thought to be a major dust source in cold, high latitudes. Due to the recent rapid and widespread retreat of glaciers, high-latitude dust emissions are projected to increase, especially in the Arctic region, which is highly sensitive to climate change. However, the potential contribution of high-latitude dusts to ice nucleation in Arctic low-level clouds is not well acknowledged. Here we show that glacial outwash sediments in Svalbard (a proxy for glacially sourced dusts) have a remarkably high ice nucleating ability under conditions relevant for mixed-phase cloud formation, as compared with typical mineral dusts. The high ice nucleating ability of the sediments is probably governed by the presence of small amounts of organic matter (<1 wt% organic carbon) rather than mineral components. In addition, our results from intensive field measurements and model simulations indicate that the concentrations of atmospheric ice nucleating particles over the Svalbard region are expected to be enhanced in the summertime under the influence of dust emissions from Svalbard and its surroundings. In conclusion, we suggest that high-latitude dust sources have the potential to significantly influence glaciation of Arctic low-level clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗
DOE OSTI2025

Daytime urban heat stress in North America reduced by irrigation

There is considerable uncertainty regarding the impact of irrigation on heat stress, partly stemming from the choice of heat stress index. Moreover, existing simulations are at scales that cannot appropriately resolve population centres or clouds and thus the potential for human impacts. Using multi-year convection-permitting and urban-resolving regional climate simulations, we demonstrate that irrigation alleviates summertime heat stress across more than 1,600 urban clusters in North America. This holds true for most physiologically relevant heat stress indices. The impact of irrigation varies by climate zone, with more notable irrigation signals seen for arid urban clusters that are situated near heavily irrigated fields. Through a component attribution framework, we show that irrigation-induced changes in wet-bulb temperature, often used as a moist heat stress proxy in the geosciences, exhibit an opposite sign to the corresponding changes in wet bulb globe temperature—a more complete index for assessing both indoor and outdoor heat risk—across climate zones. In contrast, the local changes in both wet-bulb and wet bulb globe temperature due to urbanization have the same sign. Here, our results demonstrate a complex relationship between irrigation and heat stress, highlighting the importance of using appropriate heat stress indices when assessing the potential for population-scale human impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Direct thermal neutron detection by the 2D semiconductor 6 LiInP 2 Se 6

Highly efficient neutron detectors are critical in many sectors, including national security, medicine, crystallography and astronomy. The main neutron detection technologies currently used involve 3 He-gas-filled proportional counters and light scintillators for thermalized neutrons. Semiconductors could provide the next generation of neutron detectors because their advantages could make them competitive with or superior to existing detectors. In particular, solids with a high concentration of high-neutron-capture nuclides (such as 6 Li, 10 B) could be used to develop smaller detectors with high intrinsic efficiencies. However, no promising materials have been reported so far for the construction of direct-conversion semiconductor detectors. Here we report on the semiconductor LiInP 2 Se 6 and demonstrate its potential as a candidate material for the direct detection of thermal neutrons at room temperature. This compound has a good thermal-neutron-capture cross-section, a suitable bandgap (2.06 electronvolts) and a favourable electronic band structure for efficient electron charge transport. We used α particles from an 241 Am source as a proxy for the neutron-capture reaction and determined that the compact two-dimensional (2D) LiInP 2 Se 6 detectors resolved the full-energy peak with an energy resolution of 13.9 per cent. Direct neutron detection from a moderated Pu–Be source was achieved using 6 Li-enriched (95 per cent) LiInP 2 Se 6 detectors with full-peak resolution. Here, we anticipate that these results will spark interest in this field and enable the replacement of 3 He counters by semiconductor-based neutron detectors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spatial and Temporal Characterization of Activity in Public Space, 2019–2020

The data reported here characterize spatial and temporal variation in the ratio of short-to-long-duration visits in public places (i.e., points of interest) in the United States for each week between January 2019 and December 2020. The underlying data on anonymized and aggregated foot traffic to public places is curated by SafeGraph, a geospatial data provider. In this work, we report the estimated number and duration of “short” (i.e., <4 hours) and “long” (i.e., >4 hours) visits to public places at the US census block group level. Long visits are shown to be a good proxy for workers based on formal economic data. We propose that short visits are more likely to represent nonobligate activities: people visiting a public place for leisure, shopping, entertainment, or civic or cultural engagement. Our work constructs a ratio of short to long visits, which can be used to inform population estimates for nonworker use of public space. These data may be useful for understanding how people’s use of public space has changed during the COVID-19 pandemic and, more generally, for understanding activity patterns in public.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Revised monthly energy generation estimates for 1,500 hydroelectric power plants in the United States

Abstract The U.S. Energy Information Administration (EIA) conducts a regular survey (form EIA-923) to collect annual and monthly net generation for more than ten thousand U.S. power plants. Approximately 90% of the ~1,500 hydroelectric plants included in this data release are surveyed at annual resolution only and thus lack actual observations of monthly generation. For each of these plants, EIA imputes monthly generation values using the combined monthly generating pattern of other hydropower plants within the corresponding census division. The imputation method neglects local hydrology and reservoir operations, rendering the monthly data unsuitable for various research applications. Here we present an alternative approach to disaggregate each unobserved plant’s reported annual generation using proxies of monthly generation—namely historical monthly reservoir releases and average river discharge rates recorded downstream of each dam. Evaluation of the new dataset demonstrates substantial and robust improvement over the current imputation method, particularly if reservoir release data are available. The new dataset—named RectifHyd—provides an alternative to EIA-923 for U.S. scale, plant-level, monthly hydropower net generation (2001–2020). RectifHyd may be used to support power system studies or analyze within-year hydropower generation behavior at various spatial scales.

13 HYDRO ENERGY↗
DOE OSTI2023

Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations

In situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP 2 EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015

Large datasets of carbon dioxide, energy, and water fluxes were measured with the eddy-covariance (EC) technique, such as FLUXNET2015. These datasets are widely used to validate remote-sensing products and benchmark models. One of the major challenges in utilizing EC-flux data is determining the spatial extent to which measurements taken at individual EC towers reflect model-grid or remote sensing pixels. To minimize the potential biases caused by the footprint-to-target area mismatch, it is important to use flux datasets with awareness of the footprint. This study analyze the spatial representativeness of global EC measurements based on the open-source FLUXNET2015 data, using the published flux footprint model (SAFE-f). The calculated annual cumulative footprint climatology (ACFC) was overlaid on land cover and vegetation index maps to create a spatial representativeness dataset of global flux towers. The dataset includes the following components: (1) the ACFC contour (ACFCC) data and areas representing 50%, 60%, 70%, and 80% ACFCC of each site, (2) the proportion of each land cover type weighted by the 80% ACFC (ACFCW), (3) the semivariogram calculated using Normalized Difference Vegetation Index (NDVI) considering the 80% ACFCW, and (4) the sensor location bias (SLB) between the 80% ACFCW and designated areas (e.g. 80% ACFCC and window sizes) proxied by NDVI. Finally, we conducted a comprehensive evaluation of the representativeness of each site from three aspects: (1) the underlying surface cover, (2) the semivariogram, and (3) the SLB between 80% ACFCW and 80% ACFCC, and categorized them into 3 levels. The goal of creating this dataset is to provide data quality guidance for international researchers to effectively utilize the FLUXNET2015 dataset in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Forty-year hydropower generation reanalysis for Conterminous United States

First published in 2022, the RectifHyd dataset provides hydrologically consistent estimates of monthly net generation for approximately 1,500 hydropower plants in the United States, addressing a gap in industrial surveys that have collected monthly generation data from only ~10% of plants post-2003. Here we present RectifHydPlus—an extended and enhanced dataset that improves on both the proxy information and temporal downscaling methodology adopted in RectifHyd. In addition to providing updated estimates of historical monthly generation for 590 plants with >10 MW nameplate capacity from 1980 through 2019, RectifHydPlus adds a hydrological control dataset that isolates the influence of historical water availability on generation. The new hydrological control dataset is suited to applications seeking to represent the capabilities of the contemporary fleet subject to historical interannual variability in climate. RectifHydPlus also includes a forty-year, daily-resolution, spill-adjusted water release time series for each dam, allowing users to aggregate generation estimates to the desired temporal resolution.

Hydroelectricity↗
DOE OSTI2019

Iterative screening methodology enables isolation of strains with improved properties for a FACS-based screen and increased L-DOPA production

Abstract Optimizing microbial hosts for the large-scale production of valuable metabolites often requires multiple mutations and modifications to the host’s genome. We describe a three-round screen for increased L-DOPA production in S. cerevisiae using FACS enrichment of an enzyme-coupled biosensor for L-DOPA. Multiple rounds of screening were enabled by a single build of a barcoded in vitro transposon-mediated disruption library. New background strains for screening were built for each iteration using results from previous iterations. The same in vitro transposon-mediated disruption library was integrated by homologous recombination into new background strains in each round of screening. Compared with creating new transposon insertions in each round, this method takes less time and saves the cost of additional sequencing to characterize transposon insertion sites. In the first two rounds of screening, we identified deletions that improved biosensor compartmentalization and, consequently, improved our ability to screen for L-DOPA production. In a final round, we discovered that deletion of heme oxygenase (HMX1) increases total heme concentration and increases L-DOPA production, using dopamine measurement as a proxy. We further demonstrated that deleting HMX1 may represent a general strategy for P450 function improvement by improving activity of a second P450 enzyme, BM3, which performs a distinct reaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Targeted detection of Dehalococcoides mccartyi microbial protein biomarkers as indicators of reductive dechlorination activity in contaminated groundwater

Dehalococcoides mccartyi ( Dhc ) bacterial strains expressing active reductive dehalogenase (RDase) enzymes play key roles in the transformation and detoxification of chlorinated pollutants, including chlorinated ethenes. Site monitoring regimes traditionally rely on qPCR to assess the presence of Dhc biomarker genes; however, this technique alone cannot directly inform about dechlorination activity. To supplement gene-centric approaches and provide a more reliable proxy for dechlorination activity, we sought to demonstrate a targeted proteomics approach that can characterize Dhc mediated dechlorination in groundwater contaminated with chlorinated ethenes. Targeted peptide selection was conducted in axenic cultures of Dhc strains 195, FL2, and BAV1. These experiments yielded 37 peptides from housekeeping and structural proteins (i.e., GroEL, EF-TU, rpL7/L2 and the S-layer), as well as proteins involved in the reductive dechlorination activity (i.e., FdhA, TceA, and BvcA). The application of targeted proteomics to a defined bacterial consortium and contaminated groundwater samples resulted in the detection of FdhA peptides, which revealed active dechlorination with Dhc strain-level resolution, and the detection of RDases peptides indicating specific reductive dechlorination steps. The results presented here show that targeted proteomics can be applied to groundwater samples and provide protein level information about Dhc dechlorination activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Nitrogen Fertilization Restructured Spatial Patterns of Soil Organic Carbon and Total Nitrogen in Switchgrass and Gamagrass Croplands in Tennessee USA

Nitrogen (N) fertilizers can potentially alter spatial distribution of soil organic carbon (SOC) and total nitrogen (TN) concentrations in croplands such as switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.), but it remains unclear whether these effects are the same between crops and under different rates of fertilization. 13 C and 15 N are two important proxy measures of soil biogeochemistry, but they were rarely examined as to their spatial distributions in soil. Based on a three-year long fertilization experiment in Middle Tennessee, USA, the top mineral horizon soils (0–15 cm) were collected using a spatially explicit design within two 15-m 2 plots under three fertilization treatments in SG and GG croplands. A total of 288 samples were collected based on 12 plots and 24 samples in each plot. The fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha -1 in urea) and high N input (HN: 168 kg N ha -1 in urea). The SOC, TN, SOC/TN (C: N), δ 13 C and δ 15 N were quantified and their within-plot variations and spatial distributions were achieved via descriptive and geostatistical methods. Results showed that SG generally displayed 10~120% higher plot-level variations in all variables than GG, and the plot-level variations were 20~77% higher in NN plots than LN and HN plots in SG but they were comparable in unfertilized and fertilized plots in GG. Relative to NN, LN and HN showed more significant surface trends and spatial structures in SOC and TN in both croplands, and the fertilization effect appeared more pronounced in SG. Spatial patterns in C: N, δ 13 C and δ 15 N were comparable among different fertilization treatments in both croplands. The descending within-plot variations were also identified among variables (SOC > TN > δ 15 N > C: N > δ 13 C). This study demonstrated that N fertilizations generally reduced the plot-level variance and simultaneously re-established spatial structures of SOC and TN in bioenergy croplands, which little varied with fertilization rate but was more responsive in switchgrass cropland.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data-driven studies of magnetic two-dimensional materials

We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A 2 B 2 X 6 , based on the known material Cr 2 Ge 2 Te 6 , using density functional theory (DFT) calculations and machine learning methods to determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability. We show that machine learning tools, combined with DFT calculations, can provide a computationally efficient means to predict properties of such two-dimensional (2D) magnetic materials. Our data analytics approach provides insights into the microscopic origins of magnetic ordering in these systems. For instance, we find that the X site strongly affects the magnetic coupling between neighboring A sites, which drives the magnetic ordering. Our approach opens new ways for rapid discovery of chemically stable vdW materials that exhibit magnetic behavior.

42 ENGINEERING↗
DOE OSTI2021

Manipulating polymer composition to create low-cost, high-fidelity sensors for indoor CO2 monitoring

Abstract Carbon dioxide (CO 2 ) has been linked to many deleterious health effects, and it has also been used as a proxy for building occupancy measurements. These applications have created a need for low-cost and low-power CO 2 sensors that can be seamlessly incorporated into existing buildings. We report a resonant mass sensor coated with a solution-processable polymer blend of poly(ethylene oxide) (PEO) and poly(ethyleneimine) (PEI) for the detection of CO 2 across multiple use conditions. Controlling the polymer blend composition and nanostructure enabled better transport of the analyte gas into the sensing layer, which allowed for significantly enhanced CO 2 sensing relative to the state of the art. Moreover, the hydrophilic nature of PEO resulted in water uptake, which provided for higher sensing sensitivity at elevated humidity conditions. Therefore, this key integration of materials and resonant sensor platform could be a potential solution in the future for CO 2 monitoring in smart infrastructure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Tailoring polyvinyl alcohol-sodium alginate (PVA-SA) hydrogel beads by controlling crosslinking pH and time

Abstract Hydrogel-encapsulated catalysts are an attractive tool for low-cost intensification of (bio)-processes. Polyvinyl alcohol-sodium alginate hydrogels crosslinked with boric acid and post-cured with sulfate (PVA-SA-BS) have been applied in bioproduction and water treatment processes, but the low pH required for crosslinking may negatively affect biocatalyst functionality. Here, we investigate how crosslinking pH (3, 4, and 5) and time (1, 2, and 8 h) affect the physicochemical, elastic, and process properties of PVA-SA-BS beads. Overall, bead properties were most affected by crosslinking pH. Beads produced at pH 3 and 4 were smaller and contained larger internal cavities, while optical coherence tomography suggested polymer cross-linking density was higher. Optical coherence elastography revealed PVA-SA-BS beads produced at pH 3 and 4 were stiffer than pH 5 beads. Dextran Blue release showed that pH 3-produced beads enabled higher diffusion rates and were more porous. Last, over a 28-day incubation, pH 3 and 4 beads lost more microspheres (as cell proxies) than beads produced at pH 5, while the latter released more polymer material. Overall, this study provides a path forward to tailor PVA-SA-BS hydrogel bead properties towards a broad range of applications, such as chemical, enzymatic, and microbially catalyzed (bio)-processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗