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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

High Speed and High Spatial Density Parameter Measurement Using Fiber Optic Sensing Technology

The present invention is an improved fiber optic sensing system (FOSS) having the ability to provide both high spatial resolution and high frequency strain measurements. The inventive hybrid FOSS fiber combines sensors from high acquisition speed and low spatial resolution Wavelength-Division Multiplexing (WDM) systems and from low acquisition speed and high spatial resolution Optical Frequency Domain Reflection (OFDR) systems. Two unique light sources utilizing different wavelengths are coupled with the hybrid FOSS fiber to generate reflected data from both the WDM sensors and OFDR sensors operating on a single fiber optic cable without incurring interference from one another. The two data sets are then de-multiplexed for analysis, optionally with conventionally-available WDM and OFDR system analyzers.

Parker, Allen R. Jr.↗
NASA NTRS2018

Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-Based Chlorophyll Fluorescence Data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, V(sub cmax) at a reference temperature of 25 deg C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, V(sub cmax), in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007-2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to V(sub cmax) at the seasonal scale (R(squared)=0.70 for C4 and R(squared)=0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking V(sub cmax) with SIF that was used to estimate spatially and temporally varying crop V(sub cmax) for the US Corn Belt region. The resulting V(sub cmax) maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite- based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal V(sub cmax) from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional V(sub cmax) using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Drought↗
NASA NTRS2018

Image Station Matching, Preprocessing, Spatial Registration and Change Detection with Multi-Temporal Remotely-Sensed Imagery

A method for collecting and processing remotely sensed imagery in order to achieve precise spatial co-registration (e.g., matched alignment) between multi-temporal image sets is presented. Such precise alignment or spatial co-registration of imagery can be used for change detection, image fusion, and temporal analysis/modeling. Further, images collected in this manner may be further processed in such a way that image frames or line arrays from corresponding photo stations are matched, co-aligned and if desired merged into a single image and/or subjected to the same processing sequence. A second methodology for automated detection of moving objects within a scene using a time series of remotely sensed imagery is also presented. Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (image registration) between multitemporal image frame sets. In addition, specialized change detection techniques are employed in order to automate the detection of moving objects.

Coulter, Lloyd Lawrence Arthur↗
NASA NTRS2019

Orbital Path and Spacecraft Attitude Correction for the MODIS Lunar Spatial Characterization

For the Moderate Resolution Imaging Spectroradiometer(MODIS) on the Terra and Aqua platforms, regularlyscheduled lunar observations using spacecraft roll maneuvershave been used extensively for sensor characterization. Whilethe primary purpose of these observations is for radiometriccalibration of the reflective solar bands, they have also beenleveraged for a number of other sensor performance assessments,such as the band-to-band (BBR) and detector-to-detector (DDR)spatial registration. The spatial registration calculations arecomplicated by the fact that the Moon does not move in astraight path across the sensor field-of-view (FOV). This path isdetermined by the relative orbital motion between the spacecraftand the Moon and the instrument attitude error that resultsfrom the roll maneuver. In this work, we develop a correctionfor the MODIS lunar spatial characterization measurements bycalculating the predicted path of the Moon across the sensor FOVusing spacecraft and lunar ephemeris data to model the relativeorbital motion between the spacecraft and the Moon along withspacecraft attitude error data acquired during the roll maneuver.The difference between measured and predicted positions of theMoon in the MODIS FOV can be used to calculate the BBRand DDR results. Since the predicted path across the FOV willbe the same for each band, the BBR results will be minimallyaffected. However, we will show that the along-scan spread inthe DDR can be significantly reduced, which results in a muchgreater consistency throughout the full mission for both Aquaand Terra MODIS.

Truman Wilson↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP – Based Satellite Soil Moisture Retrievals into SWAT Hydrological Model: the Impact of Satellite Revisit Time and Product Spatial Resolution on Flood Simulations in Small Basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR obtained via S1 over ASCAT was small likely due to very challenging areas for S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the soil moisture pre-storm conditions.

Small basins↗
NASA NTRS2020

Environmental factors driving spatial heterogeneity in desert halophile microbial communities

Spatial heterogeneity in microbial communities is observed in all-natural ecosystems and can stem from both adaptations to local environmental conditions as well as stochastic processes. Extremophile microbial communities inhabiting evaporitic halite nodules (salt rocks) in the Atacama Desert, Chile, are a good model ecosystem for investigating factors leading to microbiome heterogeneity, due to their diverse taxonomic composition and the spatial segregation of individual nodules. We investigated the abiotic factors governing microbiome composition across different spatial scales, allowing for insight into the factors that govern halite colonization from regional desert-wide scales to micro-scales within individual nodules. We found that water availability and community drift account for microbiome assembly differently at different distance scales, with higher rates of cell dispersion at the smaller scales resulting in a more homogenous composition. This trend likely applies to other endoliths, and to non desert communities, where dispersion between communities is limited. At the intra-nodule scales, a light availability gradient was most important in determining the distribution of microbial taxa despite intermixing by water displacement via capillary action.

microbiome extremophile, desert, heterogeneity, Me↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP–based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via the Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR-SWI obtained via S1 over ASCAT was small, likely due to very challenging areas for the S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the pre-storm soil moisture conditions.

Shima Azimi↗
NASA NTRS2021

Spatial Variation of Fine Particulate Matter Levels in Nairobi Before and During the COVID-19 Curfew: Implications for Environmental Justice

The temporary decrease of fine particulate matter (PM(sub 2.5)) concentrations in many parts of the world due to the COVID-19 lockdown spurred discussions on urban air pollution and health. However there has been little focus on sub-Saharan Africa, as few African cities have air quality monitors and if they do, these data are often not publicly available. Spatial differentials of changes in PM(sub 2.5) concentrations as a result of COVID also remain largely unstudied. To address this gap, we use a serendipitous mobile air quality monitoring deployment of eight Sensirion SPS 30 sensors on motorbikes in the city of Nairobi starting on 16 March 2020, before a COVID-19 curfew was imposed on 25 March and continuing until 5 May 2020. We developed a random-forest model to estimate PM(sub 2.5) surfaces for the entire city of Nairobi before and during the COVID-19 curfew. The highest PM(sub 2.5) concentrations during both periods were observed in the poor neighborhoods of Kariobangi, Mathare, Umoja, and Dandora, located to the east of the city center. Changes in PM(sub 2.5) were heterogeneous over space. PM(sub 2.5) concentrations increased during the curfew in rapidly urbanizing, the lower-middle-class neighborhoods of Kahawa, Kasarani, and Ruaraka, likely because residents switched from LPG to biomass fuels due to loss of income. Our results indicate that COVID-19 and policies to address it may have exacerbated existing air pollution inequalities in the city of Nairobi. The quantitative results are preliminary, due to sampling limitations and measurement uncertainties, as the available data came exclusively from low-cost sensors. This research serves to highlight that spatial data that is essential for understanding structural inequalities reflected in uneven air pollution burdens and differential impacts of events like the COVID pandemic. With the help of carefully deployed low cost sensors with improved spatial sampling and at least one reference-quality monitor for calibration, we can collect data that is critical for developing targeted interventions that address environmental injustice in the African context.

Environmental justice↗
NASA NTRS2021

The sensitivity of runoff generation to spatial snowpack uniformity in an alpine watershed: Green Lakes Valley, Niwot Ridge Long-Term Ecological Research station

Seasonal water storage in high-elevation alpine catchments are critical sources of water for mountainous regions like the western U.S. The spatial distribution of snow in these topographically complex catchments is primarily governed by orography, solar radiation, and wind redistribution. While the effect of solar shading is relatively consistent from year-to-year, the redistribution of snow due to wind is more variable–capable of producing snowpacks that have varying degrees of uniformity across these hydrologically-important catchments. A reasonable hypothesis is that a warmer climate will cause snowfall to become more dense (i.e. wetter and heavier), possibly leading to less wind redistribution and thus produce a more uniformly distributed snowpack across the landscape. In this study, we investigate the role of increasingly uniform spatial snowpack distributions on streamflow generation in the Green Lakes Valley Niwot Ridge Long Term Ecological Research station, within the headwaters of the Boulder Creek watershed in Colorado. A set of idealized hydrologic simulation experiments driven by reconstructed snowpacks spanning 2001–2014 show that more a more uniform spatial snowpack distribution leads to an earlier melt-out of31 days on average and tends to produce less total streamflow, with maximum decreases as large as 7.5%. Isolating the role of snowpack heterogeneity from melt-season precipitation, we find that snowpack uniformity reduces total streamflow by as much as 13.2%. Reductions in streamflow are largely explained by greater expo-sure to solar radiation in the uniformly distributed case relative to a more heterogeneous snowpack, with this exposure driving shifts towards earlier snowmelt and changes in soil water storage. Overall, we find that the runoff efficiency from shallower snowpacks is more sensitive to the effects of uniformity than deeper snowpacks, which has potential implications for a warming climate where shallower snowpacks and enhanced sensitivities may be present.

Alpine catchment↗
NASA NTRS2023

The Spatial Distribution of Soluble Organic Matter and Their Relationship to Minerals in the Asteroid (162173) Ryugu

We performed in-situ analysis on a ~1 mm-sized grain A0080 returned by the Hayabusa2 spacecraft from near-Earth asteroid (162173) Ryugu to investigate the relationship of soluble organic matter (SOM) to minerals. Desorption electrospray ionization-high resolution mass spectrometry (DESI-HRMS) imaging mapped more than 200 CHN, CHO, CHO–Na (sodium adducted), and CHNO soluble organic compounds. A heterogeneous spatial distribution was observed for different compound classes of SOM as well as among alkylated homologues on the sample surface. The A0080 sample showed mineralogy more like an Ivuna-type (CI) carbonaceous chondrite than other meteorites. It contained two different lithologies, which are either rich (lithology 1) or poor (lithology 2) in magnetite, pyrrhotite, and dolomite. CHN compounds were more concentrated in lithology 1 than in lithology 2; on the other hand, CHO, CHO–Na, and CHNO compounds were distributed in both lithologies. Such different spatial distribution of SOM is likely the result of interaction of the SOM with minerals, during precipitation of the SOM via fluid activity, or could be due to difference in transportation efficiencies of SOMs in aqueous fluid. Organic-related ions measured by time-of-flight secondary ion mass spectrometry (ToF–SIMS) did not coincide with the spatial distribution revealed by DESI-HRMS imaging. This result may be because the different ionization mechanism between DESI and SIMS, or indicate that the ToF–SIMS data would be mainly derived from methanol-insoluble organic matter in A0080. In the Orgueil meteorite, such relationship between altered minerals and SOM distributions was not observed by DESI-HRMS analysis and field-emission scanning electron microscopy, which would result from differences of SOM formation processes and sequent alteration process on the parent bodies or even on the Earth. Alkylated homologues of CHN compounds were identified in A0080 by DESI-HRMS imaging as observed in the Murchison meteorite, but not from the Orgueil meteorite. These compounds with a large C number were enriched in Murchison fragments with abundant carbonate grains. In contrast, such relationship was not observed in A0080, implying different formation or growth mechanisms for the alkylated CHN compounds by interaction with fluid and minerals on the Murchison parent body and asteroid Ryugu.

Ryugu↗
NASA NTRSDate not supplied

Springtime SEA Air Is Consistently Both Smoky and Humid, but This Relationship (and Its Radiative Effects) Varies Spatially and Seasonally

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. A previous study discussed the spatial characteristics of the water vapor-BB plume observations in the September 2016 flight data and their degree of agreement with several atmospheric reanalyses and models. In the present work, we first discuss atmospheric chemistry, structure, and aerosol results from all three ORACLES deployments to place these results in a broader seasonal context. Despite the differing locations and season of each deployment, we show that there continues to be good agreement between the airborne ORACLES dataset and large-scale reanalyses, specifically the ECMWF ERA5 and CAMS reanalyses. Other reanalyses (specifically NASA's MERRA-2) preserved the observed correlation between meteorology and biomass burning conditions, but, as was seen for 2016, was frequently displaced spatially relative to the observations. The CAMS reanalysis performs better with water vapor than with CO. Results comparing CAMS column AOD to the field measurements show slight overestimates, consistent with previous analysis, but the good relationship observed between AOD and inlet-based aerosol extinction demonstrates this metric's utility to broader studies. The good ERA5/CAMS/ORACLES agreement allows us to next examine the multi-year seasonal patterns and trends beyond the three ORACLES deployment periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalysis, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. This classification will allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗
NASA NTRSDate not supplied

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗
NASA NTRSDate not supplied

Spatially-Resolved Freestream Velocity Measurements at the NASA Langley 31-Inch Mach 10 Air Tunnel Using FLEET

Freestream velocity measurements in the NASA Langley 31-inch Mach 10 wind tunnel are reported in this paper using Femtosecond Laser Electronic Excitation Tagging (FLEET). The freestream measurements acquired during the January 2023 test campaign were the first direct measurement of freestream velocity in this hypersonic wind tunnel facility. Spatial distributions of time-averaged and instantaneous velocity measurements were obtained at all three typical wind tunnel freestream unit Reynolds number conditions of Re∞/L = 1.8∙106 m-1, 3.6∙106 m-1, and 6.4∙106 m-1, though the current paper focuses on centerline measurements for the three Re∞/L and spatial distributions for one Re∞/L. Measured values for time-averaged velocity and mean of the instantaneous velocity at the wind tunnel centerline agree within 5 m/s or 0.4% of the calculated velocity from the facility data acquisition system. Measurements acquired at locations away from the wind tunnel centerline reveal the spatial extent of the core flow of the hypersonic facility.

FLEET↗
NASA NTRSDate not supplied

Spatially-Resolved Freestream Velocity Measurements at the NASA Langley 31-Inch Mach 10 Air Tunnel Using FLEET

Freestream velocity measurements in the NASA Langley 31-inch Mach 10 wind tunnel are reported in this paper using Femtosecond Laser Electronic Excitation Tagging (FLEET). The freestream measurements acquired during the January 2023 test campaign were the first direct measurement of freestream velocity in this hypersonic wind tunnel facility. Spatial distributions of time-averaged and instantaneous velocity measurements were obtained at all three typical wind tunnel freestream unit Reynolds number conditions of Re∞/L = 1.8∙106 m-1, 3.6∙106 m-1, and 6.4∙106 m-1, though the current paper focuses on centerline measurements for the three Re∞/L and spatial distributions for one Re∞/L. Measured values for time-averaged velocity and mean of the instantaneous velocity at the wind tunnel centerline agree within 5 m/s or 0.4% of the calculated velocity from the facility data acquisition system. Measurements acquired at locations away from the wind tunnel centerline reveal the spatial extent of the core flow of the hypersonic facility.

FLEET↗
DOE OSTI2024

Quantum spatial search with multiple excitations

Spatial search is the problem of finding a marked vertex in a graph. A continuous-time quantum walk in the single-excitation subspace of an $n$ spin system solves the problem of spatial search by finding the marked vertex in $O(\sqrt{n})$ time. Here, we investigate a natural extension of the spatial search problem, marking multiple vertices of a graph, which are still marked with local fields. We prove that a continuous-time quantum walk in the $k$-excitation subspace of $n$ spins can determine the binary string of $k$ marked vertices with an asymptotic fidelity in time $O(\sqrt{n})$, despite the size of the state space growing as $O(n^k)$. Numerically, we show that this algorithm can be implemented with interactions that decay as $1/r^\alpha$, where $r$ is the distance between spins, and an $\alpha$ that is readily available in current ion trap systems.

Lewis, Dylan↗
DOE OSTI2025

A staged deep learning approach to spatial refinement in 3D temporal atmospheric transport

High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume dispersion in complex terrain. However, their high computational cost makes them impractical for applications requiring rapid responses or iterative processes, such as optimization, uncertainty quantification, or inverse modeling. To address this challenge, this work introduces the Dual-Stage Temporal Three-dimensional UNet Super-resolution (DST3D-UNet-SR) model, a highly efficient deep learning model for plume dispersion predictions. DST3D-UNet-SR is composed of two sequential modules: the temporal module (TM), which predicts the transient evolution of a plume in complex terrain from low-resolution temporal data, and the spatial refinement module (SRM), which subsequently enhances the spatial resolution of the TM predictions. We train DST3D-UNet-SR using a comprehensive dataset derived from high-resolution large eddy simulations (LES) of plume transport. We propose the DST3D-UNet-SR model to significantly accelerate LES of three-dimensional (3D) plume dispersion by three orders of magnitude. Additionally, the model demonstrates the ability to dynamically adapt to evolving conditions through the incorporation of new observational data, substantially improving prediction accuracy in high-concentration regions near the source.

3D temporal sequences↗
DOE OSTI2024

Lithiophilic CoF 2 @C hollow spheres towards spatial lithium deposition for stable lithium metal batteries

Lithium metal (LM) is a promising anode for next-generation batteries due to its high theoretical capacity and low electrode potential. Nonetheless, side reactions, volume change, and unwanted lithium dendrite growth seriously limit the practical application of LM. Herein, with the aid of a hard template approach, a novel lithiophilic CoF 2 -carbon hollow sphere (CoF 2 @C-HS) composite material is successfully prepared via a facile in-situ fluorination and etching strategy. The lithiophilic CoF 2 acts as nucleation sites to reduce nucleation overpotential as well as induces the spatial Li deposition and the formation of LiF-rich solid electrolyte interphase (SEI), and the hollow carbon matrix can enhance the electrical conductivity and offer free space for LM deposition. Theoretical simulations reveal that the synergistic effect of lithiophilic CoF 2 and hollow carbon matrix homogenizes the electric field distribution and Li + flux. Benefiting from these advantages, the CoF 2 @C-HS-modified copper substrate electrode delivers an enhanced Coulombic efficiency (CE) of 93.7% for 280 cycles at 1 mA cm –2 and 1 mA h cm –2 . The symmetrical cell using CoF 2 @C-HS can stably cycle more than 1800 h with a low voltage hysteresis of 11 mV at a current density of 0.5 mA cm –2 and an areal capacity of 0.5 mA h cm –2 . Moreover, the Li@CoF 2 @C-HS composite anode enables more than 300 stable cycles at 1 C with a capacity retention of 95% in LiFePO 4 -based full cell and 110 stable cycles at 1 C in LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811)-based high-voltage full cell. Finally, this work might shed a new light on designing lithiophilic hosts to spatially confine LM deposition, realizing dendrite-free LM anodes and the practical applications of LM batteries.

25 ENERGY STORAGE↗