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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Trends and limits of CO 2 capture in solid and liquid sorbents at standard conditions

Carbon capture and storage (CCS) plays a critical role in achieving climate change mitigation targets, offering a pathway to decarbonize power generation, industrial processes, and heat production while addressing atmospheric CO 2 removal. While CCS technologies are technically advanced, the widespread adoption of 100 % CO 2 capture capacities such as 1 mol of CO 2 /mol of material and 1 g CO 2 /g storage (targeted by the DARPA, Defense Sciences Office, USA Govt.) has raised questions about the feasibility of achieving higher capture capacities. In the context of limiting global warming to 1.5°C, reaching 100 % CO 2 capture capacity is increasingly necessary, with residual emissions requiring complementary carbon dioxide removal (CDR) technologies. This review exclusively focuses on the CO 2 capture capacities of various sorbents under standard conditions, using different evaluation metrics. This study explores the performance of solid and liquid sorbents under standard conditions, analyzing factors including surface area, pore structure, solvent type, and functionalization to identify materials optimized for industrial-scale CCS applications. Emerging sorbents, including ILs, MOFs, COFs, POPs, DES, RCC, hybrid materials, and reactive sorbents, offer significant potential for enhanced selectivity and energy-efficient regeneration. Through a systematic assessment of gravimetric, volumetric, and molar capacities, the study provides insights into material efficiencies and trade-offs, offering guidance on optimizing sorbent selection for specific applications. The research advances understanding of scalable CCS technologies, contributing to global efforts to achieve net-zero emissions and address the pressing challenge of climate change.

Absorption↗
DOE OSTI2026

Quantifying the relationship between electric field enhancement and plasmon-driven electron transfer

Plasmonic materials interact strongly with light to create localized, out-of-equilibrium environments with intense electromagnetic fields known as hotspots. After forming, hotspots dissipate energy into their surroundings and can transfer energy and charge carriers to nearby molecules, giving plasmonic materials the potential to drive reactions with sunlight. However, the field needs a better mechanistic understanding of plasmon–molecule interactions and how the local plasmon environment, specifically the electromagnetic field enhancement and spatial distribution of hotspots, impacts the reaction yield. Here, in this work, we mapped plasmon-driven charge transfer across ordered plasmonic substrates using diffraction-limited surface-enhanced Raman spectroscopy (SERS) microscopy to understand the relationship between the average local electric field enhancement and charge transfer reaction yield. We tracked the plasmon-induced electron transfer to buckminsterfullerene (C 60 ) and found that areas with the greatest SERS intensity were not the areas with the greatest ensemble-averaged reduction of C 60 , suggesting that areas with higher electric field enhancement—or “hotter,” more enhancing hotspots—do not improve the charge transfer reaction yield. This work shows that efforts to improve plasmon-driven charge transfer should not merely focus on creating substrates with extremely enhancing regions but also consider how other factors could optimize photoreduction yields.

Koble, MaKenna M. [Univ. of Minnesota, Minneapolis↗
DOE OSTI2026

Scalable Solar Fuels Production in A Reactor Train System by Thermochemical Redox Cycling of Novel Nonstoichiometric Perovskites

Hydrogen production via two-step thermochemical water splitting redox cycles using nonstoichiometric redox-active metal oxides has the potential to dramatically increase fuel production rates. At moderate-to-low water splitting temperatures, surface reaction kinetics co-limit the process. In such cases, stable and high surface area microstructures that allow exploitation of the full thermodynamic potential of the materials are essential as is tight thermal integration of the reactor module. This project’s goals were the development of novel nonstoichiometric perovskite oxides with high stability and favorable thermodynamic and kinetic properties, to optimize their microstructure for maximizing the fuel productivity, and to build a prototype reactor train system (RTS) comprising at least one reactor to meet specific performance targets: (1) capable of an in-house solar thermochemical hydrogen (STCH) productivity ≥ 12 mL g -1 for stable continuous operation ≥ 20 cycles; and (2) demonstration of scalable solar fuels production at practical solar reactor level in an industrial-scale concentrated solar tower (CST) using developed perovskites to achieve a hydrogen production rate ≥ 1 g h -1 .

08 HYDROGEN↗
DOE OSTI2025

Structure-dependent mechanisms for plastic degradation in the marine environment

The visible and invisible accumulation of waste plastic in our oceans is a consequence of rapidly increasing inputs and very slow degradation rates. In general, this combination of effects results in long residence times. Nevertheless, the abiological degradation rate of a specific synthetic plastic varies widely, depending on its structural characteristics at the molecular, mesoscopic, and macroscopic levels. This chapter summarizes factors that determine these rates of degradation, and describes their principal mechanisms, for several of the major types of waste plastic found in the oceans. Mechanical forces cause cracking and flaking that break macroplastics into microplastics and even smaller fragments with increasing surface-to-volume ratios. Chemical degradation rates increase with surface area, influenced by intrinsic variations in crystallinity and the presence of additives, as well as extrinsic factors such as temperature, pH, and UV light intensity. Since polyolefin-based plastics are less dense than seawater and lack hydrolysable bonds in their polymer backbones, they accumulate close to the surface of the ocean where photo-oxidation is the principal cause of C–C bond cleavage in the polymer backbone. In contrast, polyesters and polyamides are denser than seawater and they sink, experiencing less exposure to solar irradiation. However, they can also degrade by slow hydrolysis of the C–O or C–N bonds intrinsic to the polymer structures.

Maciulis, Nicholas A.↗
DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2024

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska: Modeling Archive

The dataset is a model output used in a study that examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. The study highlights the importance of mechanistically representing hillslope-scale coupled surface and sub-surface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems. The dataset contain ecosys model outputs used in a study: Article Title - Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska. It includes the data files (ten *.csv files) used in creating figures in the publication and three *.pdf files (user guide and two Supplementary Information documents).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hot Hydrogen Exposure of U x Zr 1-x C y Nuclear Fuel: The Influence of Composition and Density

Refractory carbide nuclear fuel has been one of the most promising fuel candidates for space nuclear propulsion due to its high melting point, temperature stability, and compatibility in a hot hydrogen environment. In this study, U x Zr 1-x C y fuel was produced by means of a carbothermic reduction process in different UC compositions including 5,10, 20, and 30 at.% UC in the fuel compound. The powder feedstock was consolidated via direct current sintering with densities up to 97% of the theoretical density. The samples with different U x Zr 1-x C y compositions were exposed to hot hydrogen at 2600 K for a cumulative time of 300 min. The samples were characterized by SEM, XRD, density, and measured for mass losses. The high-density samples displayed improved performance in hot hydrogen by minimizing porous sites and reducing areas of direct contact with hydrogen gas, leading to reduced mass losses. Variations in sample density proved to induce large changes in mass loss rates, increasing them up to 90%. The compositions with higher UC content reported the largest mass losses in the study. The loss of uranium occurred primarily at the surfaces exposed to the hot hydrogen where changes in the lattice constant confirmed losses exceeding 50% of the initial UC content in higher compositions, specifically to U 0.3 Zr 0.7 C y . XRD analyses revealed the presence of UH 3 in U 0.3 Zr 0.7 C y suggesting that metallic uranium formed inside the sample as a product of carbon losses. High-density U x Zr x-1 C y fuel with UC concentrations at or below 20 at.% UC exhibited stability and negligible density changes in a high temperature hydrogen environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Atmospheric Gases as Quantitative Indicators of Urbanization Across Land-Use Gradients

The urban heat island (UHI) effect is a significant phenomenon characterized by higher surface temperatures in cities compared to surrounding rural areas. This change in the Earth's energy balance presents considerable challenges for urban populations, increasing heat exposure, straining energy infrastructure, and exacerbating health vulnerabilities. Quantifying UHI intensity is challenging due to blurred distinctions between urban and rural areas as land-use patterns evolve. To address this challenge, the present study builds on the framework established by Salvador et al. (2025) and investigates the use of atmospheric constituents, specifically volatile organic compounds (VOCs) and inorganic gases, as tracers of urbanization levels. A key improvement in this approach is the inclusion of a designated true rural site for comparison. Field measurements were conducted at two locations in the Southeastern United States during the summer of 2025. Inorganic gases were monitored continuously, while VOC samples were collected biweekly and analyzed using a proton transfer reaction time-of-flight mass spectrometer. The urban site exhibited elevated concentrations of anthropogenic inorganic gases, with carbon monoxide and nitrogen dioxide averaging 878 ppb and 17.99 ppb, respectively. In contrast, the rural site showed lower levels of these pollutants, 796 ppb for carbon monoxide and 12.46 ppb for nitrogen dioxide, while displaying higher concentrations of biogenic VOCs, including isoprene and monoterpenes at 1.24 ppb and 0.08 ppb, respectively. Extended mass spectral analyses revealed distinct chemical differences between the two sites, supporting the observed variability of major gases. Overall, these findings are consistent with our previous research and highlight the value of atmospheric constituents as effective indicators of urbanization, thereby improving our understanding of UHI dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Global scale assessment of urban precipitation anomalies

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with larger populations, pronounced urban heat island effects, and higher aerosol loads also show noticeable precipitation enhancements. This research maps global urban rainfall hotspots, establishing a foundation for the consideration of urban rainfall corrections in climatology datasets. This advancement holds promise for projecting extreme precipitation and fostering the development of more resilient cities in the future.

Science & Technology - Other Topics↗
DOE OSTI2024

Active Layer Depth and Permafrost Temperatures at the Teller 47 Field Site, Seward Peninsula, Alaska, 2022

With extreme climate warming in the Arctic, there is increasing focus on mapping permafrost stability and improving understanding of the impacts of thawing permafrost. Summer active layer depths and temperatures at the top of the permafrost were collected at the Teller 47 field site on the Seward Peninsula, Alaska to better understand permafrost thermal state in areas of discontinuous permafrost. Measurements were taken between August 14th and August 20th, 2022. Active layer depths were measured with a 120 cm thaw probe, and temperature measurements were taken with a SpotOn Temperature probe at the top of permafrost and at a maximum depth of XYZ, when no near-surface permafrost (within 120 cm of the surface) was present. Measurements were co-located with ground surface displacement measurements, which can be found in the associated dataset, NGA254. Precise location data were collected at each observation point using a GNSS RTK GPS unit. This dataset contains a *.csv file of permafrost temperature and active layer depths and a *.kml file of measurement locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ground surface temperature derived Snow Cover Properties, Seward Peninsula, Alaska, 2019-2023

Snow-ground interface temperatures have been collected at the Teller mile marker 27 and Kougarok mile marker 64 field sites on the Seward Peninsula, Alaska from 2019 through 2023 (with data missing from Fall 2020 through Summer 2021 due to COVID). Temperatures were measured using iButton Link DS1921G-F5# Thermochron miniature temperature sensors and Tinytag TGP-4017 internal sensors deployed across the Kougarok 64 and Teller 27 field sites. These sensors are a cost-efficient way to collect snow-ground interface temperatures at a high spatial resolution, and when paired with air temperature data these measurements can provide insight into fine-scale variability in snowpack characteristics across the study sites. From this data, snow process metrics were calculated at each sensor location based on the methods outlined in Staub and Delaloye, 2017. Metrics are calculated daily for each sensor as well as over the entire season. These metrics include ground surface temperature (°C), the number of days under snow cover (number of days), the insulation effect of snow (unitless), the length of the transitional snow periods (number of days), as well as intermediaries such as temperature variability. Calculating these snow processes relies on the assumption that when snow covers a temperature sensor, it is buffered from diurnal fluctuations in air temperature by the insulating snow layer. More information on the calculated metrics can be found in the User Guide of this dataset, as well as in Staub and Delaloye’s 2017 publication Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications. This dataset includes one daily and one seasonal *.csv file of metrics for every year of data, a daily and a seasonal *.csv data dictionary, and one User Guide document (*.pdf) describing data collection and processing.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advancing Porous Carbons: Understanding the Importance of Surface Chemistry for the Energy–Environment Nexus

This review intends, in a critical way, the comprehensive view of the importance of porous carbons surface chemistry for their applications in an energy− environment nexus. Surface chemistry is presented as a combination of functional heteroatom-containing groups, dopants, and structural defects. First, we briefly address carbon surface chemical environment and the methods of its modification and characterization, indicating their practical limitations. Then, the effects of surface chemistry on separation, catalysis, energy storage, sensing and microwave absorption are introduced. Besides a critical analysis of published findings on these topics, we also include our views on the advancement in the processes which rely on porous carbons surface chemistry, and identify strategic areas and directions that should deserve further attention. We focus on new findings and important original contributions to the field. Since the community of carbon researchers grows following the strategic application of these materials, the role of functional groups, dopants and structural defects in various cutting-edge applications is emphasized, showing the progress in the field and the evolution of findings. A clear determination of the effects of carbon surface is often a challenge since carbons porosity and the locations of specific bonds/sites/ defects in the carbon texture provide nanoconfinement effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reference Site Conditions for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. In addition to providing curated reference site condition datasets for four U.S. areas, our assessment highlights the need for more publicly available metocean and soil condition data.

17 WIND ENERGY↗
DOE OSTI2025

Synthesis of multicomponent oxygen evolution reaction coatings via block copolymer templating with vapor- and solution-phase precursors

Porous mixed transition metal oxide heterostructures are promising electrocatalysts due to their high surface area. However, achieving conformal multicomponent oxide coatings with controlled nanoscale architectures remains challenging. Here, we report a synthesis strategy that integrates solution-based swelling infiltration (SBI) with gas-phase sequential infiltration synthesis (SIS) in a block copolymer template to fabricate porous, high-surface-area, conformal mixed-oxide electrocatalytic coatings. In this approach, a PS75-P4VP25 block copolymer (BCP) film is first infiltrated with transition metal acetylacetonate precursors via SBI, followed by exposure to gas phase precursors of ZnO via SIS process. Thermal annealing of the infiltrated BCP films converts them into all-inorganic Fe–ZnO, Fe–Co–ZnO, and Fe–Ni–ZnO coatings. Electrochemical testing on 70 nm thick conformal coatings demonstrates promising oxygen evolution reaction (OER) activity in alkaline media, with mass-specific current densities up to 1.0 × 10 5 mA/g at an overpotential of 330 mV (vs. RHE) at ultralow loading (~0.005 g/cm 2 ). Among the compositions, Fe–Co–ZnO and amorphous Fe–Ni–ZnO show the best OER performance, delivering current densities of 2.00 and 3.04 mA/cm 2 , respectively, compared to 1.52 mA/cm 2 for Fe–ZnO.. This work establishes SBI–SIS as a versatile route for fabricating nm-thin, high-performance multicomponent oxide heterostructures on cost-efficient supports, enabling efficient catalyst utilization in electrochemical energy conversion application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2024

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr −1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr −1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10 3 ± 0.9×10 3 km 3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Nelson, Jacob A.↗
DOE OSTI2024

Switchable planar chirality and spin texture in highly ordered ferroelectric hybrid perovskite domains

Chiral organic-inorganic hybrid perovskites offer a promising platform for developing non-linear chiro-optical applications and chiral-induced spin selectivity. Here, we show that achiral hybrid perovskites that have highly ordered ferroelectric domains with orthogonal polarization exhibit planar chirality, as manifested by second harmonic generation with strong circular dichroism. Interestingly, the handedness of the second harmonic generation circular dichroism response can be alternatingly switched between orthogonally polarized domains and domain walls. To correlate the origin of planar chirality in these domains, atom-resolved atomic force microscopy is used to reveal distinct arrangements of atomic rows in these ferroelectric crystals that indicate planar symmetry breaking. Remarkably, a large SHG anisotropy factor of 0.41 is measured at the domain wall. Additionally, spatially resolved two-photon photoluminescence excitation measurement provide evidence of larger Rashba spin-splitting in these chiral ferroelectric domains compared to domain-free areas. Our discoveries of domain-dependent planar chirality and spin texture hold great promise for advancement of domain-specific chiro-optical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗