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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Comparison of the Arrhenius parameters between conventional hydrothermal and microwave-assisted synthesis methods for tin oxide nanoparticles

Microwave (MW) irradiation has emerged as a powerful tool for accelerating materials synthesis, yet the origins of its specific influence on reaction kinetics remain elusive. While multiple studies have attributed the observed enhancements in reaction rates under MW heating to reduced activation energies, other accounts have suggested modifications to the Arrhenius pre-exponential factor as the predominant cause. Distinguishing between these parameters in modern applications of MW processing in nanomaterials requires experimental approaches capable of resolving the dynamic and nuanced structural kinetics that govern MW-assisted chemistry. Here, we combine in-situ synchrotron X-ray total scattering with pair distribution function (PDF) analysis to track the structural evolution of SnO 2 nanoparticles synthesized via MW-assisted and conventional hydrothermal conditions. Avrami modeling and Arrhenius analysis suggest that although MW irradiation yields a higher apparent activation energy, the enhanced crystallization is better explained by a pre-exponential factor several orders of magnitude larger than that of conventional heating. These findings suggest that the MW field induces a higher frequency of successful molecular rearrangements rather than lowering the intrinsic activation barrier. The results contribute further insights clarifying the role of the applied MW field for materials design where MW-specific effects can be deliberately harnessed. Furthermore, this work presents a framework promoting the utility of in-situ PDF characterization coupled with kinetic analysis for developing more sophisticated descriptions of nanoscale transformations for MW-driven reaction kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Deep generative learning of magnetic frustration in artificial spin ice from magnetic force microscopy images

Increasingly large datasets of microscopic images with nanoscale resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images of honeycomb lattice spin-ice samples serve as datasets from which we automate the calculation of net magnetic moments and directional orientations of spin-ice configurations. In the first stage of our workflow, machine learning models are trained to accurately predict magnetic moments and directions within spin-ice structures. Variational Autoencoders (VAEs), an emergent unsupervised deep learning technique, are employed to generate high-quality synthetic magnetic force microscopy (MFM) images and extract latent feature representations, thereby reducing experimental and segmentation errors. The second stage of proposed methodology enables precise identification and prediction of frustrated vertices and nanomagnetic segments, effectively correlating structural and functional aspects of microscopic images. This facilitates the design of optimized spin-ice configurations with controlled frustration patterns, enabling potential on-demand synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chemically and Mechanically Recyclable Vitrimers from Carbon Dioxide-Based Polycarbonates

Designing thermoset materials with dynamic crosslinks is an important strategy to mitigate rising global carbon dioxide emission levels. The development of polymers from sustainable feedstocks, with efficient manufacturing methods, for high-value applications, and with circular end-of-use solutions is essential for advancing material technologies. One approach involves exploiting carbon dioxide itself as feedstock to create high performance, sustainable materials, by enchaining 50 mol% CO2 via copolymerization with epoxides to yield polycarbonates. This work describes the synthesis, end-functionalization, and curing of poly(propylene carbonate) (PPC) and poly(cyclohexene carbonate) (PCHC) into beta-hydroxy ester vitrimers. These vitrimers demonstrate the ability to be mechanically reprocessed up to 3 times with retention of the material’s properties through dynamic transesterification exchange reactions. The polycarbonate vitrimers with gel fractions exceeding 90 % exhibit high tensile strength (> 50 MPa) and Young’s modulus (> 2 GPa), achieved by varying repeat unit structure in the polymer backbone from the low Tg PPC to the more rigid high Tg PCHC structures. Owing to an entropically favorable chain back-biting mechanism, the network chains can be cleaved and depolymerized into cyclic small molecules. In the case of PCHC, this process enables repolymerization back to polycarbonates with 69 wt.% CO2 retention through life-cycles. The promising mechanical performance and recyclability of these CO2-based polycarbonate vitrimers indicate their potential for sustainable, high-performance materials, paving the way for future innovations in circular polymer technologies and carbon capture utilization.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Biobased Flame Retardants Towards Sustainable Building Materials with Low Embodied Carbon

Incorporation of fire retardants in different types of products is one of the essential steps in the material production process to minimize fire risk and meet fire safety requirements. A variety of commonly used flame retardants based on halogen, mineral, and other compounds has gained popularity due to their efficient flame-retardant behaviors. However, especially in the case of halides, there are numerous toxicity related issues and environmental pollution effects that have urged the building sector to deviate from their use and focus on the development of non-toxic alternatives. Therefore, to enhance the safety of flame retardants, the synthesis of flame retardants from waste feedstocks using phosphorous chemistry with a dual flame-retardant mechanism has been established. A range of waste feedstocks that include cardanol, vanillin, and gallic acids has been converted into a series of flame retardants using a one-step approach by incorporating phosphorous moieties into their structures. The established pathways allow to develop a range of flame-retardant materials by converting waste feedstocks into phosphorous-based materials with inherent flame retardancy. The introduction of abundant aromatic structures from biobased feedstocks enables high charring capabilities in materials in which these biobased flame retardants have been incorporated, increasing their char yields which significantly enhances the flame suppressing properties of the designed materials. Studies show that inclusion of phosphoric moieties into structures allows the displacement of flame enhancing radicals, by releasing non-flammable and non-toxic gases, therefore inhibiting the spread of fire in the gas phase. The resulting biobased flame retardants have been incorporated in wood substrates, foam insulation, and hemp fibers where the results show that only 1-5% of loading of biobased flame retardant suppressed the flame completely. This study represents a novel approach for the development of flame retardants with high performance while utilizing waste feedstocks as a source for their design.

Demchuk, Zoriana [ORNL] (ORCID:0000000326292235)↗
DOE OSTI2025

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗
DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗
DOE OSTI2025

Mechanistic insights into nitrogen activation on atomic Ru clusters in self-pillared pentasil using operando atomistic models and experimental kinetics

Alternative catalysts to the industrial Haber Bosch process have been of significant interest in the field of heterogeneous catalysis, yet realizing ammonia synthesis under mild conditions (e.g., 300 °C and 10 bar) is challenging due to the low per-pass conversion. One strategy is to promote the associative ammonia synthesis mechanism which eschews direct N-N bond cleavage. Here, in this work, we use self-pillared pentasil, a self-pillared hierarchical zeolite built by thin MFI zeolite nanosheets, as a support for subnanometric Ru clusters to synthesize ammonia. We show that Ru remains well-dispersed during reaction and further demonstrate that ammonia synthesis rates are higher than Cs-Ru/MgO. Reaction kinetics show a positive order in H 2 providing evidence for the associative mechanism, which then becomes negative in H 2 if Ru is allowed to aggregate into nanoparticles. Operando Density Functional Theory models for Ru speciation in SPP, free energy diagrams, and microkinetic modeling were then applied to develop a reaction mechanism that involves sequential hydrogenation of N 2 from metallic Ru clusters. For this hydrogenation to occur, there are site requirements for N 2 to adopt a bridge-bound configuration that facilitates sequential hydrogenation on single sites and metal clusters. These site requirements in turn inform the design of improved zeolite-supported ammonia synthesis catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Biogas sequestration to carbon nanofibers via tandem catalytic strategies

Upgrading decentralized biogas represents a sustainable route to produce valuable products while mitigating two potent greenhouse gases, namely, methane (CH 4 ) and carbon dioxide (CO 2 ). Conventional dry reforming of CH 4 with CO 2 yields syngas with low H 2 /CO ratios (≤1) and requires high temperatures (>800 °C) to overcome equilibrium constraints and abate coke deposition, which limits commercial implementation. Here we demonstrate the conversion of biogas into value-added carbon nanofibers via reaction integration in tandem reactors, while reducing the reaction temperature, shifting equilibrium limits and yielding H 2 -enriched syngas (H 2 /CO = 2–3) as a byproduct. Experimental and theoretical insights reveal that potassium (K) modification enhances carbon nanofiber formation due to synergistic effects via a balanced interplay between KO x -induced cobalt facets and cobalt carbide species. In conclusion, the energy cost and CO 2 footprint analyses highlight the potential advantages of tandem processes for the sustainable upgrading of biogas into valuable solid carbon products.

09 BIOMASS FUELS↗
DOE OSTI2026

Development of a Techno-Economic Analysis Framework for a Solar Thermochemical Fuel Production Process

Synthetic liquid fuels can provide a drop-in substitute for fossil-based fuels in sectors such as aviation and maritime, where electrification is not a viable option due to the need for high specific energy density. However, for these alternative fuels to be adopted at a commercial scale, their price must be competitive compared to their fossil-based counterparts. The reverse water-gas shift (RWGS) reaction offers a promising pathway, using hydrogen (sourced from electrolysis) and carbon dioxide as the feed and reacting to produce syngas - a mixture of H2 and CO at a specific ratio. Syngas is a useful precursor that can be converted into fuels and chemicals via known downstream processes, such as liquid transportation fuels via Fischer-Tropsch (FT) synthesis. The RWGS reaction is currently not applied in commercial scale, unlike the rest of the components in the process chain (electrolyzers and syngas-to-fuel synthesis units). The RWGS reaction poses several challenges due to its restrictive thermodynamics. Being an equimolar reaction, high temperatures and a large excess of H2 are needed to achieve reasonable CO2 conversion at equilibrium. This has detrimental effects on practical process implementation and the quality of syngas that can be produced, with direct effect on the energy and capital requirements, as well as the need for expensive downstream separation. In this work, we are proposing to develop a new concentrating solar thermal (CST) compatible RWGS reactor, performing the reaction in a 2-step chemical looping process using metal oxide at a temperature range of 600-800 degrees Celsius. By decoupling the reactor from the solar receiver, the Generation 3 (Gen3) CST technology could be utilized, together with its proposed thermal energy storage (TES) technology, benefitting from a good match to the required temperatures. CST technology is a viable option for supplying the heat that could be rapidly deployed in scale, thus being a good match to the gas-to-liquid (GTL) process which requires a large minimal scale to be commercially viable. The integration of TES with CST also allows operating the plant at large annual capacity factors and avoids multiple shutdown/startup cycles, thus fitting into the steady-state operation mode that most GTL processes require. The main innovation in the proposed design hinges on a countercurrent reaction design using a packed bed reactor. In 2019 Metcalfe et al. showed the benefits of countercurrent species exchange could be realized in a redox chemical-looping processes, by storing the favorable countercurrent chemical potential profiles in a packed bed of non-stoichiometric oxide. Metcalfe et al. applied this breakthrough concept to the WGS reaction, which is conventionally a co-feed catalytic process, showing a dramatic improvement. Bulfin et al. (2023) performed a similar proof-of-concept demonstration for the RWGS reaction using CeO2, achieving cumulative and peak CO2 conversions of 88% and 95%, respectively, compared to a thermodynamic limit of 58% for the co-feed catalytic process at the same conditions. In our new REGENLOOP project, we are developing a reactor prototype from the heat-exchange packed bed reactor-type, a commonly used reactor in the chemical industry. The endothermic heat of reduction will be supplied to the reactor using CST, while the same heat transfer fluid (HTF) mechanism will be used to extract the exothermic heat of oxidation. An array of multiple reactors is used to supply constant high-purity CO stream, that is then mixed with H2 from electrolysis to produce a high-purity syngas at the required composition. By removing the CO-CO2 separation after the RWGS process, significant energy and cost reduction can be achieved. A physics-based TEA framework is currently being developed, covering all the major plant processes, from the solar collection through storage, chemical looping RWGS, GTL, and auxiliary unit operations, up to the liquid hydrocarbon product. This modeling framework will utilize reduced-order models for the chemical looping RWGS and TES, CST modeling using SolarPILOT, and Aspen Plus for the GTL. By using this combined physics-based approach, the effects of design/operating parameters on the performance and cost can be elucidated. In our presentation, the modeling framework will be presented in detail, including preliminary cost predictions of using this plant configuration under a few selected relevant case studies. This study will be used to identify the major cost drivers, informing further system design and optimization needed to chart the way for a commercially viable pathway.

14 SOLAR ENERGY↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. 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 OSTI2024

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

2D in-Plane Ordered MXene Nanosheets Derived from (Mo 2/3 Er 1/3 ) 2 AlC Rare-Earth i-MAX for Energy Storage Applications

MXenes have become one of the most versatile families of two-dimensional (2D) materials due to their high conductivity, hydrophilicity, and remarkable electrochemical performance. This has stimulated intense efforts to design and synthesize MXenes, including structurally unique in-plane ordered 2D MXenes called i-MXenes. Here, we have synthesized the quaternary rare earth (RE)-based i-MAX phase (Mo 2/3 Er 1/3 ) 2 AlC using an arc melting method, and the corresponding 2D i-MXene was then obtained through a LiF/HCl soft etching process. Literature studies have shown that Al and the RE element are etched out during the etching process, leading to the formation of pure vacancy-ordered Mo1.33C 2D i-MXene. However, our investigation reveals that upon exposure to a fluorine solution, the i-MAX phase forms RE fluoride impurities, which are challenging to remove through HCl−DI water washing and persist in the final product, resulting in impure Mo 1.33 C@Er i-MXene. These results were confirmed by various characterizations such as X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, and scanning transmission electron microscopy. Although the Mo 1.33 C@Er electrode showed a 24-fold increase in specific capacitance compared to its parent i-MAX phase, it still exhibited a high charge-transfer resistance arising from the insulating nature of RE fluoride byproducts, which adversely influence the overall capacitance behavior of the synthesized 2D Mo 1.33 C@Er i-MXenes. This study contributes to identifying pathways for the preparation of pure 2D i-MXenes from RE-based i-MAX phases and developing improved synthesis methods. With additional process optimization, the 2D i-MXene holds a strong potential for electrochemical energy storage applications. Additionally, the electronic structures of Mo 1.33 C were theoretically studied using first-principles density functional theory calculations, which revealed that pristine Mo 1.33 C is metallic, and this metallic nature is preserved even with −O, −F, and mixed functionalization.

chemical structure↗
DOE OSTI2025

Topography, surface water distribution and subsurface structure in 2023 across an Arctic coastal tundra site near Utqiagvik, Alaska

Subsurface electrical resistivity tomography (ERT), active layer thickness measurements, photogrammetry, and topographic data were collected in September 2023 along a 475 m long, 20 m wide corridor that traverses various polygon types within the Barrow Environmental Observatory (BEO) on the Alaskan Arctic Coastal Plain, approximately 4 miles from the Beaufort Sea near Utqiaġvik, Alaska. These measurements were designed to assess decadal changes in surface water distribution, topography, and subsurface structure across this dynamic landscape. This archive contains the datasets acquired in 2023 and references to the datasets acquired previously at the same location. The ERT survey was conducted along the 475 m transect using 0.5 m electrode spacing and a roll-along acquisition strategy. Thaw layer thicknesses were measured with a tile probe along the same transect. Photogrammetry data were acquired using an unoccupied aerial vehicle (UAV) and were used to generate a digital elevation model and an RGB mosaic. A real-time kinematic (RTK) GPS was used to survey the ERT electrodes and the ground control points for the aerial imagery. The dataset contains 5 *.csv data files, 6 *.csv metadata files, and 6 *.tif files.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

Hierarchical Hybrid Multifunctional Materials through Interface Engineering

This project focuses on the development of stimuli-responsive hybrid multifunctional materials. We place emphasis on the design, synthesis, structural characterization, evaluation of functional properties (electronic, thermal and optical) of several (1-x)Cu 2 Se/(x)WBGS hierarchical bulk composites between Cu 2 Se, a narrow band gap semiconductor (NBGS), with a range of wider band gap semiconductors (WBGS) such as CuMSe 2 (M = Al, Ga, In, Fe, Cr) and Cu 4 TiSe 4 . Cu2Se is a well-studied NBGS with excellent thermoelectric properties (high electrical conductivity, large thermopower, etc.) while CuMSe 2 and Cu 4 TiSe 4 are high performance solar absorber materials (large band gap, large absorption coefficient, etc.). Our primary objectives are (i) to demonstrate the ability to integrate dissimilar functional properties such as large optical absorption coefficient and high electronic conductivity, within (1-x)Cu 2 Se/(x)WBGS composite; and (ii) to establish the correlation between the hierarchical structural entanglement of Cu 2 Se with WBGS (CuMSe 2 or Cu 4 TiSe 4 ) phase, the interactions between native electronic defects within the coexisting phases in the resulting (1-x)Cu 2 Se/(x)WBGS bulk composites , and the impacts on their electronic conductivity, thermal transport and optical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Review of Nanocarbon-Based Anode Materials for Lithium-Ion Batteries

Renewable and non-renewable energy harvesting and its storage are important components of our everyday economic processes. Lithium-ion batteries (LIBs), with their rechargeable features, high open-circuit voltage, and potential large energy capacities, are one of the ideal alternatives for addressing that endeavor. Despite their widespread use, improving LIBs’ performance, such as increasing energy density demand, stability, and safety, remains a significant problem. The anode is an important component in LIBs and determines battery performance. To achieve high-performance batteries, anode subsystems must have a high capacity for ion intercalation/adsorption, high efficiency during charging and discharging operations, minimal reactivity to the electrolyte, excellent cyclability, and non-toxic operation. Group IV elements (Si, Ge, and Sn), transition-metal oxides, nitrides, sulfides, and transition-metal carbonates have all been tested as LIB anode materials. However, these materials have low rate capability due to weak conductivity, dismal cyclability, and fast capacity fading owing to large volume expansion and severe electrode collapse during the cycle operations. Contrarily, carbon nanostructures (1D, 2D, and 3D) have the potential to be employed as anode materials for LIBs due to their large buffer space and Li-ion conductivity. However, their capacity is limited. Blending these two material types to create a conductive and flexible carbon supporting nanocomposite framework as an anode material for LIBs is regarded as one of the most beneficial techniques for improving stability, conductivity, and capacity. This review begins with a quick overview of LIB operations and performance measurement indexes. It then examines the recently reported synthesis methods of carbon-based nanostructured materials and the effects of their properties on high-performance anode materials for LIBs. These include composites made of 1D, 2D, and 3D nanocarbon structures and much higher Li storage-capacity nanostructured compounds (metals, transitional metal oxides, transition-metal sulfides, and other inorganic materials). The strategies employed to improve anode performance by leveraging the intrinsic features of individual constituents and their structural designs are examined. The review concludes with a summary and an outlook for future advancements in this research field.

25 ENERGY STORAGE↗
DOE OSTI2024

Porous Organic Cage Membranes for Molecular Gas Separations (Final Technical Report for DE-SC0021357)

This proposal aims at demonstrating the development of a novel family of membranes, composed of porous organic cages (POC) which offer the possibility of displaying high separation performance for challenging molecular gas separations relevant to natural gas purification, and olefin/paraffin separation. The proposed POCs synthesized in membrane form will display the most desirable properties of polymers (facile processability and flexibility) and inorganic materials (hierarchically ordered pores with molecular sieving properties) leading to highly selective and permeable membranes. POCs should display distinctive structural, compositional, adsorption and transport properties than those of conventional porous materials, opening the doors for a new research direction in membrane science, and gas separations. Our preliminary results demonstrate the feasibility of preparing POC crystals with controlled size, and continuous POC membranes with remarkable high permeances, and separation ability for CO 2 /CH 4 , N 2 /CH 4 and C 3 H 6 /C 3 H 8 separations serving as a solid foundation for our proposed work. Fundamentally, this proposal aims at elucidating separation mechanisms of different gas mixtures related to natural gas composition, and olefin/paraffin separation over porous organic cage membranes. The proposed research will result in fundamental understanding of adsorption and transport properties of industrially relevant gas molecules through novel microporous membranes, and may lead to the development of a cost effective membrane technology for natural gas purification, and olefin/paraffin separation surpassing the conventional benchmark technology distillation. Furthermore, we aim at demonstrating selective water transport through POC membranes, which can be positively impactful in numerous industrial applications in which water is present. The ability to fabricate thin, chemically and mechanically stable POC membranes for societal relevant gas separations constitute a new and distinctive direction in membrane science. Our proposed work aims at addressing some of the challenges recognized in the Research Agenda for Transforming Separation Science . Specifically: (a) advancing understanding of complex mixtures on separation performance; (b) exploring thermodynamic and kinetic mechanisms through the elucidation of separation mechanisms, and (c) study potential stability issues of the membranes to be assessed by evaluating the long term membrane stability and performance at various temperatures and pressures. The team is uniquely qualified to execute the proposed work. The PI has solid expertise in the rational molecular engineering design of porous crystalline membranes for molecular gas separations. The PNNL collaborator has extensive experience in the synthesis, characterization, and functional applications of microporous crystals, with particular emphasis on gas adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Juvenile Salmon and Their Habitats in the Columbia River Estuary: A Review and Synthesis of Knowledge Development 2000–2025

[This is a 90% discussion draft.] This is the third Synthesis Memorandum funded by the U.S. Army Corps of Engineers and developed for the Columbia Estuary Ecosystem Restoration Program (CEERP) on the topic of habitat restoration in the Columbia River Estuary (CRE) from Bonneville Dam to the river mouth. While the first two were developed by PNNL and NOAA without the benefit of stakeholder participation, for the current memo, two key activities were initiated: (1) review, by the Expert Regional Technical Group (ERTG), of status and trends monitoring and action effectiveness monitoring funded by CEERP, and (2) a workshop including representatives of the Bonneville Power Administration and the U.S. Army Corps of Engineers (the action agencies [AAs]), the National Oceanic and Atmospheric Administration (NOAA), major research agencies contributing to CEERP, and sponsors who implement CEERP restoration actions. A systematic literature review was conducted using ClarivateTM Web of ScienceTM database. The topics of interest for CRE relevant research included salmon ecology, physical processes, and wetland habitats, and therefore required the use of broad search terms. Our final search criteria included a combination of Boolean operators and an approach to combine different sets of search terms. The final search result yielded 669 records. The records were classified by groups and assigned to the relevant disciplinary expert for review. The review identified substantive advances in understanding the provision of salmon habitat functions through spatiotemporally dynamic physical and ecological processes, and the use of CRE habitats by numerous stocks of juvenile salmon. It also uncovered heretofore unincorporated historical documentation of riparian habitats across the CRE. The characterization of the structural components of floodplain habitat including plant associations and channel networks has advanced considerably, together with the understanding of seasonal changes and long-term trends. The relative influence of salmon-habitat location in the CRE as compared with temporal factors, mainly season, has been well described, which affects the prioritization of restoration. Stressors on the ecosystem and fish, and the drivers of these stressors, have been more carefully elucidated and predictive models are in various stages of development. The vision, aims, and design of restoration projects have advanced together with methods of data collection, analysis, and modeling that have seen substantial improvements. Experiments intended to inform the design of restoration projects are underway or have been completed. An important outstanding area of research that has lagged behind the advances in fundamental understanding of the ecosystem and salmon habitat functions remains the peer-reviewed documentation of the outcomes of restoration for both habitats and fish functions.

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