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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗
DOE OSTI2024

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of ~4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics. Similar content being viewed by others

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ab initio thermodynamics reveals the nanocomposite structure of ferrihydrite

Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.

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

Past and future ocean warming

Changes in ocean heat content (OHC) provide a measure of ocean warming, with impacts on the Earth system. This Review synthesizes estimates of past and future OHC changes using observations and models. The top 2,000 m of the global ocean has significantly warmed since the 1950s, gaining 351 ± 59.8 ZJ (1 ZJ = 10 21 J) from 1958 to 2019. The rate of warming increased from <5 to ~10 ZJ yr –1 from the 1960s to the 2010s. Observed area-averaged warming is largest in the Atlantic Ocean and southern oceans at 1.42 ± 0.09 and 1.40 ± 0.09 × 109 J m –2 , respectively, for the upper 2,000 m over 1958–2019. These observed patterns of heat gains are dominated by heat redistribution. Observationally constrained projections suggest that historic ocean warming is irreversible this century, with net warming dependent on the emission scenario. By 2100, projected warming in the top 2,000 m is 2–6 times that observed so far, ranging from 1,030 [839–1,228] ZJ for a low-emission scenario to 1,874 [1,637–2,109] ZJ for a high-emission scenario. The Pacific is projected to be the largest heat reservoir owing to its size, but area-averaged warming remains strongest in the Atlantic and southern oceans. Ocean warming has extensive impacts that pose risks to marine ecosystems and society. Here, the projected changes necessitate a continuation and improvement of observations and models, along with better uncertainty estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Regression Analysis with the Directed Infusion of Data

Integrating artificial intelligence and machine learning tools into industry necessitates large-scale collaborative efforts that ensure the robust and accurate execution of downstream analytics such as time series prediction, uncertainty quantification, grid optimization, and condition monitoring. However, concerns related to data privacy pervade the nuclear industry due to the proprietary nature of its data and the possibility of data leakage. Legacy techniques such as encryption often require the explicit transmission of data to trustworthy parties, thereby inviting data leakage concerns. The ideal collaboration scenario avoids the explicit dissemination of data/code while maintaining experimental fidelity, which is currently accomplished using various techniques such as trusted execution environments, homomorphic encryption, differential privacy, and multimatrix masking. These techniques, however, often necessitate a trade-off between trust, efficiency, and utility. This article extends a previously proposed technique called the directed infusion of data (DIOD) that ensures data privacy, allows for scalable obfuscation, and combats the risk of data leakage without compromising utility. The experiments discussed in this article examine a regression-type scenario using DIOD with the goal of preserving the inferential link between two variables. Using the point-kinetics equations, regression experiments compare the performance of a model trained using the original data to that of a model trained using the obfuscated data, which produced identical results. Our claim is further strengthened by an information theoretic proof and experiment, which showed that the inferential content between variables remains the same after obfuscation, thereby avoiding the required communication of the proprietary data.

47 - OTHER INSTRUMENTATION↗
DOE OSTI2022

2022 Accomplishments Report Template

Chromium-doped UO 2 fuels is an industrially important Accident Tolerant Fuel (ATF) due to the ability to increase the average grain size relative to standard UO 2 . However, there is a lack of knowledge of the thermophysical properties of these doped fuels, which is necessary for accurately modeling the in-pile performance. The work accomplished this FY focused on developing large grain Cr-doped UO 2 pellets as a function of Cr content and subsequently measuring the thermophysical and mechanical properties. The microstructural variations were also investigated to evaluate chromium formation within the microstructure of the sintered pellets.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Integrated Biorefinery of Brewer’s Spent Grain for Second-Generation Ethanol, Mycoprotein, and Bioactive Vinasse Production

Brewer’s spent grain (BSG), the main lignocellulosic by-product of the beer industry, represents an abundant yet underutilized resource with high potential for valorization. This study presents an integrated biorefinery approach to convert BSG into second-generation (2G) ethanol, bioactive vinasse for plant growth promotion, and fungal biomass as a potential mycoprotein source. The biomass was first subjected to biological delignification using the white-rot fungus Ganoderma lucidum, after which two valorization routes were explored: (i) evaluation of the fungal biomass as a mycoprotein candidate and (ii) alcoholic fermentation for ethanol production. For the latter, three pretreatment strategies were assessed (diluted sulfuric acid and two deep eutectic solvents (DESs) based on choline chloride combined with either glycerol or lactic acid) followed by a one-pot enzymatic saccharification and fermentation using Kluyveromyces marxianus SLP1. The highest ethanol yield on substrate (YP/S) was achieved with [Ch]Cl:lactic acid pretreatment (0.46 g/g, 89.32% of theoretical). Vinasse, recovered after distillation, was characterized for organic acid content and tested on Solanum lycopersicum seed germination, showing promising biostimulant activity. Overall, this work highlights the potential of BSG as a sustainable feedstock within circular economy models, enabling the production of multiple bio-based products from a single residue.

Ganoderma lucidum↗
DOE OSTI2023

Reduced viscosity steadily weakens oceanic currents

The viscosity of both air and water is temperature dependent. A rising temperature leads to an increased viscosity for air but a decreased viscosity for water. As climate becomes warmer, this increased air viscosity can partly inhibit the reduction of wind stress over the ocean, and the reduced water viscosity causes less downward momentum and heat transport. As these opposing effects of warming on air and water viscosity are not included in the state-of-the-art climate models, the understanding of their potential impacts on the response of the climate system to the anthropogenic warming is lacking. Here, via analyzing the Simple Ocean Data Assimilation oceanic reanalysis dataset, we show that the ocean heat content increases at a rate of ~1.3 × 10 22 J/yr over 35 years, which leads to a continuous reduction of oceanic viscosity. As a result, the ocean vertical shear enhances with a shoaling of the mixed layer depth and a reduced vertical linkage in the ocean. Our calculations show a reduction of the oceanic kinetic energy at a rate of ~2.4 × 10 16 J/yr. Potentially, this could generate far-reaching impacts on the energy storage of the climate system and, hence, could pace the global warming. Thus, it is important to include the temperature-dependent viscosity in our climate models. Freshwater discharged from polar ice sheets and mountain glaciers also contributes to the reduction in oceanic viscosity but, at present, to a lesser extent than that in oceanic warming. Reduced oceanic viscosity, therefore, is an important, but hitherto overlooked, response to a warming climate and contributes to many recent weather extremes including heavier rainfall rates in hurricanes, slackening of the polar vortex, and oceanic heat waves.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Solubility Predictions for Hanford Tank Concentrates with HSC - 20459

The commercially available Outotec HSC 9.9.0{sup R} provides excellent predictions for the solubilities of many species for Hanford waste tank concentrates. The HSC solubility predictions with a Harvie activity model agreed well with five boildowns that showed solubility limits for NaNO{sub 3}, NaNO{sub 2}, Na{sub 2}CO{sub 3}, NaF, Na{sub 2}SO{sub 4}, and Na{sub 3}PO{sub 4}. However, the HSC did not predict density and therefore water content very well and therefore we used the measured densities and derived water content from the difference between measured density and assays. Furthermore, we adjusted the HSC enthalpy for the minor species Na{sub 3}PO{sub 4}*NaF double salt in order to fit the five boildowns as well. Previous work has shown that gibbsite becomes and remains supersaturated in all of these boildowns and so there was no alumina precipitation despite supersaturation. Furthermore, an equilibrium model like HSC always shows complete oxidation of any TOC in the presence of nitrate and nitrite. We therefore suppressed the HSC oxidation of acetate and oxalate in order to fit measured acetate and oxalate solubilities as TOC. Space in Hanford waste tanks is very limited and therefore evaporator campaigns continue to recover needed tank space from dilute tank liquids. Prior to each evaporator campaign, a boildown of a sample of tank liquid for each campaign provides a basis for planning by measuring density, water activity, soluble species, and solids precipitation as a function of concentration at 18 deg. C. These boildowns then provide validations and calibrations for the HSC solubility prediction for Hanford wastes. Previous work has shown the solubilities of minor electrolytes in these five boildowns follow rather simple power law solubility products. Hanford's 222-S laboratory has reported each of five boildowns for concentrated liquids from five waste tanks and tank blends. All boildowns eventually showed the precipitation of the dominant electrolyte, NaNO{sub 3}, and overall solution activity largely drives all solubility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Investigating the Effect of Water on the Mechanical Properties of Cellulose from Multiscale Molecular Dynamics Simulations

Classical molecular dynamics (MD) simulations provide insight into the structure and physicochemical properties of materials with atomic resolution. However, the length and time scales accessible to atomistic MD are orders of magnitude smaller than many relevant processes such as the response of a bulk material to experimentally accessible strain rates, which presents challenges when comparing models to experimental measurements. Bottom-up coarse-graining provides a means for systematically mapping atomistic information to lower resolution models to increase the length and time scales achievable by simulation. Cellulose is an abundant carbohydrate biopolymer with applications to many fields of research, such as materials science and renewable energy, due to its desirable mechanical properties and viability for conversion into biofuel. The effect of moisture content on the Young's modulus of cellulose is of special interest due to its native environment often being in the hydrated secondary plant cell wall and the grinding energy requirements for biomass feedstock preprocessing. The current work investigates the effects of water solvent on the Young's modulus of cellulose calculated from coarse-grained MD mechanical stress simulations. The coarse-grained model was parametrized from atomistic MD calculations of cellulose-cellulose potentials of mean force using umbrella sampling techniques under vacuum and solvated conditions. The Young's moduli of the coarse-grained cellulose assemblies parametrized from cellulose in vacuum or solvated in water were computed via mechanical stress simulations to highlight the importance of capturing solvent interactions for modeling the mechanical behavior of cellulose.

BASIC BIOLOGICAL SCIENCES,RADIATION PROTECTION AND↗
DOE OSTI2020

Growth of Jupiter: Formation in disks of gas and solids and evolution to the present epoch

The formation of Jupiter is modeled via core-nucleated accretion, and the planet's evolution is simulated up to the present epoch. Throughout the phases when the planet acquires most of its heavy-element content, the calculation of solids' accretion accounts for interactions with an evolving disk of planetesimals. The phase of growth from an embryo of a few hundred kilometers in radius until the time when the accretion of gas overtakes solids' accretion was presented by D'Angelo et al., and the same numerical methods are applied here. Those calculations followed the formation for about 4 × 10 5 years, until the epoch when the heavy-element and hydrogen/helium masses were $M_Z ≈ 7.3$ and $M_{XY} ≈ 0.15$ Earth's masses ($M_⊕$), respectively, and $\dot {M} _{XY} ≈ $$\dot {M}_Z$. In this work, the calculation is continued through the phase when $M_{XY}$ grows to equal $M_Z$ , at which age, about 2.4 × 10 6 years, the total mass of the planet is $M_p ≈ 20 M_⊕$. About 9 × 10 5 years later, $M_p$ is approximately $60 M_⊕$ and $M_Z ≈ 16 M_⊕$, three-quarters of which are delivered by planetesimals larger than 10 km in radius. Around this epoch, the contraction of the envelope dictates gas accretion rates a few times 10 –3 $M_⊕$ per year, initiating the regime of disk-limited accretion, whereby the planet can accrete all the gas provided by the disk, and its evolution is therefore tied to disk's evolution. Growth is continued by constructing simplified models of protosolar accretion disks that evolve through viscous diffusion, winds, and accretion on the planet. Jupiter's formation ends after ≈ 3.4–4.2 Myr, depending on the applied disk viscosity parameter, when nebula gas disperses. The young Jupiter is 4.5–5.5 times as voluminous as it is presently and thousands of times as luminous, ~10 –5 $L_⊙$. The heavy-element mass is ≈ 20 $M_⊕$. The evolution proceeds through the cooling and contraction phase, in isolation except for solar irradiation. After 4570 Myr, the age of the solar system, radius and luminosity of the planet are within 10$\%$ of current values, accounting also for uncertainties in the power absorbed from the Sun. During formation, and soon thereafter, the planet exhibits features, e.g., luminosity and effective temperature, that may probe aspects of the latter stages of formation, if observable. These possibly distinctive features, however, seem to disappear within a few tens of Myr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Testing and Modeling of Functionally Graded Aluminum-Doped Zinc Oxide Using Spark Plasma Sintering and Discrete Powder Layers of Varying Composition

Functionally graded material (FGM) ZnO is made via spark plasma sintering/field-assisted sintering technique (SPS/FAST) by varying the Al dopant content along the z-axis or pressing direction. A wide range of Al content (0–5 wt%) is used by adding Al powder to nanosized ZnO powder. Thermoelectric (TE) measurements are done on the FGM and individual layers made separately. X-ray diffraction (XRD) shows two phases, ZnO and spinel phase (ZnAl 2 O 4 ). High-resolution Raman spectroscopy reveals doped ZnO and spinel phase (ZnAl 2 O 4 ) spatially and shows segregation in the layer with highest Al content. Electron backscatter diffraction (EBSD) reveals noticeable grain growth with decreasing Al content, and there is a common, random preferred orientation in all layers. The tested properties are used to simulate efficiency curves for a discretely graded, five-layer FGM as well as a homogenous material, where both graded structures provide an opportunity to widen the current density ranges and therefore the temperature range of useful energy conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗
DOE OSTI2024

Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment - supporting data and code

This data package contains data, descriptions, and code-based analyses that were used to support conclusions drawn in “Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment”, by Freitas et al. (2025) (https://doi.org/10.1038/s41561-024-01614-y). The study evaluated greenhouse gas production along a deep sediment core (20 m) taken in 2018 from below Goldstream Lake, a field site approximately 15 km north of Fairbanks, Alaska.The file “ESSDive_NFreitas_2024_flmd.csv” includes an overview of all other csv files in this data package, namely: sediment descriptions (depth and type of sediment), sediment characterizations (bulk density, gravimetric water content, total carbon, etc.), calculated respiration and temperature sensitivity values associated with year-long incubations of the sediment core, and the R code used to process the dataset. Additional details regarding the content of these files and how the calculations were performed are described in the Methods section of this archive. The “data_dictionary_ESSDive_NFreitas_2024_dd.csv” is a data dictionary for all files included in the data package. Each row in the data dictionary represents a column name in a given file. 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).Data package updates- August 2024: Title was updated, R code now includes a process for calculating potential production across the whole sediment column, the "sediment_column_production_potentials_ESSDive_NFreitas_2024.csv" is the associated data output file, and the file level metadata and data dictionaries were updated to reflect the contents of the additional csv file.- October 2024: Title was updated, and a statement was added to Step 2 of the Methods that describes that samples were collected (and exported) in a responsible manner and in accordance with relevant permits and local laws.- January 2025: Updated the associated manuscript details in the Abstract (manuscript title, publication date, DOI link) and in the Related References section (full citation).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

General Relativistic Stability and Gravitational Wave Content of Rotating Triaxial Neutron Stars

Triaxial neutron stars can be sources of continuous gravitational radiation detectable by ground-based interferometers. The amplitude of the emitted gravitational wave can be greatly affected by the state of the hydrodynamical fluid flow inside the neutron star. In this work, we examine the most triaxial models along two sequences of constant rest mass, confirming their dynamical stability. We also study the response of a triaxial figure of quasiequilibrium under a variety of perturbations that lead to different fluid flows. Starting from the general relativistic compressible analog of the Newtonian Jacobi ellipsoid, we perform simulations of Dedekind-type flows. We find that in some cases the triaxial neutron star resembles a Riemann-S-type ellipsoid with minor rotation and gravitational wave emission as it evolves towards axisymmetry. The present results highlight the importance of understanding the fluid flow in the interior of a neutron star in terms of its gravitational wave content.

Luo, Yufeng (ORCID:0000000246230683)↗
DOE OSTI2022

Interfacial Water Manipulation with Ionic Liquids for the Oxygen Reduction Reaction

The role that interfacial water plays in both promoting and inhibiting the electrochemical oxygen reduction reaction (ORR) remains somewhat unclear and controversial. Here, we use electroanalytical chemistry, spectroscopy, and microkinetic modeling to probe the impact of hydrophobic ionic liquid (IL) thin films on interfacial water structure and its role in promoting or inhibiting the ORR. Through the use of in situ ATR-SEIRAS, we find that the IL thin films limit the content of water at the interface and prevent the formation of hydrogen bond stabilized water organization. The impact of this exclusion of water on the promotion of the ORR is through the reduced coverage of OH ad spectator species. The decreased solvation of “active” OH ad species weakens its interaction with the catalyst surface, lowering the barrier to the last step in the ORR mechanism. This “destabilized” OH ad impact on ORR kinetics is confirmed through a microkinetic model. Furthermore, the results presented here highlight the mechanistic pathway through which hydrophobic ILs enhance ORR kinetics and point to pathways to both further improve this performance enhancement and the potential for integration of hydrophobic ILs into other technologically relevant elementary electrochemical reactions.

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

Shrub Expansion Simulations at Trail Valley Creek Tundra site using E3SM Land Model (ELM) Arctic-focused Version

The warming of the Arctic is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and densification in parts of the Arctic. Assessing the impact of these changes in vegetation composition on the Arctic’s carbon and energy budgets is important to constrain projected local and global surface-atmosphere exchanges. We conduct a sensitivity analysis of the projected surface energy fluxes, soil carbon pools, and carbon dioxide fluxes (net ecosystem exchange, gross primary production, and ecosystem respiration) between present day and 2100 to different shrub expansion rates and air temperature increases under future emission scenarios (intermediate – RCP4.5, and high – RCP8.5) using the Arctic-focused version of the Energy Exascale Earth System Model (E3SM) Land Model (ELM). We focus on Trail Valley Creek (TVC), a mineral upland tundra site located in the western Canadian Arctic, which is experiencing tall shrub densification and expansion. In this study, we run TVC under two different warming scenarios RCP4.5 and RCP 8.5 and simulate different shrubification rates projected until year 2100. In this repository, we include all the forcing, input, parameters, and output data corresponding to all the simulations performed. flmd.csv includes a detailed description of the datasets files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw: Modeling Archive

This Modeling Archive is in support of a NGEE Arctic publication in review "Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw". The study used a cryohydrology model to assess the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. The spatially resolved simulations are for a small catchment 465 ice-wedge polygons in polygonal tundra near Utqiagvik, Alaska in the high-emissions RCP8.5 climate scenario. The simulations are compared to runoff, evapotranspiration and subsidence in the current climate and agree well. The study used the ATS code configured as an intermediate-scale cryohydrology model (Advanced Terrestrial Simulator, Version v2). The archive includes input files for spinup (1985 to 2005) and projections (2006 to 2100 - the manuscript reports 2006 to 2098). Three of the projections include the effects of subsidence and microtopography change with different depth profiles of ice content corresponding to the median, 20th percentile and 80th percentile. The fourth projection has subsidence turnoff and uses the reference case (median) ice content. Spatially averaged or aggregated output variables are included for the projections. Selected checkpoint files for the projections and postprocessing scripts are also included. Files included are *.xml; *.h5; *.exo; *.py; *.sh, *. nb, mesh files, and one file in the original Excel format plus *.csv and *.pdf to conserve formatting contained in the original file. 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↗