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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Fast Dynamic Internal Predictive Power Scheduling Approach for Power Management in Microgrids: Preprint

This paper presents a Dynamic Internal Predictive Power Scheduling (DIPPS) approach for optimizing power management in microgrids, particularly focusing on external power exchanges among diverse prosumers. DIPPS utilizes a dynamic objective function with a time-varying binary parameter to control the timing of power transfers to the external grid, facilitated by efficient usage of energy storage for surplus renewable power. The microgrid power scheduling problem is modeled as a mixed-integer nonlinear programming (MINLP-PS) and subsequently transformed into a mixed-integer linear programming (MILPPS) optimization through McCormick's relaxation to reduce computational complexity. A predictive window window with 6 data points is solved at an average of 0.92s, a 97.6% improvement over the 38.27s required for the MINLP-PS formulation, implying the numerical feasibility of the DIPPS approach for real-time implementation. Finally, the approach is validated against a static objective using real-world load data across three case studies with different time-varying parameters, demonstrating the ability of DIPPS to optimize power exchanges and efficiently utilize distributed resources while shifting the external power transfers to specified time durations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 2. Evaluating Controls on Flow Persistence in an Urbanized Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.

ATS↗
DOE OSTI2024

From sensing to acclimation: The role of membrane lipid remodeling in plant responses to low temperatures

Abstract Low temperatures pose a dramatic challenge to plant viability. Chilling and freezing disrupt cellular processes, forcing metabolic adaptations reflected in alterations to membrane compositions. Understanding the mechanisms of plant cold tolerance is increasingly important due to anticipated increases in the frequency, severity, and duration of cold events. This review synthesizes current knowledge on the adaptive changes of membrane glycerolipids, sphingolipids, and phytosterols in response to cold stress. We delve into key mechanisms of low-temperature membrane remodeling, including acyl editing and headgroup exchange, lipase activity, and phytosterol abundance changes, focusing on their impact at the subcellular level. Furthermore, we tabulate and analyze current gycerolipidomic data from cold treatments of Arabidopsis, maize, and sorghum. This analysis highlights congruencies of lipid abundance changes in response to varying degrees of cold stress. Ultimately, this review aids in rationalizing observed lipid fluctuations and pinpoints key gaps in our current capacity to fully understand how plants orchestrate these membrane responses to cold stress.

Plant Sciences↗
DOE OSTI2024

Abstract for CRADA between National Energy Technology Laboratory and Shell International Exploration & Production, Inc

Introducing CO₂ into geothermal systems as a working fluid in reservoirs can enhance geothermal conductivity, production, and pressure maintenance. A cross-disciplinary interaction of geothermal reservoir stimulation and CO₂ utilization satisfies renewable energy demands and operations that support sustainable energy infrastructure. Challenges to implementing CO₂-stimulated geothermal enhancement (CS-GE) include (1) accurately characterizing and imaging CO₂-stimulated geothermal reservoirs; (2) quantitatively inferring CS-GE evolution under current and future engineered conditions for cost effective operations; and (3) monitoring resources by improving observational methods to advance the understanding of complex geothermal systems for sweep efficiency and, ultimately, cost effectiveness. NETL and Shell will collaborate under this CRADA to develop software to image key features, including CO₂-stimulated fracture imaging, CO₂ fluid sweep imaging and heat transfer and exchange imaging by leveraging available datasets and applying advanced Artificial Intelligence/Machine Learning (AI/ML), multi-level data analytics and data/information fusion to better understand the comprehensive mechanisms of CO₂-stimulated geothermal systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Removal of Selenium Oxyanions from Aqueous Solutions by Ion Exchange: Equilibrium, Kinetics, and Mechanistic Modeling

Selenium (Se) is an essential micronutrient but toxic at high concentrations, posing challenges for water treatment. This study investigated the removal of selenate (SeO 4 2– ) and selenite (SeO 3 2– ) using the strong-base anion-exchange resin IRA-900, particularly in the presence of competing sulfate (SO 4 2– ). The performance of the commercially available resin IRA-900 was systematically investigated. The batch equilibrium behavior was studied in both single- and binary-component systems, and the kinetic behavior was investigated in single-component systems. Results confirmed a selectivity order of SeO 4 2– > SO 4 2– > SeO 3 2– , indicating preferential SeO 4 2– removal over competing SO 4 2– but lower affinity for SeO 3 2– . The maximum total exchange capacity was determined to be 2.04 mequiv/g. Furthermore, SeO 3 2– uptake was found to be pH-dependent, whereas SeO 4 2– uptake remained stable across a broad pH range. From a modeling perspective, the Law of Mass Action model effectively described equilibrium data, and a transport–reaction modeling framework captured removal kinetics of oxyanions including film and intraparticle diffusion. Finally, X-ray photoelectron spectroscopy confirmed ion exchange between chloride and Se oxyanions as the primary removal mechanism. These findings provide fundamental insights into the removal of Se oxyanions from aqueous solutions by ion exchange.

IRA-900↗
DOE OSTI2025

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spin wave theory for the triaxial magnetic anisotropy 2D van der Waals antiferromagnet CrSBr

The magnetic properties of two-dimensional (2D) materials have been attracting increasing attention in recent years due to their unique behavior and possible applications in new devices. One material of great interest is the 2D van der Waals (vdW) crystal CrSBr, which exhibits antiferromagnetic (AF) order at low temperatures due to an interlayer AF exchange interaction. Here, we present a full quantum spin-wave theory for vdW crystals considering one interlayer and three intralayer exchange interactions, and triaxial magnetic anisotropy. The fits of the theoretical results to antiferromagnetic resonance measurements and inelastic neutron scattering data in CrSBr yield reliable values for the seven interaction parameters that can be used to calculate other properties of this interesting material.

2D materials↗
DOE OSTI2025

Measurements of Gamow-Teller transitions from 59 Co via the 59 Co ⁢(𝑡, 3 He +𝛾) charge-exchange reaction and its application to the stellar electron-capture rates

Electron-capture reactions on iron-group nuclei play a crucial role in the late stages of massive star evolution. Since stellar evolution simulations depend on accurate electron-capture rates—which are highly sensitive to the detailed Gamow-Teller (GT) strength distributions—reliable theoretical models are essential. However, experimental data on GT strength distributions are scarce. High-resolution measurements are therefore vital for benchmarking and improving these theoretical calculations. To provide high-resolution data on Gamow-Teller strength distributions of iron-group nuclei and to compare these results with theoretical calculations within this mass region. Differential cross sections for the 59 Co ⁢(𝑡, 3 He)⁢ 59 Fe charge-exchange reaction at 115 MeV/u were measured using the S800 spectrometer. Furthermore, to resolve individual levels that are not distinguishable in the S800 particle singles data, coincident 𝛾 rays from the 59 Fe residual nucleus were detected by using the Gamma-Ray Energy Tracking In-beam Nuclear Array 𝛾-ray tracking array. Here, the Gamow-Teller transition strength distribution from the ground state of 59 Co to 59 Fe was extracted up to an excitation energy of 10 MeV. Additionally, transition strengths for several low-lying states were determined from coincident 𝛾-ray measurements. Electron-capture rates calculated using the present data indicate that these low-lying states contribute significantly to the overall rates in relevant stellar environments. The experimental results show reasonable agreement with theoretical predictions based on both shell-model and projected shell-model calculations. High-resolution data on Gamow-Teller strength distributions—particularly for individual low-lying states—are essential for accurately determining electron-capture rates in iron-group nuclei. Coincident 𝛾-ray measurements provide a powerful tool for obtaining such detailed information. While the present work demonstrates that shell-model calculations successfully reproduce the experimental results, such comparisons are scarce and more experimental data are desirable.

59 ≤ A ≤ 89↗
DOE OSTI2024

Two-Fluid and Discrete Element Modeling of a Parallel Plate Fluidized Bed Heat Exchanger for Concentrating Solar Power

A novel high-temperature particle solar receiver is developed using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a fluidized bed at the lower section, leaving the system from the bottom at a constant flowrate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built by collaborators at the Colorado School of Mines and their data are used for model validation. In this experimental setup, near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using the discrete element method and a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A new continuum conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2 K.

concentrating solar power↗
DOE OSTI2026

Geomechanical properties of the Meletta sandstone - the high-temperature heat storage reservoir rock of DeepStor

The DeepStor project aims at storing excess heat at temperatures up to 140 °C in the depleted Leopoldshafen oil field at a depth of about 1300 m. In order to gain knowledge on the target horizons, the different layers of the Meletta sandstone, samples cored in a block retrieved in a quarry near Nussloch where the Meletta sandstone outcrops were studied. Several petrophysical properties were investigated including mineralogy, porosity, permeability, thermal conductivity, P- and S-wave velocities and quality factor. A mechanical study focused on compressive strength under uniaxial and triaxial stress conditions, tensile strength, critical pressure and stress-dependence of physical properties. Our results show that the Meletta sandstone is heterogeneous, anisotropic, mechanically weak, stress-sensitive and prone to water weakening. Petrophysical measurements on few Meletta sandstone cores retrieved in boreholes at about 1250 m depth showed that the outcrop samples are significantly less cohesive and weaker. Therefore, one should consider the Nussloch outcrop as a good reservoir analog only with great caution. Several models were applied to account for our experimental results on anisotropy, mechanical behavior and stress-dependence of the outcrop samples. Our study provides a valuable data set which can feed numerical models to simulate the behavior of the host formation during heat exchange operations in the DeepStor project.

Geomechanics↗
DOE OSTI2026

Frustration-driven magnetic correlations in the spin-$\frac{5}{2}$ triangular lattice antiferromagnet RbFe⁢(HPO 3 ) 2

Here, a detailed study of the structural and magnetic properties of a spin-5/2 triangular lattice antiferromagnet RbFe⁢(HPO 3 ) 2 is presented using x-ray diffraction, magnetization, heat capacity, and 31 P nuclear magnetic resonance (NMR) experiments on a polycrystalline sample. The crystal structure features an equilateral triangular lattice of Fe 3+ ions. The thermodynamic measurements reveal the onset of a magnetic long-range order at 𝑇 N⁢1 ≃7.8K in zero field, followed by another low-temperature field-induced ordering at 𝑇 N⁢2 in higher fields. The transition at 𝑇 N⁢1 is further confirmed from the NMR spin lattice relaxation measurements. The value of the frustration ratio (𝑓≃7) implies moderate spin frustration in the compound. The 31 P NMR spectra exhibit two distinct spectral lines corresponding to two inequivalent phosphorus sites (P1 and P2), consistent with the crystal structure. The P1 site is strongly coupled with an isotropic hyperfine coupling of 𝐴$^{iso}_{hf}$ = 0.55⁢(2)⁢ T/𝜇 B while the P2 site is weakly coupled with 𝐴$^{iso}_{hf}$ = 0.25⁢(3)⁢ T/𝜇 B with the Fe 3+ ions. The magnetic susceptibility and NMR shift data are described well assuming a spin-5/2 isotropic triangular lattice antiferromagnetic model with an average exchange coupling of 𝐽/𝑘 B = 2.8⁢(2)⁢K. Below 𝑇 N⁢1 , the spectra evolve into a nearly rectangular powder pattern, indicating a commensurate antiferromagnetic type order. The 31 P spin-lattice relaxation rate well below 𝑇N⁢1 follows a 𝑇 3 temperature dependence, implying a two-magnon Raman scattering mechanism in the ordered state. Three well-defined phase regimes are clearly ascertained in the 𝐻−𝑇 phase diagram, reflecting a weak magnetic anisotropy in the compound.

Nagpal, V. [Indian Institute of Science Education ↗
DOE OSTI2025

Spin dynamics in the itinerant antiferromagnet SrCr 2 ⁢As 2

SrCr 2 ⁢As 2 is an itinerant antiferromagnet in the same structural family as the SrFe 2 ⁢As 2 high-temperature superconductors. Here, we report our calculations of exchange-coupling parameters 𝐽 𝑖⁢𝑗 for SrCr 2 ⁢As 2 using a static linear-response method based on first-principles electronic-structure calculations. We find that the dominant nearest-neighbor exchange coupling 𝐽 1 >0 is antiferromagnetic whereas the next-nearest-neighbor exchange coupling 𝐽 2 <0 is ferromagnetic with 𝐽 2 /𝐽 1 = −0.68, reinforcing the checkerboard in-plane magnetic structure. Thus, unlike other transition-metal arsenides based on Mn, Fe, or Co, we find no competing magnetic interactions in SrCr 2 ⁢As 2 , which aligns with experimental findings. Moreover, the orbital resolution of exchange interactions shows that 𝐽 1 and 𝐽 2 are dominated by direct exchange mediated by the Cr 𝑑 orbitals. To validate the calculations we conduct inelastic neutron-scattering measurements on powder samples that show steeply dispersive magnetic excitations arising from the magnetic Γ points and persisting up to energies of at least 175 meV. The spin-wave spectra are then modeled using the Heisenberg Hamiltonian with the theoretically calculated exchange couplings. In conclusion, the calculated neutron-scattering spectra are in good agreement with the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Decision and Control of Complex Systems – A Data-Drive Framework

During the project period, we have collaborated with other team members and developed novel algorithms for novelty detection, continual learning, and graph learning algorithms for dynamic systems. The results are documented in publications and meeting notes. Moreover, we leverage virtual collaboration tools (such as Basecamp, Microsoft Teams and Zoom) for technical exchanges. Our research on novelty detection was published at AAAI 2022 and Lecture Notes in Artificial Intelligence, Springer Nature. The newly developed algorithms were successfully applied to realistic cases, including thermal data from buildings at Pacific Northwest National Lab and microelectronic data provided by GlobalFoundries. Multiple publications have been produced from this project, in collaboration with other team members. Three PhD students were supported in this project to conduct their research.

42 ENGINEERING↗
DOE OSTI2026

2022 Bull E-Bike Pilot Program Study

In 2022, the City of Durham conducted an e-bike pilot program study to learn more about how electric bikes (e-bikes) could improve the transportation experience in the "Bull City" (a.k.a., Durham, North Carolina). The study used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The City of Durham's Transportation Department conducted the study. #### Survey Methodology Program participants used electric-assist e-bikes for at least 4 weeks between August and November 2022 in exchange for sharing information about their experiences, including tracking their travel via a smartphone app. In addition to the e-bike, participants received maintenance support along with a helmet, bike lock, and other accessories. Data collection was enabled by the [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include a total of 76 participants. The dataset contains 3 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from participants. The number of total trips was 6,488, the number of e-bike trips was 2,183, and the number of e-bike miles traveled was 5,450.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
DOE OSTI2024

Heterogeneous Cluster Energetics and Nonlinear Thermodynamic Response in Supercritical Fluids

Microstructural heterogeneities arising from molecular clusters directly affect the nonlinear thermodynamic properties of supercritical fluids. We present a physical model to elucidate the relation between energy exchange and heterogeneous cluster dynamics during the transition from liquidlike to gaslike conditions. By analyzing molecular-dynamics data and employing physical principles, the model considers contributions from three key processes, namely, changing cluster density, cluster separation, and transfer of molecules between clusters. We show that the proposed model is consistent with the energetics at subcritical conditions and can be used to explain the nonlinear behavior of thermodynamic response functions, including the peak in the isobaric heat capacity.

42 ENGINEERING↗
DOE OSTI2024

Vegetation Warming Experiment: Leaf mass area, leaf carbon and nitrogen content, Utqiagvik, Alaska, 2021-2022

Leaf mass per area (LMA), and leaf carbon and nitrogen content of an Arctic graminoid, Carex aquatilis, from within warming chambers and paired control plots. The plants were sampled in July 2021 and July 2022 as part of the Zero Power Warming (ZPW) vegetation warming experiment conducted on the Barrow Environmental Observatory (BEO), Utqiagvik (formerly Barrow), Alaska. Samples include leaves used for gas exchange measurements and bulk harvests from each warming chamber and paired ambient plot. The files included in this data package are in .csv format, and include 3 data files and 4 metadata files. See related datasets for plant physiology, phenology, thaw depth and environmental conditions of the plots and warming chambers. 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↗