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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗
DOE OSTI2022

Effects of Vegetation on Fluxes of Nitric Oxide, Nitrogen Dioxide, and Nitrous Oxide in a Mixed Deciduous Forest Clearing

Atmosphere-terrestrial exchange of nitrogen oxides, such as nitric oxide (NO), nitrogen dioxide (NO2) and nitrous oxide (N2O), plays an important role in controlling atmospheric composition and the radiative forcing of Earth’s atmosphere. In this study, the impact of vegetation ground cover on NOx (NOx = NO + NO2) and N2O fluxes in a deciduous forest clearing was studied using dynamic flow chambers located on three experimental plots with differing vegetation ground cover. Microbial emissions of NO and N2O were observed throughout the measurement period, while NO2 was exclusively deposited. Vegetation had no observable impact on NO2 deposition. Under dry conditions, total measured nitrogen emissions were numerically similar across all plots, although the N2O:NO ratio was higher for plots containing plants. Vegetation elevates soil water content through enhanced water retention, a condition that favors denitrification and more N2O production, relative to NO. Two rain events induced pulses of NO and N2O that were higher for bare soil compared to the vegetated plots. Lower NO and N2O emissions in plant-containing chambers stemmed from enhanced root uptake of N following rewetting, which diminished the amount of N substrate available for microbial NO and N2O production. The sensitivity of soil N emissions to vegetation ground cover highlights the need for more studies that investigate this effect over a wide range of ecosystems and to include vegetation effects in future parameterizations of soil NOx and N2O used in atmospheric models. This dataset includes processed data collected from 4 dynamic flux chambers and 17 sensors. Data includes ambient gas measurements made 1 m from the surface and soil flux measurements of NO, NO2, N2O, ozone (O3) and carbon dioxide (CO2). Also included is a suite of meteorological (air temperature, humidity, pressure) and soil parameters (water filled pore space, soil temperature). Refer to the readme for more information about each of the data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microbial Curing of Cement for Energy Applications

Rutgers University, Lawrence Livermore National Laboratory, and the University of Arizona executed this program over 36 months with a 4-Task Program: (M1)-Microbial Engineering (M2)-Microstructure Modelling, (M3) Cement and Concrete Formulation, (M4)-Techno-economic analysis (TEA) and lifecycle assessment (LCA). This program developed a new carbonate cement concrete manufacturing process called microbial curing (MBC). MBC utilizes in-situ microbial production of CO 2 that dissolves into pore-bound water to carbonate a cementitious material creating a bonding matrix of CaCO 3 and SiO 2 that hardens and densifies the material. This is the first work of this type where calcium silicate was used in microbial studies. All other work reported in the literature always used a soluble form of calcium. This final report describes the work done in the final quarter, the best procedures and results, and the final techno-economic and lifecycle analyses. This quarter, we cast and cured twenty-five (4”x8”) cylinder samples. The compressive strength, split tensile, Young’s modulus, chloride permeability, and creep measurements were performed. These measurements demonstrated that MBC of calcium silicate concrete exhibits scaling problems due to the escape of ammonia gas, a product of the microbial reaction to generate CO 2 . As curing proceeds, the ability for the gas to escape from within the cylinder is restricted by the outer cylindrical portions densifying, making the outer portion highly impermeable to gas flow. In contrast, the small samples cured are uniformly cured, forming materials whose mechanical properties are 7x better than the large samples. This problem needs to be solved before this technology can be commercialized. The techno-economic and lifecycle analyses indicate that the technology developed in this program exhibits a significant opportunity to reduce the cost of cement and CO 2 emissions associated with concrete, provided the curing issue associated with larger samples can be addressed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data from: Quantifying and correcting for pre-assay CO2 loss in short-term carbon mineralization assays

The active fraction of soil organic carbon is an important component of soil health and often is quickly assessed as the pulse of CO2 released by re-wetting dried soils in short-term (24–72 h) assays. However, soils can lose carbon (C) as they dry and, if soil samples vary in moisture content at sampling, differential C loss during the pre-assay dry-down period may complicate the assay's interpretations. We examined the impact of pre-assay CO2 loss in a long-cultivated agricultural soil at initial moisture contents of 30 %, 50 %, and 70 % water-filled pore space (WFPS). We found that 50 % and 70 % WFPS treatments lost more C during drying than did those in the 30 % WFPS treatment and that dry-down losses led to a 26 %–32 % underestimate of their CO2 pulses. We developed a soil-specific correction factor to account for these initial soil moisture effects. Future C mineralization studies may benefit from similar corrections.

Belanger, Matthew↗
DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗
DOE OSTI2021

Quantifying and correcting for pre-assay CO 2 loss in short-term carbon mineralization assays

The active fraction of soil organic carbon is an important component of soil health and often is quickly assessed as the pulse of CO 2 released by re-wetting dried soils in short-term (24–72 h) assays. However, soils can lose carbon (C) as they dry and, if soil samples vary in moisture content at sampling, differential C loss during the pre-assay dry-down period may complicate the assay's interpretations. We examined the impact of pre-assay CO 2 loss in a long-cultivated agricultural soil at initial moisture contents of 30 %, 50 %, and 70 % water-filled pore space (WFPS). We found that 50 % and 70 % WFPS treatments lost more C during drying than did those in the 30 % WFPS treatment and that dry-down losses led to a 26 %–32 % underestimate of their CO 2 pulses. We developed a soil-specific correction factor to account for these initial soil moisture effects. Future C mineralization studies may benefit from similar corrections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗
DOE OSTI2021

Data for: Spatial access and resource limitations control carbon mineralization in soils

This dataset contains data and code used for the paper "Spatial access and resource limitations control carbon mineralization in soils", https://doi.org/10.1016/j.soilbio.2021.108427. Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale water-soluble soil organic matter (SOM) mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble carbon (acetate) and nitrogen (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Soil respiration was measured during the incubation, after which pore water was extracted from the saturated soils and analyzed for water soluble organic carbon concentrations and characterization. Our results showed that carbon (C) amendments increased the cumulative carbon dioxide (CO2) evolved from the soil cores, suggesting that the soils were C-limited. Drought and rewetting increased soil respiration, and there was a greater abundance of complex aromatic molecules in pore waters sampled from these soils. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We had hypothesized that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (pore water samples), drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules, suggesting that fresh inputs stimulated the C-and N-limited microbial populations present deeper in the soil profile. Our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_spatial_access_2021 (DOI: 10.5281/zenodo.5522938).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Energetics of water expulsion from intervening space between two particles during aggregation

Solvent expulsion away from an intervening region between two approaching particles plays important roles in particle aggregation yet remains poorly understood. Here, in this work, we use metadynamics molecular simulations to study the free energy landscape of removing water molecules from gibbsite and pyrophyllite slit pores representing the confined spaces between two approaching particles. For gibbsite, removing water from the intervening region is both entropically and enthalpically unfavorable. The closer the particles approach each other, the harder it is to expel water molecules. For pyrophyllite, water expulsion is spontaneous, which is different from the gibbsite system. A smaller pore makes the water removal more favorable. When water is being drained from the intervening region, single chains of water molecules are observed in gibbsite pore, while in pyrophyllite pore water cluster is usually observed. Water-gibbsite hydrogen bonds help stabilize water chains, while water forms clusters in pyrophyllite pore to maximize the number of hydrogen bonds among themselves. This work provides the first assessment into the energetics and structure of water being drained from the intervening region between two approaching particles during oriented attachment and aggregation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evolution of water structures in metal-organic frameworks for improved atmospheric water harvesting

Designing water uptake Although the locations of water molecules in some porous materials have been determined with diffraction techniques, determining the filling sequence of water sites has been challenging. Hanikel et al . used single-crystal x-ray diffraction to locate all of the water molecules in pores of the metal-organic framework MOF-303 at different water loadings (see the Perspective by Öhrström and Amombo Noa). They used this information on the water molecule adsorption sequence to modify the linkers of this MOF and control the water-harvesting properties from humid air for different temperature regimes. —PDS

Science & Technology - Other Topics↗
DOE OSTI2020

Dam-Break Flow Measurements of Liquid–Granular Mixtures in a Channelized Reservoir

Dam-break flows of granular materials exhibit a complex non-Newtonian rheology, which is strongly influenced by various factors, such as the characteristics of the granular material, the degree of initial compaction, and saturation level of the granular matrix. Specially adapted nonintrusive techniques are required to investigate these flows in the laboratory. This paper investigated the nonintrusive technique of image analysis. The methodologies used in the measurement of bulk flow parameters, such as flow depth, front velocity, and flow rate, and the extraction of detailed flow characteristics such as velocity profiles, were discussed in the context of a series of granular dam-break flow experiments. These experiments were performed under three types of initial conditions: dry, saturated (water filling the pore space), and submerged (a layer of saturated granular material submerged under water) using four types of granular materials—PET pellets, crushed walnut shells, urea, and sand—with grain sizes ranging from 200 μm to 2.9 mm. High-speed cameras were used to capture the evolution and local properties of the flow, such as velocity fields using particle image velocimetry (PIV). Bulk properties of the flow were obtained by tracking the surface profile of the granular matrix and the water table. The extracted profiles were used to measure the evolution of the volume of the granular matrix and the fluid phase separately upstream and downstream of the gate, which allowed measuring the dilatancy (increase in pore space). The study showed that the image analysis techniques are versatile and can be adapted to measure different flow parameters in a variety of granular flows to better understand and analyze their complex behavior. Finally, the advantages and drawbacks of each image analysis technique were discussed and best-practice recommendations were provided.

42 ENGINEERING↗
DOE OSTI2025

Controlling matric potential in microfluidics to examine microbial dynamics in unsaturated porous media

The use of microfluidics for the study of soil microbial ecology is an emerging field. Most microfluidic studies of biological systems, however, have been performed under fully saturated conditions that are not representative of natural soil. Therefore, while microfluidics offer many unique capabilities that other methodologies cannot, they are not currently suited to address the effects of matric potential, an important variable defining the microbial moisture niche. Here, a methodology is presented that allows the user to control the aqueous conditions within microfluidic networks by manipulating matric potential using a hanging water column. The method relies on hydrophilic surface treatment of the microfluidic device using polyvinyl alcohol (PVA) and incorporating a bed of small pores at the network boundaries, which serve as a porous ceramic plate analogue (PPA). The method was validated on a simple capillary bundle and then on a more complex pore network. A water retention curve, exhibiting hysteresis, was generated for the pore network over a narrow matric potential range of 0 to – 5 kPa. Both the drainage and wetting curves were reproducible, as were the spatial configuration and the number of fragmented moisture niches in the pore network, particularly on the drainage curve. In contrast, the wetting curve exhibited greater variability in spatial configuration due to the “ink bottle effect,” where capillarity was interrupted by wider pore bodies. Ultimately, the methodology provides realistic pore-scale moisture conditions that can be easily manipulated and maintained, enabling new opportunities to explore soil biophysics and microbial biogeography in unsaturated porous media. As a brief example, images showing the localization of fluorescently tagged Pantoea sp. YR343 at −4.3 kPa are presented, highlighting bacterial distributions in water films and air-water interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Water transport in reverse osmosis membranes is governed by pore flow, not a solution-diffusion mechanism

We performed nonequilibrium molecular dynamics (NEMD) simulations and solvent permeation experiments to unravel the mechanism of water transport in reverse osmosis (RO) membranes. The NEMD simulations reveal that water transport is driven by a pressure gradient within the membranes, not by a water concentration gradient, in marked contrast to the classic solution-diffusion model. We further show that water molecules travel as clusters through a network of pores that are transiently connected. Permeation experiments with water and organic solvents using polyamide and cellulose triacetate RO membranes showed that solvent permeance depends on the membrane pore size, kinetic diameter of solvent molecules, and solvent viscosity. This observation is not consistent with the solution-diffusion model, where permeance depends on the solvent solubility. Motivated by these observations, we demonstrate that the solution-friction model, in which transport is driven by a pressure gradient, can describe water and solvent transport in RO membranes.

42 ENGINEERING↗
DOE OSTI2024

Confinement Effects on Proton Transfer in TiO 2 Nanopores from Machine Learning Potential Molecular Dynamics Simulations

Improved understanding of proton transfer in nanopores is critical for a wide range of emerging applications, yet experimentally probing mechanisms and energetics of this process remains a significant challenge. To help reveal details of this process, we developed and applied a machine learning potential derived from first-principles calculations to examine water reactivity and proton transfer in TiO 2 slit-pores. Here, we find that confinement of water within pores smaller than 0.5 nm imposes strong and complex effects on water reactivity and proton transfer. Although the proton transfer mechanism is similar to that at a TiO 2 interface with bulk water, confinement reduces the activation energy of this process, leading to more frequent proton transfer events. This enhanced proton transfer stems from the contraction of oxygen–oxygen distances dictated by the interplay between confinement and hydrophilic interactions. Our simulations also highlight the importance of the surface topology, where faster proton transport is found in the direction where a unique arrangement of surface oxygens enables the formation of an ordered water chain. In a broader context, our study demonstrates that proton transfer in hydrophilic nanopores can be enhanced by controlling pore size, surface chemistry, and topology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imogolite in water: Simulating the effects of nanotube curvature on structure and dynamics

Imogolite is a fascinating inorganic nanotube that is found in nature or synthesized in a laboratory. The synthesis process is carried out in liquid media, and leads to the formation of almost monodisperse diameter nanotubes. Here we investigate, employing classical molecular dynamics simulations, the interaction of water and imogolite for nanotubes of several radii. We established that water penetrates the pores of N = 9 and larger nanotubes, and adopts a coaxial arrangement in it. Also, while water molecules can diffuse along the center of the nanotube, the molecules next to the inner imogolite walls have very low mobility. At the outer nanotube wall, an increase of water density is observed, this effect extends up to 1 nm, beyond which water properties are bulk-like. Both phenomena are affected by the imogolite curvature.

58 GEOSCIENCES↗
DOE OSTI2025

Dehydration of Methyl Lactate on Alkali Cation-Exchanged Faujasite: Effects of Metal Cation Identity and Water Pressure

Turnover rates for the catalytic dehydration of methyl lactate (ML) over ion-exchanged faujasite (FAU) catalysts depend on the identity of alkali metal cations (Na + , K + , Cs + ) and local solvation effects. Analysis of rate measurements and in situ infrared spectroscopy gives evidence that the reaction involves kinetically relevant dissociation of adsorbed methyl lactate upon alkali metal cations. This process involves concerted methyl transfer to the surface and dissociation of the alkali metal from the framework, which occurs at cationic active sites that remain predominantly unoccupied under relevant conditions (0.5–10 kPa ML, 0.5–15 kPa H 2 O, 563–583 K). Despite the mechanistic similarities, apparent activation enthalpies (ΔH app ‡ ) decrease linearly (47 kJ mol –1 from Na + to Cs + ) with ionization energy and cationic radius, and apparent activation entropies (ΔS app ‡ ) decrease 74 J mol –1 K –1 . These trends reflect electrostatic interactions that stabilize the cations to the anionic sites on the zeolite: stronger association between these charges leads to increasingly endothermic processes to displace the alkali metal to form a cationic methoxy and an intrapore metal lactate intermediate. Water physisorption measurements suggest alkali metal ions bind superstoichiometric quantities of water within FAU pores, and in situ infrared spectra suggest the concerted adsorption of ML requires reorganization of this water. Consequently, these processes introduce entropic gains that partially offset entropy losses associated with ML adsorption. Hence, turnover rates differ only by a factor of 2 among Na-, K-, and Cs-FAU at 573 K (ΔΔG app ‡ = 5 kJ mol –1 ). These findings demonstrate the interplay of alkali metal ions with zeolite active sites and intrapore water clusters for ML dehydration, indicating that these interactions can be leveraged to deliver optimal performance under different reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗