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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Groundwater Age and Recharge Source on Nitrate Concentrations in Domestic Wells in the San Joaquin Valley

Nitrate is one of the most abundant contaminants in groundwater globally, in the United States, and in California (CA). We studied well construction information, water chemistry, stable isotopes, and noble gases to understand how groundwater travel time and recharge source and mechanism control nitrate concentrations in domestic wells in the San Joaquin Valley (SJV), CA, a large semiarid, irrigated agricultural region. Using nonparametric statistics, we find a decreasing trend in nitrates with groundwater travel time and well depth. Samples collected from wells that are closer to rivers and that show indications of river water recharge, either low recharge temperature or low δ 18 O signature, have lower concentrations of nitrates than samples with isotopic signatures indicating mixed source or local precipitation recharge. The curbing effect of river water recharge on nitrate concentrations in domestic wells is similar for direct river recharge and water applied as irrigation. This suggests that irrigation with river water also has a diluting effect that reduces the concentration of nitrate found in groundwater. This conclusion supports the idea that flood-managed aquifer recharge may be considered for remediation of groundwater nitrate when designing replenishment of aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Imaging Plasmons with Sub-2 nm Spatial Resolution via Tip-Enhanced Four-Wave Mixing

Four-wave mixing at plasmonic tip-sample nanojunctions may be used to visualize plasmonic fields with sub-2nm spatial resolution under ambient laboratory conditions. We illustrate the latter using a gold-coated atomic force microscopy probe irradiated with a pair of near-IR femtosecond laser pulses and used to interrogate plasmonic gold nanoplates and silver nanocubes. Through diagnostic polarization-dependent tip-only measurements, we illustrate that the 4-wave mixing signal is localized to the tip apex. The apex-bound signal is further enhanced when the tip is located near plasmonic nanoparticles. Overall, this work paves the way for visualizing coherent electronic and vibrational dynamics with joint femtosecond temporal and few-nanometer spatial resolution under ambient conditions.

Wang, Chih-Feng↗
DOE OSTI2022

Marine Boundary Layer Decoupling and the Stable Isotopic Composition of Water Vapor

Decoupling of the subcloud layer in stratocumulus-topped marine boundary layers (STMBL) influences low-cloud cover by limiting the supply of water vapor from the surface. However, the relative importance of mixing between surface fluxes and other reservoirs of water vapor as a function of the degree of decoupling is poorly understood. Water vapor transport within the STMBL and its response to decoupling is explored using surface measurements of water vapor isotopic composition that were obtained from Graciosa Island, Azores, during the summer and fall of 2018. The data show an inverse relationship between the decoupling metric, Δq, and the degree of drying from an isotopically depleted water vapor source. The isotopic data require some degree of drying with an isotopically depleted source for coupled conditions, and likely require a small amount of mixing even for strongly decoupled conditions. The data are consistent with mixing between purely local reservoirs of water vapor, subjected to a small amount of condensation and fractionation, and do not require the invocation of large-scale transport of water vapor aloft or additional cloud-formation effects aloft.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Strong band renormalization and emergent ferromagnetism induced by electron-antiferromagnetic-magnon coupling

The interactions between electrons and antiferromagnetic magnons (AFMMs) are important for a large class of correlated materials. For example, they are the most plausible pairing glues in high-temperature superconductors, such as cuprates and iron-based superconductors. However, unlike electron-phonon interactions (EPIs), clear-cut observations regarding how electron-AFMM interactions (EAIs) affect the band structure are still lacking. Consequently, critical information on the EAIs, such as its strength and doping dependence, remains elusive. Here we directly observe that EAIs induce a kink structure in the band dispersion of Ba 1–x K x Mn 2 As 2 , and subsequently unveil several key characteristics of EAIs. We found that the coupling constant of EAIs can be as large as 5.4, and it shows strong doping dependence and temperature dependence, all in stark contrast to the behaviors of EPIs. The colossal renormalization of electron bands by EAIs enhances the density of states at Fermi energy, which is likely driving the emergent ferromagnetic state in Ba 1–x K x Mn 2 As 2 through a Stoner-like mechanism with mixed itinerant-local character. Our results expand the current knowledge of EAIs, which may facilitate the further understanding of many correlated materials where EAIs play a critical role.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Electric light-duty vehicles have decarbonization potential but may not reduce other environmental problems

Electric vehicles are promoted as ‘clean’ technologies and offer promising reductions in transportation emissions. Nevertheless, their environmental benefits critically depend on the local electricity grid mix and the type of emission being considered. Here, we conduct a comparative life cycle assessment of the four dominant light-duty vehicle categories at both the global scale and in three representative countries: Norway, the US, and China. By analyzing different environmental indicators, particularly global warming potential and respiratory effects, and quantifying related parametric uncertainties, we reveal that the advantages of electric vehicles vary across these regions and across environmental impact types. While electric vehicles offer considerable decarbonization potential as the grid mix becomes cleaner, they might not mitigate other environmental impacts, such as increased respiratory effects on rural, low-income communities. Our results support stakeholders in identifying environmentally friendly vehicle and policy options while considering multiple factors, and emphasize the importance of tailored approaches over one-size-fits-all solutions in sustainable transportation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Halide sublattice dynamics drive Li-ion transport in antiperovskites

Here, in this work, we resolve how proton dynamics and halide mixing enhance or impede ionic conduction in protonated lithium antiperovskites (pLiAP) at compositions near the eutectic points of the halide salts. As a material class, pLiAPs of the form Li 3-x OH x X, (X = Cl, Br) show vast compositional design freedom; however, the resulting properties are susceptible to synthesis and processing methodologies. Proton incorporation and halide mixing stabilize the perovskite cubic phase at low temperatures (<50 °C) and using halide mixtures near the eutectic points (~250 to 300 °C) offer possibilities of lower temperature and faster synthesis and processing conditions (<1 h). Mixed-halide compositions such as Li 2 OHCl 0.37 Br 0.63 lead to a 30-fold improvement in room temperature ionic conductivity of a single halide structure, 1.5 × 10 -6 vs. 4.9 × 10 -8 S cm -1 (Li 2 OHCl). We combine infrared spectroscopy and nuclear magnetic resonance with first-principles density functional theory calculations to deconvolute halide mixing effects from local proton dynamics on Li-ion transport. In contrast to what has been supposed, our findings suggest that the halide sublattice dynamics, besides the OH rotation, correlate strongly with the fast-ion conduction at high temperatures.

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

IRIS-GNN: Leveraging Graph Neural Networks for Scheduling on Truly Heterogeneous Runtime Systems

The diversity of accelerators in computer systems poses significant challenges for software developers, such as managing vendor-specific compiler toolchains, code fragmentation requiring different kernel implementations, and performance portability issues. To address these, the Intelligent Runtime System (IRIS) was developed. IRIS works across various systems, from smartphones to supercomputers, enabling automatic performance scaling based on available accelerators. It introduces abstract tasks for seamless execution transitions between accelerators while ensuring memory consistency and task dependencies. Although IRIS simplifies system details, optimal dynamic scheduling still requires user input to understand workload structures. To address this, we introduce a new scheduling policy for IRIS, termed IRIS-GNN, which is the first IRIS hybrid policy that operates in conjunction with the dynamic policies. This policy employs a Graph-Neural Network (GNN) to conduct Graph Classification of any task graphs submitted to IRIS. This GNN analyzes the structure and attributes of the task graph, categorizing it as either locality, concurrency, or mixed. This classification subsequently guides the selection of the dynamic policy used by IRIS. We provide a comparison of the performance of IRIS-GNN against the complete spectrum of IRIS’s dynamic policies, assess the overhead introduced by the GNN within this scheduling framework, and ultimately explore its practical application in real-world scenarios.

Johnston, Beau↗
DOE OSTI2022

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w20_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. This was done by using machine learning (ML) techniques to develop emulators for subscale physics that can be used in coarse-scale continuum simulations, trained on fine-scale molecular dynamics (MD) simulations that are launched on-the-fly via active learning. raditional inertial confinement fusion (ICF) simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions; our approach directly accounts for this physics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Thermodynamic non-ideality and disorder heterogeneity in actinide silicate solid solutions

Non-ideal thermodynamics of solid solutions can greatly impact materials degradation behavior. We have investigated an actinide silicate solid solution system (USiO 4 –ThSiO 4 ), demonstrating that thermodynamic non-ideality follows a distinctive, atomic-scale disordering process, which is usually considered as a random distribution. Neutron total scattering implemented by pair distribution function analysis confirmed a random distribution model for U and Th in first three coordination shells; however, a machine-learning algorithm suggested heterogeneous U and Th clusters at nanoscale (~2 nm). The local disorder and nanosized heterogeneous is an example of the non-ideality of mixing that has an electronic origin. Partial covalency from the U/Th 5f–O 2p hybridization promotes electron transfer during mixing and leads to local polyhedral distortions. The electronic origin accounts for the strong non-ideality in thermodynamic parameters that extends the stability field of the actinide silicates in nature and under typical nuclear waste repository conditions.

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

Comparing Global Spray Combustion Characteristics and Local Shot-to-Shot Variations in a Reacting n -Heptane Spray

In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.

42 ENGINEERING↗
DOE OSTI2023

Entanglement structures in quantum field theories. II. Distortions of vacuum correlations through the lens of local observers

When observing a quantum field via detectors with access to only the mixed states of spatially separated, local regions—a ubiquitous experimental design—the capacity to access the full extent of distributed entanglement can be limited, shrouded by classical correlations. By performing projective measurements of the field external to two detection patches and classically communicating the results, underlying pure states may be identified for which entanglement quantification is clear. In the Gaussian continuous-variable states of the free scalar field vacuum, this protocol uncovers a disparity between the spacelike entanglement established within the field and that which is locally detectable. Further, this discrepancy is found to grow exponentially with the separation between observation regions. The protocol developed herein offers insight and practical guidance for clarifying the unavoidable distortion of quantum field correlations when viewed from the vantage of a pair of local observers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Interplay between Cation “Coloring” and Stereochemically Active Lone Pairs in AgBiS 2 Thin Films

Solution-processed AgBiS 2 thin films were fabricated using novel thiol− amine precursor inks to investigate the stereochemical activity of Bi 3+ 6s 2 lone pairs and their impact on the structure. A dual-space analysis combining Bragg diffraction and hard X-ray photoelectron spectroscopy (HAXPES) revealed a rock salt-like average structure with local distortions linked to cation coloring. Density functional theory (DFT) and crystal orbital Hamilton population (COHP) analyses confirmed that local Bi-rich and Ag-rich nanodomains amplify stereochemical activity, whereas more mixed and cation-order nanodomains are less stereochemically active. This local, nanoscopic mixing of segregated and ordered domains would indeed explain an average Fm3̅m structure that is rock salt-like and that does not manifest the full anharmonicity and noncentrosymmetry evidenced in canonical structures with stereochemical expression. These findings provide insights into the local structural and electronic complexities governing the optoelectronic properties of AgBiS 2 thin films.

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

Transient mixing behavior of a supercritical fluid injected into supercritical and subcritical environments

Transient, near-field mixing of a supercritical fluid injected into supercritical and subcritical environments is investigated experimentally. Fuel (propane) from a 100 μm diameter Bosch diesel injector is injected into a high-pressure test rig with a steady flow of heated, low-velocity nitrogen to control the ambient pressure and temperature. The fuel supply pressure is approximately 190 bar, allowing short injections lasting 3–4 ms to be performed in quick succession to acquire statistically significant datasets to represent the unsteady fuel–air mixing. Two test cases with the same ambient density and injector inlet pressure and temperature were chosen in an attempt to isolate effects of mixture phase behavior. Microscopic rainbow Schlieren deflectometry (RSD) is used for visualization and quantitative data acquisition. In the case of the supercritical ambient, the injector inlet and exit and ambient conditions are all supercritical. The RSD analysis reveals a mixing process similar to the single phase fluid mixing, though condensation is also observed locally, and can be explained by the adiabatic mixing theory presented in the paper. For the subcritical ambient case, the injector inlet is supercritical, but the injector exit and ambient conditions are both subcritical. The results show a rapid expansion in the near-field promoting mixing between propane and nitrogen. At downstream locations, significant condensation is also observed as predicted by the adiabatic mixing theory. As a result, the supercritical ambient case exhibited longer and narrower jet penetration compared to the subcritical ambient case.

02 PETROLEUM↗
DOE OSTI2020

Mixing states of Amazon basin aerosol particles transported over long distances using transmission electron microscopy

The Amazon basin is important for understanding the global climate because of its carbon cycle and as a laboratory for obtaining basic knowledge of the continental background atmosphere. Aerosol particles play an important role in the climate and weather, and knowledge of their compositions and mixing states is necessary to understand their influence on the climate. For this study, we collected aerosol particles from the Amazon basin during the Green Ocean Amazon (GoAmazon2014/5) campaign (February to March 2014) at the T3 site, which is located about 70 km from Manaus, and analyzed them using transmission electron microscopy (TEM). TEM has better spatial resolution than other instruments, which enables us to analyze the occurrences of components that attach to or are embedded within other particles. Based on the TEM results of more than 10 000 particles from several transport events, this study shows the occurrences of individual particles including compositions, size distributions, number fractions, and possible sources of materials that mix with other particles. Aerosol particles during the wet season were from both natural sources such as the Amazon forest, Saharan desert, Atlantic Ocean, and African biomass burning and anthropogenic sources such as Manaus and local emissions. These particles mix together at an individual particle scale. The number fractions of mineral dust and sea-salt particles increased almost 3-fold when long-range transport (LRT) from the African continent occurred. Nearly 20 % of mineral dust and primary biological aerosol particles had attached sea salts on their surfaces. Sulfates were also internally mixed with sea-salt and mineral dust particles. The TEM element mapping images showed that several components with sizes of hundreds of nanometers from different sources commonly occur within individual LRT aerosol particles. We conclude that many aerosol particles from natural sources change their compositions by mixing during transport. The compositions and mixing states of these particles after emission result in changes in their hygroscopic and optical properties and should be considered when assessing their effects on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mixing states of Amazon-basin aerosol particles transported over long distances using transmission electron microscopy

The Amazon basin is important for understanding the global climate both because of its carbon cycle and as a laboratory for obtaining basic knowledge of the continental background atmosphere. Aerosol particles play an important role in the climate and weather, and knowledge of their compositions and mixing states is necessary to understand their influence on the climate. For this study, we collected aerosol particles from the Amazon basin during the Green Ocean Amazon (GoAmazon2014/5) campaign (February to March 2014) at the T3 site, which locates about 70 km from Manaus, and analyzed using transmission electron microscopy (TEM). TEM has better spatial resolution than other instruments, which enables us to analyse the occurrences of components that attach to or are embedded within other particles. Based on the TEM results of more than 10,000 particles from several transport events, this study shows the occurrences of individual particles including compositions, size distributions, number fractions, and possible sources of materials that mix with other particles. Aerosol particles during the wet season were from both natural sources such as the Amazon forest, Saharan desert, Atlantic Ocean, and African biomass burning and anthropogenic sources such as Manaus and local emissions. These particles mix together at an individual particle scale. The number fractions of mineral dust and sea-salt particles increased almost three-fold when long-range transport (LRT) from the African continent occurred. Nearly 20 % of mineral dust and primary biological aerosol particles attached sea salts on their surfaces. Sulfates were also internally mixed with sea-salt and mineral dust particles. The TEM element mapping images showed that several components with sizes of hundreds of nanometres from different sources commonly occur within individual LRT aerosol particles. We conclude that many aerosol particles from natural sources change their compositions by mixing during transport. The compositions and mixing states of these particles after emission result in changes in their hygroscopic and optical properties and should be considered when assessing their effects on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Kinetic mixing, dark photons and extra dimensions. Part III. Brane localized dark matter

Extra dimensions have proven to be a very useful tool in constructing new physics models. In earlier work, we began investigating toy models for the 5-D analog of the kinetic mixing/vector portal scenario where the interactions of dark matter, taken to be, e.g., a complex scalar, with the brane-localized fields of the Standard Model (SM) are mediated by a massive U(1) D dark photon living in the bulk. These models were shown to have many novel features differentiating them from their 4-D analogs and which, in several cases, avoided some well-known 4-D model building constraints. However, these gains were obtained at the cost of the introduction of a fair amount of model complexity, e.g., dark matter Kaluza-Klein excitations. In the present paper, we consider an alternative setup wherein the dark matter and the dark Higgs, responsible for U(1) D breaking, are both localized to the ‘dark’ brane at the opposite end of the 5-D interval from where the SM fields are located with only the dark photon now being a 5-D field. The phenomenology of such a setup is explored for both flat and warped extra dimensions and compared to the previous more complex models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Simulation of gas mixture dynamics in a pipeline network using explicit staggered-grid discretization

Here we develop an explicit staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their planned lifetimes. Our computational method accommodates an arbitrary number of constituent gases with very different physical properties that may be injected into a network with significant spatiotemporal variation. In this setting, the gas flow physics are highly location- and time- dependent, so that local composition and nodal mixing must be accounted for. The resulting conservation laws are formulated in terms of pressure, partial densities and flows, and volumetric and mass fractions of the constituents. We include non-ideal equations of state that employ linear approximations of gas compressibility factors, so that the pressure dynamics propagate locally according to a variable wave speed that depends on mixture composition and density. We derive compatibility relationships for network edge boundary values that are more complex than for a homogeneous gas. The simulation method is evaluated on initial boundary value problems for a single pipe and a small network, is cross-validated with a lumped element simulation, and used to demonstrate a local monitoring and control policy for maintaining allowable concentration levels.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An aggregation-based nonlinear multigrid solver for two-phase flow and transport in porous media

A nonlinear multigrid solver for two-phase flow and transport in a mixed fractional-flow velocity-pressure-saturation formulation is proposed. The solver, which is under the framework of the full approximation scheme (FAS), extends our previous work on nonlinear multigrid for heterogeneous diffusion problems. The coarse spaces in the multigrid hierarchy are constructed by first aggregating degrees of freedom, and then solving some local flow problems. The mixed formulation and the choice of coarse spaces allow us to assemble the coarse problems without visiting finer levels during the solving phase, which is crucial for the scalability of multigrid methods. Specifically, a natural generalization of the upwind flux can be evaluated directly on coarse levels using the precomputed coarse flux basis vectors. We find that the resulting solver is applicable to problems discretized on general unstructured grids. The performance of the proposed nonlinear multigrid solver in comparison with the standard single level Newton's method is demonstrated through challenging numerical examples. It is observed that the proposed solver is robust for highly nonlinear problems and clearly outperforms Newton's method in the case of high Courant-Friedrichs-Lewy (CFL) numbers.

58 GEOSCIENCES↗