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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Cosmological neutrino mass: a frequentist overview in light of DESI

We derive constraints on the neutrino mass using a variety of recent cosmological datasets, including DESI BAO, the full-shape analysis of the DESI matter power spectrum and the one-dimensional power spectrum of the Lyman-α forest (P1D) from eBOSS quasars as well as the cosmic microwave background (CMB). The constraints are obtained in the frequentist formalism by constructing profile likelihoods and applying the Feldman-Cousins prescription to compute confidence intervals. This method avoids potential prior and volume effects that may arise in a comparable Bayesian analysis. Parabolic fits to the profiles allow one to distinguish changes in the upper limits from variations in the constraining power σ of the different data combinations. We find that all profiles in the ΛCDM model are cut off by the ∑m ν ≥ 0 bound, meaning that the corresponding parabolas reach their minimum in the unphysical sector. The most stringent 95% C.L. upper limit is obtained by the combination of DESI DR2 BAO, Planck PR4 and CMB lensing at 53 meV, below the minimum of 59 meV set by the normal ordering. The corresponding constraining power σ is 43 meV, which highlights the importance of the cut-off by negative values in the determination of the upper limit. Extending ΛCDM to non-zero curvature and w 0 w a CDM relaxes the constraints past 59 meV again, but only w 0 w a CDM exhibits profiles with a minimum at a positive value. Additionally, we extend the formalism to constrain the lightest neutrino mass. For DESI DR2 BAO, Planck PR4 and CMB lensing, we find confidence limits at 20 and 19 meV for normal and inverted ordering, respectively. Using a combination of DESI DR1 full-shape, BBN and eBOSS Lyman-α P1D, we successfully constrain the neutrino mass independently of the CMB. This combination yields m l ≤ 97 and 98 meV in the normal and inverted orderings, and total neutrino mass ∑m ν ≤ 285 meV (95% C.L.). The addition of DESI full-shape or Lyman-α P1D to CMB and DESI BAO results in small but noticeable improvement of the constraining power of the data. Lyman-α free-streaming measurements especially improve the constraint. Since they are based on eBOSS data, this sets a promising precedent for upcoming DESI data.

Frequentist statistics↗
DOE OSTI2024

The Grid Value of Ocean Current Energy in Florida

Ocean current energy technology has been proposed as a potential contributor to Florida's energy portfolio. There has been limited investigation of how this energy would be valued when integrated into the Florida electrical grid. This study assesses three future grid scenarios to evaluate the impact of adding zero-cost ocean current energy to each. The Resource Planning Model, a tool developed by the National Renewable Energy Laboratory, is used to identify the least-cost generation mix through 2050, with and without ocean current energy. The first scenario is a base case and assumes existing policies in which the addition of ocean current energy does not retire fossil-based technologies but variable generation technologies. In the second scenario, solar and storage technologies are lower cost, and the addition of ocean current generation enables those technologies along with wind to retire existing natural gas units earlier. In the third scenario, which requires a 95% reduction in carbon emissions from 2020 levels by 2050, ocean current energy can play a role in decarbonization along with other variable generation technologies. This analysis is intended to inform stakeholders on the opportunity, potential challenges, and overall value to the grid of ocean current technology from a reliability and availability focused perspective.

capacity expansion model↗
DOE OSTI2024

The Grid Value of Ocean Current Energy in Florida: Preprint

Ocean current technology has been proposed as a potential contributor to Florida's energy portfolio. There has been limited investigation of how this energy would be valued when integrated into the Florida electrical grid. This study assesses three future grid scenarios to evaluate the impact of adding ocean current to each. NREL's capacity expansion model, Resource Planning Model, is used to identify the least-cost generation mix through 2050, with and without ocean current. The first scenario, Business as Usual, Base case assuming current policies, ocean current does not replace fossil-based technologies. In the second scenario, we allow solar and storage to have lower costs than the first scenario which allows ocean current to retire gas earlier and more variable generation technologies to be deployed. In the third scenario, the Florida carbon constraint 95 by 2050 from 2020 levels case, ocean current can play a bigger role in decarbonization than the two other cases when coupled with other technologies.

capacity expansion model↗
DOE OSTI2023

Application of machine learning for modeling brønsted-guggenheim-scatchard specific ion interaction theory (SIT) coefficients

Machine learning methodologies can provide insight into Brønsted-Guggenheim-Scatchard specific ion interaction theory (SIT) parameter values where experimental data availability may be limited. This study develops and executes machine learning frameworks to model the SIT interaction coefficient, ε. Key findings include successful estimations of ε via artificial neural networks using clustering and value prediction approaches. Additionally, applicability to other chemical parameters is also assessed briefly. Models developed here provide support for a use-case of machine learning in geologic nuclear waste disposal research applications, namely in predictions of chemical behaviors of high ionic strength solutions (i.e., subsurface brines).

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

Congestion levels on existing infrastructure

Congestion occurs when available least-cost energy cannot be delivered to some loads because transmission facilities do not have sufficient capacity to deliver the energy. When a transmission constraint is binding (i.e., its limit is reached) it has an associated shadow price – the marginal value of relieving the constraint (i.e., of increasing the asset’s flow limit). This report contains one page dedicated to each ISO and RTO in the U.S. documenting empirical outcomes related to binding constraints during 2022 through 2024 for both the day-ahead and real-time markets. For each system operator and market timeline, the report contains two maps of infrastructure elements that are color-coded based on congestion characteristics. The first map provides information on how often each element has a binding constraint, that is, the frequency of congestion on the element. The second map reflects the intensity of congestion, measured as the sum of shadow prices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

On the hot surface ignition of a wall-stagnating spray flame

The ignition of fuel sprays due to interaction with hot surfaces is an important phenomenon in the safety analysis of many engineering systems. We perform a parametric study of the hot surface ignition (HSI) of a fuel spray approaching a heated surface caused by the accidental leakage of a fuel line. Here, to this end, we employ a one-dimensional Eulerian-Eulerian formulation with a non-equilibrium evaporation model and a realistic chemical mechanism to describe $n$-dodecane fuel chemistry. We first describe and analyze the phenomenology of the unsteady processes leading to ignition using non-dimensionalized quantities. Through consideration of the temporal development of the most reactive mixture, we demonstrate that ignition occurs at a fuel-lean composition in a premixed region near the hot surface. Using non-dimensional parameters identified from the governing equations, we perform a parametric study of the time, location and local mixture composition at ignition and determine the ignition limits. We then identify the most important parametric sensitivities for physical analysis using a data-driven classification method. Our analysis demonstrates a contraction of the ignition limits with increased Stokes number and a regime of parametric insensitivity of igniting mixture composition. We also show that at high Damköhler numbers, the ignition location conforms to the parametric behavior of the thermal boundary layer, whereas at low Damköhler numbers approaching the ignition limit it reaches a near-unity value of the quenching Peclet number. We then compare the demonstrated parametric dependencies to the results of the quasi-steady asymptotic ignition literature, showing that our results are consistent with those obtained analytically within the limitations imposed by the simplified formulation of the latter.

42 ENGINEERING↗
DOE OSTI2023

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Abstract Aircraft measurements reveal ice supersaturation statistics in cirrus (ISSs) with broad maxima around ice saturation and pronounced variance. In this study, processes shaping ISSs in midlatitude and tropical upper tropospheric conditions are systematically investigated. Water vapor deposition and sublimation of size‐resolved ice crystal populations are simulated in an air parcel framework. Mesoscale temperature fluctuations (MTFs) due to gravity waves force the temporal evolution of supersaturation. Various levels of background wave forcing and cirrus thickness are distinguished in stochastic ensemble simulations. Kinetic limitations to ice mass growth are brought about by supersaturation‐dependent deposition coefficients that represent efficient and inefficient growth modes as a function of ice crystal size. The simulations identify a wide range of deposition coefficients in cirrus, but most values stay above 0.01 such that kinetic limitations to water uptake remain moderate. Supersaturation quenching times are long, typically 0.5–2 hr. The wave forcing thus causes a remarkably large variability in ISSs and cirrus microphysical properties except in the thickest cirrus, producing ensemble‐mean ISSs in line with in‐situ measurements. ISS variance is controlled by MTFs and increases with decreasing cirrus integral radii. In comparison, the impact of ice crystal growth rates on ISSs is small. These results contribute to efforts directed at identifying and solving issues associated with ice‐supersaturated areas and non‐equilibrium cirrus physics in global models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Hole-Trapping-Induced Stabilization of Ni 4+ in SrNiO 3 /LaFeO 3 Superlattices

Creating new functionality in materials containing transition metals is predicated on our ability to control the associated charge states. For a given metal, forming lower oxidation states is typically easier than generating higher values, and there is an upper limit on valence that is not exceeded under normal conditions. Here we demonstrate that we can exceed the normal upper limit of 3+ for Ni and Fe via synthesis of (SrNiO 3 )m/(LaFeO 3 )n superlattices by tuning n and m. The Goldschmidt tolerance constraints are lifted and SrNi 4+ O 3 with holes on adjacent O anions can be stabilized as a perovskite at the single unit cell level (m = 1). Spectroscopy reveals that the n = 1 superlattice contains Ni 3+ and Fe 4+ , whereas Ni 4+ and Fe 3+ are observed in the n = 5 superlattice. Here, our results show that the B-site cation valences can be tuned by controlling the magnitude of the FeO6 octahedral rotations which in turn drive the energy balance between Ni 3+ /Fe 4+ and Ni 4+ /Fe 3+ , thus controlling emergent electrical properties such as the band alignment and resulting hole confinement. We suggest that this approach may be generally useful for synthesizing novel, metastable layered structures with new functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evolution of the Electronic Gap of Directly Synthesized Versus Mechanically Transferred WS 2 Monolayer to Multilayer Films

The electronic properties of 2D materials play a critical role in determining their potential for device applications. Despite rapid developments in 2D semiconductors, studies of fundamental electronic parameters, including the electronic gap and ionization energy, are limited, with significant discrepancies in reported values. The study focuses on tungsten disulfide (WS₂) and investigates the electronic structure of films comprising an increasing number of layers deposited with two different methods: direct synthesis via metal–organic chemical vapor deposition (MOCVD) and additive mechanical transfer of exfoliated single layers. The films are characterized via Raman, UV–vis, and photoluminescence spectroscopies, as well as ultraviolet photoelectron and inverse photoemission spectroscopies (UPS/IPES). The electronic gap of WS₂ is found to decrease from 2.43 eV for the monolayer to 1.97 eV for the trilayer, indicating a bulk transition at the trilayer thickness. This reduction in the electronic gap is primarily due to the downward shift of the conduction band minimum relative to the valence band maximum. A comparative analysis with MOCVD-grown WS₂ reveals a slightly larger electronic gap for MOCVD-grown samples, attributed to differences in defect densities. The electronic levels evaluated through UPS/IPES highlight the significant influence of preparation methods on the electronic properties of WS₂.

2D materials↗
DOE OSTI2024

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗
DOE OSTI2026

Microbial valorization of lignin to malic acid by Aspergillus niger

Lignin is the largest renewable source of aromatic carbon, yet its heterogeneity and recalcitrance limit its use in higher-value bioconversion processes. In this study, Aspergillus niger was engineered to enable the bioconversion of lignin-derived aromatics and base-catalyzed depolymerized (BCD) lignin streams into malic acid, a value-added C4 dicarboxylic acid with broad industrial relevance. Overexpression of the C4 dicarboxylate transporter C4T318 from Aspergillus oryzae enhanced malic acid secretion, while medium optimization under buffered conditions further improved the production. The engineered strain efficiently assimilated representative lignin-derived aromatics, including 4-hydroxybenzoic acid and p-coumaric acid, producing up to 3.9 g/L malic acid. Conversion of BCD lignin liquors from poplar and sorghum demonstrated effective utilization of heterogeneous aromatic mixtures, generating up to 0.82 g/L malic acid. This work demonstrates direct fungal conversion of real lignin streams into malic acid and establishes A. niger as a promising platform for sustainable lignin valorization.

Aromatic bioconversion↗
DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Frictional Contacts Between Individual Woody Biomass Particles under Wet and Dry Conditions

Friction between wood particles can be a critical property when designing processing equipment for creating cellulosic biofuels and similar natural products. Also, as wood processing is likely to occur year-round, understanding the friction between wet as well as dry wood particles can help design and model equipment, such as screw feeders. Here, a tribo-rheometry method was developed using a commercial rheometer that measured the torque required to rotate two contacting millimeter-scale wood chip particles. First, a range of normal forces were used to find the limits of the experimental method. Torque values were measured for seven pairs of wood chip particles at 1 N normal force under both dry and wet conditions, at both ambient conditions and in a humidity-controlled chamber. The torque required to rotate the wet particles was consistently higher than that of the dry particles, although differences were not quite statistically significant when measurements were performed at ambient conditions. Using humidity control resulted in torque values for wet particles of 1900 uNm and 900 uNm for dry particles. Finally, the friction coefficient was calculated as 0.23 for wet particles and 0.11 for dry particles when humidity was controlled. These frictions coefficients agreed with values for wood reported in the literature. Overall, controlling humidity is strongly recommended to quantify the range of friction for particles that uptake water, including granular systems from biomass to food to powders.

biomass↗
DOE OSTI2020

Negatively Charged Excitons in CdSe Nanoplatelets

The low-temperature emission spectrum of CdSe colloidal nanoplatelets (NPLs) consists of two narrow lines. The high-energy line stems from the recombination of neutral excitons. The origin of the low-energy line is currently debated. Here, we experimentally study the spectral shift, emission dynamics, and spin polarization of both lines at low temperatures down to 1.5 K and in high magnetic fields up to 60 T and show that the low-energy line originates from the recombination of negatively charged excitons (trions). This assignment is confirmed by the NPL photocharging dynamics and associated variations in the spectrum. We show that the negatively charged excitons are considerably less sensitive to the presence of surface spins than the neutral excitons. The trion binding energy in three-monolayer-thick NPLs is as large as 30 meV, which is 4 times larger than its value in the two-dimensional limit of a conventional CdSe quantum well confined between semiconductor barriers. A considerable part of this enhancement is gained by the dielectric enhancement effect, which is due to the small dielectric constant of the environment surrounding the NPLs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Eminuscent phase in frustrated magnets: a challenge to quantum spin liquids

A geometrically frustrated (GF) magnet consists of localised magnetic moments, spins, whose orientation cannot be arranged to simultaneously minimise their interaction energies. Such materials may host novel fascinating phases of matter, such as fluid-like states called quantum spin-liquids. GF magnets have, like all solid-state systems, randomly located impurities whose magnetic moments may “freeze” at low temperatures, making the system enter a spin-glass state. We analyse the available data for spin-glass transitions in GF materials and find a surprising trend: the glass-transition temperature grows with decreasing impurity concentration and reaches a finite value in the impurity-free limit at a previously unidentified, “hidden”, energy scale. We propose a scenario in which the interplay of interactions and entropy leads to a crossover in the permeability of the medium that assists glass freezing at low temperatures. This low-temperature, “eminuscent”, phase may obscure or even destroy the widely-sought spin-liquid states in rather clean systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Global nitrogen deposition inputs to cropland at national scale from 1961 to 2020

Nitrogen (N) deposition is a significant nutrient input to cropland and consequently important for the evaluation of N budgets and N use efficiency (NUE) at different scales and over time. However, the spatiotemporal coverage of N deposition measurements is limited globally, whereas modeled N deposition values carry uncertainties. Here, we reviewed existing methods and related data sources for quantifying N deposition inputs to crop production on a national scale. We utilized different data sources to estimate N deposition input to crop production at national scale and compared our estimates with 14 N budget datasets, as well as measured N deposition data from observation networks in 9 countries. We created four datasets of N deposition inputs on cropland during 1961–2020 for 236 countries. These products showed good agreement for the majority of countries and can be used in the modeling and assessment of NUE at national and global scales. One of the datasets is recommended for general use in regional to global N budget and NUE estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A machine learning estimator trained on synthetic data for real-time earthquake ground-shaking predictions in Southern California

Abstract After large-magnitude earthquakes, a crucial task for impact assessment is to rapidly and accurately estimate the ground shaking in the affected region. To satisfy real-time constraints, intensity measures are traditionally evaluated with empirical Ground Motion Models that can drastically limit the accuracy of the estimated values. As an alternative, here we present Machine Learning strategies trained on physics-based simulations that require similar evaluation times. We trained and validated the proposed Machine Learning-based Estimator for ground shaking maps with one of the largest existing datasets (<100M simulated seismograms) from CyberShake developed by the Southern California Earthquake Center covering the Los Angeles basin. For a well-tailored synthetic database, our predictions outperform empirical Ground Motion Models provided that the events considered are compatible with the training data. Using the proposed strategy we show significant error reductions not only for synthetic, but also for five real historical earthquakes, relative to empirical Ground Motion Models.

Environmental Sciences & Ecology↗
DOE OSTI2020

Perspective on Kramers symmetry breaking and restoration in relativistic electronic structure methods for open-shell systems

Without rigorous symmetry constraints, solutions to approximate electronic structure methods may artificially break symmetry. In the case of the relativistic electronic structure, if time-reversal symmetry is not enforced in calculations of molecules not subject to a magnetic field, it is possible to artificially break Kramers degeneracy in open shell systems. This leads to a description of excited states that may be qualitatively incorrect. Despite this, different electronic structure methods to incorporate correlation and excited states can partially restore Kramers degeneracy from a broken symmetry solution. For single-reference techniques, the inclusion of double and possibly triple excitations in the ground state provides much of the needed correction. Formally, however, this imbalanced treatment of the Kramers-paired spaces is a multi-reference problem, and so methods such as complete-active-space methods perform much better at recovering much of the correct symmetry by state averaging. Using multi-reference configuration interaction, any additional corrections can be obtained as the solution approaches the full configuration interaction limit. A recently proposed “Kramers contamination” value is also used to assess the magnitude of symmetry breaking.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗