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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 OSTI2024

Fundamentals on dependence of volume on pressure and temperature

The common wisdom that volume decreases with pressure and increases with temperature is analyzed in terms of Hillert nonequilibrium thermodynamics in the present work. It is shown that the derivative of volume to pressure in a stable system is always negative, i.e., volume decreases with the increase of pressure, when all other natural variables of the system are kept constant. This originates from the stability requirement that the conjugate variables, such as volume and negative pressure, must change in the same direction in a stable system. Consequently, since volume and temperature are not conjugate variables, they do not have to change in the same direction and thus do change in opposite directions in both natural and man-made systems. It is shown that the decrease of volume with the increase of temperature, commonly referred as negative thermal expansion (NTE) in the literature, originates from the statistical competitions of configurations in the system when the volumes of metastable configurations are smaller than that of the ground-state configuration. As a result, it is demonstrated that the zentropy theory can concisely explain and accurately predict NTE based on the density functional theory without fitting parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Artificial neural networks estimate evapotranspiration for Miscanthus × giganteus as effectively as empirical model but with fewer inputs

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthu s × giganteus ( M . × giganteus ) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET. A combination of air temperature (T a ) and solar radiation (R s ) was chosen as inputs due to the highest R 2 for FFN (R 2 = 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only T a for NARX (R 2 = 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R 2 = 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A worldwide climatology of extreme air masses

Extreme temperature events are among the most damaging weather phenomena. In a warming world, more heat extremes and fewer cold extremes are expected in most regions in the future, a trade-off that warrants further understanding of such events. Here, we track and analyze large, persistent areas of hot and cold extreme temperatures in parallel, relative to the location and time of year, to quantify overall regional exposure to extreme temperatures. To accomplish this, we compare the frequencies, movements, trends, and sources/sinks in each type of extreme air mass, calling them extreme cold or extreme hot air masses (ECAMs/EHAMs). For most land regions, ECAMs occur more often than EHAMs, and ECAMs are more common in each hemisphere’s winter, when cold-air advection is strongest and most widespread. Average movement of ECAMs has a stronger equatorward component in winter than in summer, while movement of EHAMs is eastward all year, with less meridional movement than ECAMs. EHAMs have become more common almost everywhere on land, and the reverse is true for ECAMs, with the strongest trends in the northern hemisphere occurring in autumn, especially in the Arctic. The number of EHAMs around the world is increasing at a higher rate (+ 2.32 events/year) than ECAM numbers are decreasing (-1.27 events/year), causing a net increase in extremes, especially in some midlatitude regions. These results help to document the different processes driving hot and cold extremes, and thus the asymmetric and regionally varying trends in frequency for extreme air masses.

Ryan, James M↗
DOE OSTI2025

Workforce planning: a review of methodologies

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.

42 ENGINEERING↗
DOE OSTI2024

Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points

Abstract As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.

Wood, Richard A. (ORCID:0000000239609513)↗
DOE OSTI2024

Electron–Phonon Coupling in Copper-Substituted Lead Phosphate Apatite

Recent reports of room-temperature, ambient pressure superconductivity in copper-substituted lead phosphate apatite, commonly referred to as LK99, have prompted numerous theoretical and experimental studies into its properties. As the electron–phonon interaction is a common mechanism for superconductivity, the electron–phonon coupling strength is an important quantity to compute for LK99. In this work, we compare the electron–phonon coupling strength among the proposed compositions of LK99. The results of our study are in alignment with the conclusion that LK99 is a candidate for low-temperature, not room-temperature, superconductivity if electron–phonon interaction is to serve as the mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Chemical trends favoring interstitial cluster formation in bcc high-entropy alloys from first-principles calculations

Achieving high strength and ductility is a common goal in structural alloy design. Body-centered cubic high-entropy alloys (HEAs) commonly highlight the conflict between these properties, with stronger alloys being brittle and vice versa. Recent reports suggest interstitial solutes can be used to overcome this trade-off, in some cases providing both strength and ductility enhancements. This effect has been correlated with interstitial cluster formation, although the conditions favoring their formation remain incompletely understood. Using first-principles calculations of solution energies and diffusivities, we provide insights into thermodynamic and kinetic factors favoring interstitial solute clusters. Among C, N and O solutes, O interstitials display most desirable diffusion kinetics. Further, the results highlight the importance of local composition fluctuations in the HEAs to enable the formation of clusters of appreciable size. The results are explained in terms of bonding and distortion trends across solutes and HEA compositions to provide guidelines for alloy design.

Borges, Pedro P P O↗
DOE OSTI2025

Effect of stress on Laves phase precipitation in creep ruptured Grade 92 ferritic martensitic steel characterized by a novel accessible method

At high temperature conditions relevant to fossil and nuclear energy plants, Laves phase (Fe 2 X, X=Mo, W) precipitation is observed in common ferritic martensitic (FM) structural steels, with various reported effects on creep behavior. Despite being valuable metrics to correlate with mechanical properties and other precipitate phases, the volume fraction and number density of Laves phase precipitates has been difficult to quantify accurately using common techniques such as transmission electron microscopy (TEM) due to the relatively large size (∼0.25 μm) and low number density (∼10 11 cm −3 ) of Laves precipitates. Here, to address this characterization challenge, we developed and demonstrated a high-throughput and widely accessible method to quantify the volume fraction and number density of the Laves phase based on scanning electron microscope (SEM) images with a backscattered electron signal and the information depth (ID) of backscattered electrons. We applied this new technique in creep ruptured Grade 92 FM steel to study the effect of Laves phase on creep properties and determine the influence of stress on Laves phase precipitation. The quantitative accuracy of the SEM-based volume fraction and number density values was verified using synchrotron high energy X-ray diffraction and serial sectioning tomography. Stress did not significantly affect the Laves phase size or volume fraction during creep testing at 550 – 650°C and stress levels of 90 – 260 MPa (vs. unstressed conditions). Conversely, a moderate but statistically significant stress-enhanced increase in Laves phase number density, corresponding to an increase in nucleation rate, occurred during creep exposure above 110 MPa.

Creep↗
DOE OSTI2024

Methodology to determine printability criteria of highly concentrated pastes through rheological characterization

Material extrusion is an additive manufacturing technique that enables the creation of reproducible and complex hardware by depositing a viscous, shear-thinning ink onto a substrate in a custom-pattern via extrusion through a syringe. Here, the ability of an ink to be extruded onto a substrate in many layers, and maintain the desired shape is what defines the printability. Printability is often investigated by formulating, printing, and postmortem analysis of final parts in an iterative manner. Investigations of printability through rheological characterization have often been concerned with inks that straddle the line between printable and too thin, leaving out an entire class of inks that are highly-filled pastes, where extrudability is the limiting factor. Highly-filled pastes continue to pose issues for researchers as the effect of filler morphology, size, loading, and packing fraction on the ink rheology and corresponding printability is not understood. While traditional rheological characterizations may be useful for some inks, we show that protocols utilizing steady-shear, or large-amplitude oscillatory shear are difficult and unreliable for highly-filled pastes. Through transient rheology paired with real-time images we show that each traditional protocol produces inhomogeneous deformations that violate the assumptions that underly common rheological definitions. Instead, we demonstrate metrics measured with small-amplitude oscillatory shear that are correlated to the printability of various ink formulations ranging in loading. The rheological measures that accurately predict the printability of the inks are the axial stress measured at small amplitudes, and the critical stress amplitude above which rheological characterizations become impossible. In addition, we estimate the maximum packing fraction for each filler, based on the exponent common to hard sphere models, and show that the printability of each ink can be predicted by the ratio of the packing fraction to the theoretical maximum. We show how small-amplitude oscillatory shear allows users to develop printability criteria for any ink to enhance the workflow in the development of new inks, increase the performance of material extrusion printing, and improve the stability of printed parts, with less wasted time and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Infrared triggered dwell and active cooling thermal control effects on microstructural uniformity in DED

Directed Energy Deposition (DED) offers rapid large scale fabrication, but difficulty in delivering consistent microstructures and properties hinders the use of DED fabricated components in safety or performance critical applications. Variability stems from the complex thermal cycles generated by the toolpath used to print the required geometry. Several practical methods have become established in DED to regulate overheating, such as active cooling of the baseplate structure or the use of an infrared camera to inject interlayer pauses to ensure the top layer of the component cools to a set temperature, which have been shown to affect microstructure. However, no critical assessment has been performed as to how effective these controls are in promoting microstructural uniformity in the context of complex layer timing commonly generated by non-prismatic geometries. Here we show how controls influence the thermal field, phase transformations, and dynamic annealing of a low-temperature transformation steel using infrared imaging and operando neutron diffraction. Counterintuitively, common thermal homogenization process controls can reduce microstructural uniformity because these approaches stabilize peak temperature while overlooking temperatures near the solid-state phase transformation fronts. Instead, the cyclic reheating induces spatially-variant dynamically annealed regions which can be modulated via control parameters. We show that these controls have spatially linked effects centimeters away from the active weld, which implies that microstructure control must co-optimize thermal input across many subsequent layers. In conclusion, our results demonstrate the pressing need for higher order controls that integrate predictive elements of simulation data to stabilize printed properties for future qualification of DED components.

Directed energy deposition↗
DOE OSTI2024

An empirical analysis of supply offers in the ERCOT operating reserves markets

Here, this paper seeks to improve theoretical and empirical understanding of supplier dynamics in wholesale markets for operating reserves, which have been understudied compared to energy markets. We begin by identifying several economic factors that unit owners may consider when submitting offers into operating reserves auctions in two-stage, co-optimized markets common across much of North America. Next, we analyze historical offer data from the Electric Reliability Council of Texas (ERCOT) market to assess whether actual reserve market behavior aligns with expectations based on economic theory, as well as with commonly used assumptions in electricity market modeling efforts. We find that the aggregate supply of operating reserves in ERCOT varies meaningfully over time, becoming more expensive during summer afternoons, which is consistent with theoretical expectations but contradicts the typical modeling assumption of temporally invariant reserve offers. Analysis of offers made by individual units uncovers additional insights, such as the existence of large offer pattern differences by unit owner and the tendency of battery storage units to submit very low offer prices. We conclude by discussing how our findings can be integrated into electricity market modeling assumptions to improve alignment with observed operating reserve offer inputs and pricing outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A Trichomonas vaginalis C2-XYPPX-repeat protein with a structured C2 domain displaying dampened flexibility upon binding calcium

C2 domains are ubiquitous membrane-binding modules of ∼130 residues in eukaryotes that are often associated with proteins involved in membrane trafficking and lipid modification. The genome of Trichomonas vaginalis, the most common, non-viral, sexually transmitted human pathogen, encodes eight genes that contain a N-terminal C2 module linked to a XYPPX-repeat domain of more than four XYPPX repeats (C2-XYPPX). While the function of the XYPPX-repeat domain remains unknown, its multiple association with C2 domains in T. vaginalis suggests it is important. Here, the C2 domain from one of these C2-XYPPX-repeat proteins, Tv-C2-1, was structurally and physically characterized using X-ray crystallography and NMR spectroscopy. The crystal structure for Tv-C2-1 shows that this domain shares a fold common to all C2 domains, a compact Greek-key motif composed of eight anti-parallel β-strands in the type-2 topology. An NMR chemical shift perturbation study with Ca 2+ showed that Tv-C2-1 bound two Ca 2+ atoms primarily via two loops (loop-1 and loop-3) on the predicted calcium binding face of the protein with K d s of 58.0 ± 0.1 μM and 232 ± 6 μM. Estimations of the overall rotational correlation time, τ c , in the apo (11.1 ns) and Ca 2+ -bound (9.2 ns) state suggests the protein becomes more compact upon Ca 2+ binding, consistent with a decrease in dynamics in loop-3 and marginally in loop-1 suggested by amide 15 N heteronuclear steady-state { 1 H}- 15 N NOEs. Showing Tv-C2-1 binds calcium and adopts a compact Greek-key motif structure, two primary features of C2 domains, suggests understanding the function of the XYPPX-repeat domain may be warranted.

NMR spectroscopy↗
DOE OSTI2025

Effect of bisphosphonate treatment on the oim mouse middle ear ossicles' structure, composition and hearing

Hearing loss is common in people with osteogenesis imperfecta (OI or brittle bone disease). Bisphosphonates are commonly used to treat long bone fragility in children with OI. However, its impact on the bone quality of the middle ear ossicles and hearing remains unknown. This study determines whether bisphosphonates treatment itself may contribute to hearing loss in OI by evaluating its effects in the oim/oim mouse model of severe OI having normal auditory function. Specifically, this study reports the effects of alendronate (ALN), a nitrogen-containing bisphosphonate, on ossicle morphology, porosity, and elemental composition in 14-week-old oim/oim mice treated weekly, starting at 2 weeks of age. The ossicles were examined using synchrotron microtomography and X-ray fluorescence microscopy (XFM). Hearing was assessed longitudinally until 26 weeks of age by determining auditory brainstem response (ABR) thresholds in another group of mice also treated weekly starting at 2 weeks of age. ALN treatment further reduces in size the already small oim/oim ossicles, specifically in female mice. Porosity, bone composition, and hearing function, however, were generally not affected by the ALN treatment. Furthermore, ALN does not prevent joint fusions, excessive bone formations, or enlarged joint spaces in WT or oim/oim experimental groups. One ALN-treated oim/oim mouse with a bone formation in the interior of the footplate, and one ALN-treated WT mouse with a fixed footplate had frequency-specific hearing loss. Since footplate abnormalities are not observed in PBS-treated mice in this study, it remains unclear whether ALN fails to prevent these changes or contributes to their development. Future studies should investigate the mechanisms of ossicular abnormalities and bisphosphonates modulatory role in the ossicles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Mobility of heavy rare earth elements in magmatic-hydrothermal systems: Experimental determination of DyPO 4 solubility in supercritical fluids

Dysprosium (Dy) is part of the heavy rare earth elements (REE) and a critical component in the production of high-performance super magnets used in wind turbines, electric vehicles, and other green technologies. The HREE phosphate, xenotime, is commonly associated with hydrothermal systems, where the mobility, fractionation, and deposition of REE are controlled by the stability of aqueous complexes and solubility of REE minerals which depend on temperature, pressure, and fluid composition (salinity, pH, and ligand availability). Here, we conducted a series of synthetic DyPO 4 solubility experiments in NaCl-HCl-bearing aqueous solutions (pH of 2 at 25 °C) from 500 to 700 °C and 1.5 kbar using externally heated pressure vessels. DyPO 4 displays a strong prograde solubility with temperature across all studied fluid salinities (0–0.5 m NaCl). The DyPO₄ solubility isotherms at 500 °C, 600 °C, and 700 °C show a complex relationship with salinity where DyPO₄ solubility is highest (39.2–1552 ppm at 500–700 °C) in 0 m NaCl solutions, decreases strongly (21–331 ppm at 500–700 °C) in the 0.06 m NaCl solutions and remains relatively constant in the 0.25 m (42.8–248 ppm) and 0.5 m NaCl (40.2–124 ppm) solutions. Thermodynamic modeling suggests that pH increases as a function of temperature and salinity, and controls solubility due to the stability of chloride complexes (i.e., DyCl +2 and DyCl 2 + ) at 500–600 °C, transitioning to hydroxyl complexes (i.e., Dy(OH) 3 0 ) dominating at 700 °C and relatively alkaline pH. Comparison with NdPO 4 solubility data indicates that the light REE in monazite is significantly more soluble than the heavy REE in xenotime in saline fluids at high temperature (500–700 °C), implying efficient light/heavy REE fractionation in supercritical fluids. The lower solubility of DyPO 4 relative to NdPO 4 suggests that at high temperatures, acidic (pH 2–4), low-salinity (∼5 wt% NaCl) fluids will favor the precipitation of xenotime over monazite as it will cool from 700 °C to below 500 °C. These observations align with paragenetic mineral assemblages in NYF pegmatites (e.g., Baveno, Italy), where xenotime commonly immobilizes heavy REE during the high-temperature hydrothermal stages.

58 GEOSCIENCES↗
DOE OSTI2026

Exploring stages of resilience maturity as communities confront climate risks

Coastal communities are facing increased risks due to climate change, as evidenced by heightened shocks such as hurricanes and wildfires, and stressors including sea-level rise and drought. To confront these risks, many coastal communities are planning and designing their built environments in new ways, with the overall goal of increasing their resilience. However, resilience practices have been widely guided by an event-based timeframe, which may not be sufficient to confront the multiple and overlapping threats expected over the coming decades. To address this concern, this study investigated a long-term perspective on resilience progression, termed resilience maturity. To better understand resilience maturity in practice, this study drew directly on community perspectives, thereby identifying common challenges. Furthermore, variation in resilience maturity across communities provided an opportunity to identify existing successful strategies. Inductive qualitative analysis was used to examine perspectives from 15 interviews with local practitioners across 12 coastal communities. The analysis revealed that communities in early stages of resilience maturity often struggle with local stakeholder alignment and minimal dedicated resilience resources. In contrast, those further along the maturity path often face technology barriers and challenges in aligning regional stakeholders. Few examples of a fully mature resilience culture were found within the communities studied, underscoring systemic barriers to achieving advanced resilience maturity. Overall, these findings supported development of a practical framework for classifying community resilience efforts, identifying common obstacles, and informing localized resilience advancement.

Resilience maturity↗
DOE OSTI2025

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery↗
DOE OSTI2025

Converting sWeights to probabilities with density ratios

The use of machine learning approaches continues to have many benefits in experimental nuclear and particle physics. One common issue is generating training data which is sufficiently realistic to give reliable results. Here we advocate using real experimental data as the source of training data and demonstrate how one might subtract background contributions through the use of probabilistic weights which can be readily applied to training data. The sPlot formalism is a common tool used to isolate distributions from different sources. However, the negative sWeights produced by the sPlot technique can cause training problems and poor predictive power. This article demonstrates how density ratio estimation can be applied to convert sWeights to event probabilities, which we call drWeights. The drWeights can then be applied to produce the distributions of interest and are consistent with direct use of the sWeights. This article will also show how decision trees are particularly well suited to convert sWeights, with the benefit of fast prediction rates and adaptability to aspects of experimental data such as the data sample size and proportions of different event sources. We also show that a density ratio product approach in which the initial drWeights are reweighted by an additional converter gives substantially better results.

Glazier, Derek I. [Univ. of Glasgow, Scotland (Uni↗
DOE OSTI2025

Fungal endophytes

Organisms are commonly grouped into ecological guilds that reflect their shared resource use and similar ecological roles. The guild concept has been used to categorize the vast diversity of the fungal kingdom (estimated at 2.2–5 million species) into groups of fungi with common lifestyles, such as mycorrhizal symbionts, pathogens of animals and plants, and the group that is the focus of this primer — fungal endophytes of plants. Fungal endophytes have resisted scientists’ attempts to silo organisms into neat assemblages. In conclusion, scattered across the fungal tree of life and lacking few diagnostic characteristics, they are defined less by what they are than by what they are not.

Cosner, Julian [Oak Ridge National Laboratory (ORN↗