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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Large negative magnetoresistance in the off-stoichiometric topological semimetal PrSb x Te 2- x

Magnetic topological materials LnSbTe (Ln = lanthanide) have attracted intensive attention because of the presence of interplay between magnetism, topological, and electron correlations depending on the choices of magnetic Ln elements. Varying Sb and Te composition is an efficient approach to control structural, magnetic, and electronic properties. Here we report the composition-dependent properties in PrSb x Te 2-x . We identified the tetragonal-to-orthorhombic structure transitions in this material system, and very large negative magnetoresistance in the x = 0.3 composition, which might be ascribed to the coupling between magnetism and transport. Such unusual magnetotransport enables PrSb x Te 2-x topological materials as a promising platform for device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Cleavable quaternary oxychlorides with high magnetic ordering temperatures

Quaternary oxychlorides derived from Ruddlesden–Popper 3d transition metal oxides offer a route to cleavable crystals with bulk antiferromagnetic ordering temperatures reaching at least 550 K. Here, we study the magnetic, optical, and mechanical behavior of Sr 2 FeO 3 Cl, Ca 2 FeO 3 Cl, Ca 3 Fe 2 O 5 Cl 2 , and Sr 3 Fe 2 O 5 Cl 2 . Through optical absorption measurements, we show that these antiferromagnetic semiconductors have optical band gaps of ≈2.1(1) eV. The magnetic ordering symmetries and temperatures were probed by neutron powder diffraction and Mössbauer spectroscopy on polycrystalline samples, demonstrating Néel temperatures (T N ) near room temperature in the single layer Sr 2 FeO 3 Cl (T N ≈ 311 K) and Ca 2 FeO 3 Cl (T N ≈ 360 K), and the double-layer compound Sr 3 Fe 2 O 5 Cl 2 has T N ≈ 545 K. The high-spin moments of Fe 3+ lie within the basal plane and the magnetic structures are compensated within each magnetic layer and characterized by magnetic propagation vectors k = ($\frac{1}{2}$ $\frac{1}{2}$ 0). Magnetization results demonstrate the quasi-2D nature of the magnetism, with a broad maximum in the susceptibility near 2T N for Sr 2 FeO 3 Cl. Scotch tape tests and mechanical exfoliation onto SiO 2 confirm the micaceous nature of these crystals with cleavage down to a single unit cell (two magnetic layers) achieved for Sr 3 Fe 2 O 5 Cl 2 . In conclusion, this paper highlights strong antiferromagnetic interactions, semiconducting band gaps, and cleavability of quaternary Fe-based oxychlorides and motivates future work on crystals and exfoliated flakes of these and related oxyhalide systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Expansion-Driven Self-Magnetization of High-Energy-Density Plasmas

Understanding plasma self-magnetization is one of the fundamental challenges in both laboratory and astrophysical plasmas. Self-magnetization can modify plasma transport properties, altering the dynamical evolution of plasmas. Multiple high-energy-density (HED) experiments have observed the formation of ion-scale magnetic filaments of megagauss strength, though their origin remains debated. Here, in this study, we conduct 2D collisional particle-in-cell (PIC) simulations with a laser ray-tracing module for a fully self-consistent simulation of the plasma ablation, expansion, and magnetization. The simulations use a planar geometry, effectively suppressing the Biermann magnetic fields, to focus on anisotropy-driven instabilities. The laser intensity is varied between 10 13 and 10 14 W/cm 2 , which is relevant to HED and inertial fusion experiments where collisions must be considered. We find that, above a critical intensity, the plasma rapidly self-magnetizes via an expansion-driven Weibel process, producing a plasma beta of 100 (𝛽 = 8⁢𝜋⁢𝑘 𝐵 ⁢𝑛 𝑒 ⁢𝑇 𝑒 /𝐵 2 ) and Hall parameter 𝜔 ce ⁢𝜏 𝑒 >1 within the first few hundred picoseconds. The magnetic field is sufficiently strong to modify plasma heat transport, and simulations with an artificially suppressed magnetic field show noticeably different temperature profiles.

Lezhnin, K. V. [Princeton Plasma Physics Laborator↗
DOE OSTI2024

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗
DOE OSTI2024

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗
DOE OSTI2025

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U↗
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
DOE OSTI2025

Understanding the dynamic nature of plant lipid anabolic and catabolic metabolism is key to sustainable oilseed engineering

Plant-derived oils are essential sources of reduced carbon and various fatty acid (FA) structures for food, biofuels, and the oleochemical industry. Despite extensive efforts, engineering mainstream oilseed crops to produce high levels of industrially valuable unusual FAs (UFAs) remains challenging. This review synthesizes recent advances in the understanding of lipid metabolic networks, emphasizing how species-specific regulation of FA synthesis, activation, and delivery influences triacylglycerol (TAG) assembly to govern the efficiency of UFA accumulation. Key insights reveal that acyl flux through anabolic and catabolic branches of lipid metabolism is tightly controlled by enzyme substrate selectivities, diacylglycerol (DAG) pool compartmentalization, and metabolic context, including lipid remodeling and degradation pathways. Engineering success is often constrained by incompatibilities between UFA biosynthetic enzymes and endogenous host metabolism, leading to flux imbalances, futile cycles, and undesired phenotypes. We highlight emerging strategies to overcome these barriers, such as the use of UFA-selective acyltransferases, coordinated manipulation of DAG source pools, suppression of competing endogenous enzymes, and exploitation of TAG remodeling mechanisms. This integrated synthesis provides a conceptual framework for logic-based engineering of oilseeds with enhanced UFA content by offering new avenues for sustainable biomanufacturing of valuable lipids.

acyltransferase specificity↗
DOE OSTI2020

Terabase Metagenome Sequencing of Grassland Soil Microbiomes

ABSTRACT To enable an in-depth survey of the metabolic potential of complex soil microbiomes, we performed ultra-deep metagenome sequencing, collecting >1 Tb of sequence data from three grassland soils representing different precipitation regimes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Sensing Plant Photosynthesis Using Solar-Induced Chlorophyll Fluorescence: From Chloroplasts to the Globe

Photosynthesis is the fundamental biological process that introduced oxygen into Earth's atmosphere and continues to power life, from the earliest single-celled organisms to entire global ecosystems. Yet, measuring photosynthesis across scales has been challenging because traditional techniques have not transcended scales. The emergence of remote-sensing techniques to measure solar-induced chlorophyll fluorescence (SIF) provides a unique approach to estimate photosynthesis across spatiotemporal scales, representing a new age for optical remote sensing to study photosynthesis and shaping the decades of satellite SIF research. Here, focusing on spatiotemporal scales, we review the mechanisms that drive the relationship between SIF and photosynthesis. Remotely sensed SIF is modulated by biological drivers, environmental drivers, the interaction between biological and environmental drivers, and the viewing geometry. Studying fluorescence at small scales provides the ecophysiological understanding needed to disentangle the biological and environmental drivers of SIF at larger scales. Leveraging progress in satellite SIF, future research should focus on cross-scale mechanistic understanding of the drivers of SIF and using SIF as a metric for plant function beyond photosynthesis.

ecophysiology↗
DOE OSTI2025

Reactivity of the Hydrated Electron

Hydrated electrons are created in virtually every radiation environment and in many photochemical or electrochemical environments where liquid water is present, so their reaction products and reaction rate constants are naturally important in applications. Thanks to the strong optical absorbance of (e - ) aq , these rate constants are easy to measure, and a large database has been accumulated. It is not generally appreciated that no working theory of hydrated electron reaction rates presently exists. We discuss key experimental observations of hydrated electron reactions in the context of recent progress in theoretical and simulation developments toward understanding them, made possible by ever increasing computational power.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CoVVVR: Control Variates & Vegas Variance Reduction

This package is a wrapper over the vegas integration package. The control variate variance reduction method is applied to the function when integrated along with the techniques applied in vegas such as importance sampling. To understand control variates, lets first look at how Monte Carlo works.

Scott, JacobL. [Univ. of Kansas, Lawrence, KS (Uni↗
DOE OSTI2026

Turbulence and Cloudiness in Cumulus-Topped Marine Boundary Layers

Turbulence and cloudiness in cumulus-topped marine boundary layers are studied using data from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site. The analysis includes eight periods of nonprecipitating shallow cumulus clouds, spanning 141 h and encompassing 603 individual clouds. On average, the cumulus had bases at 558 m, were 99 m thick, had a chord length of 500 m, and exhibited an hourly base-layer cloudiness of 12%. Changes in cloud fraction were primarily driven by variations in cloud number not chord length. High-resolution Doppler lidar and cloud radar observations were used to estimate updraft and downdraft mass fluxes in the cumulus base layer under both clear and cloudy regions. Cloudy updrafts contributed only ∼23% of the total updraft mass flux at cloud base, indicating that most upward mass flux originated from clear-air eddies. Updraft strength, rather than updraft fraction, was found to predominantly control both clear and cloudy updraft mass fluxes. Cloud-base cloudiness strongly correlated with cloudy updraft mass flux but showed negligible correlation with clear-air updraft mass flux. Clear-air downdraft mass flux exhibited a strong relationship with the ratio of surface buoyancy to inversion strength. Mesoscale analysis revealed that moist patches had greater cloudiness, updraft mass flux, and vertical velocity variance compared to dry patches. Additionally, mesoscale base-layer cloud fraction was highly and significantly correlated with cloudy updraft mass flux in both dry and moist environments. Results presented herein have implications for cumulus parameterization development along with climatological and model evaluation studies conducted at the ENA site.

cumulus clouds↗
DOE OSTI2024

Enhancement of harmonic generation by an intense driving laser with high-order waveguide modes in a high-pressure gas-filled hollow waveguide

High-order harmonics have been widely used as reliable tabletop coherent radiation sources recently, but their applications have often been limited by the available pulse energy. Here, we report that by using an overdriven intense laser in a long waveguide with high-pressure gas, phase matching can be achieved in three distinct “regimes”. In the third regime, favorable phase matching is achieved at near-axis positions to enhance harmonic yields. Our results are supported by a full theoretical analysis, and we demonstrate that coupling of the driving laser with the high-order waveguide modes (instead of the fundamental mode used in most prior experiments) is responsible for achieving phase matching. Furthermore, we establish that this phase matching (and harmonic enhancement) is robust, and a scaling relation is derived for the necessary waveguide and gas parameters, allowing our predictions to be tested immediately in any laboratory today.

Li, Baochang [Nanjing University of Science and Te↗
DOE OSTI2025

Hearing carrier-envelope offset frequency and phase in air with a microphone

Attosecond science and frequency metrology rely on the precise measurement and control of the laser pulse waveform, a feat traditionally achieved using optoelectronic techniques. In this study, we conducted a laser-induced acoustic experiment in air ionized by carrier-envelope phase (CEP)-stabilized sub-4 fs pulses. Our results reveal that the acoustic signal exhibits CEP dependence in few-cycle pulses, primarily through amplitude modulation from laser-driven ionization. This optoacoustic phenomenon is, to the best of our knowledge, a novel phenomenon that enables not only the measurement of the carrier-envelope offset frequency but also the direct characterization of the waveform of optical pulses through a microphone. Our study highlights the potential of laser-induced acoustic waves for advancing ultrafast science.

Han, Meng [Kansas State University, Manhattan, KS ↗
DOE OSTI2025

Array-Based Seismic Measurements of OSIRIS-REx’s Re-Entry

The return home of the OSIRIS-REx spacecraft in September 2023 marked only the fifth time that an artificial object entered the Earth’s atmosphere at interplanetary velocities. Although rare, such events serve as valuable analogs for natural meteoroid re-entries; enabling study of hypersonic dynamics, shock wave generation, and acoustic-to-seismic coupling. Here, in this study, we report on the signatures recorded by a dense (100 m scale) 11-station array located almost directly underneath the capsule’s point of peak atmospheric heating in northern Nevada. Seismic data are presented, which allow inferences to be made about the shape of the shock wave’s footprint on the surface, the capsule’s trajectory, and its flight parameters.

58 GEOSCIENCES↗