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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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11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Higher‐Order Gravity Waves and Traveling Ionospheric Disturbances From the Polar Vortex Jet on 11–15 January 2016: Modeling With HIAMCM‐SAMI3 and Comparison With Observations in the Thermosphere and Ionosphere

Abstract In Vadas et al. (2024, https://doi.org/10.1029/2024ja032521 ), we modeled the atmospheric gravity waves (GWs) during 11–14 January 2016 using the HIAMCM, and found that the polar vortex jet generates medium to large‐scale, higher‐order GWs in the thermosphere. In this paper, we model the traveling ionospheric disturbances (TIDs) generated by these GWs using the HIAMCM‐SAMI3 and compare with ionospheric observations from ground‐based Global Navigation Satellite System (GNSS) receivers, Incoherent Scatter Radars (ISR) and the Super Dual Auroral Radar Network (SuperDARN). We find that medium to large‐scale TIDs are generated worldwide by the higher‐order GWs from this event. Many of the TIDs over Europe and Asia have concentric ring/arc‐like structure, and most of those over North/South America have planar wave structure and occur during the daytime. Those over North/South America propagate southward and are generated by higher‐order GWs from Europe/Asia which propagate over the Arctic. These latter TIDs can be misidentified as arising from geomagnetic forcing. We find that the higher‐order GWs that propagate to Africa and Brazil from Europe may aid in the formation of equatorial plasma bubbles (EPBs) there. We find that the simulated GWs, TIDs and EPBs agree with EISCAT, PFISR, GNSS, and SuperDARN measurements. We find that the higher‐order GWs are concentrated at N at 200 km, in agreement with GOCE and CHAMP data. Thus the polar vortex jet is important for generating TIDs in the northern winter ionosphere via multi‐step vertical coupling through GWs.

Vadas, Sharon L. [Northwest Research Associates Bo↗
DOE OSTI2025

Templates for Risk Informed Assurance with Curvature Embeddings (TRACE)

We investigate recovery of geometric structure from networks embedded in manifolds with spatially varying curvature, extending the constant-curvature framework of Lubold et al. (2023). Our work supports cascade risk assessment in critical infrastructure through the Templates for Risk-informed Assurance with Curvature Embeddings (TRACE) framework. Simulations on a bi-modal Gaussian surface show that constant-curvature methods yield weighted averages shaped by clique patterns, while hierarchical clustering identifies distinct regimes. Localized estimation, however, reveals boundary contamination in transitional regions. To address heterogeneity, we develop distance metrics for graphs with edge and node features, proving their metric validity, and validate them via deterministic graph generation from canonical tilings. We further propose a diffusion-based anomaly detection approach that treats networks as glued manifolds, using curvature discontinuities to detect structural anomalies. Employing the carré-du-champ operator and scalar curvature, we achieve robust anomaly discrimination, demonstrated on the Singapore Water Treatment (SWaT) dataset with joint network-traffic and sensor features. Integration with TRACE reveals how curvature shapes cascade dynamics: positive curvature impedes, while negative curvature accelerates propagation. This geometric perspective provides interpretable risk metrics and visualization tools for critical infrastructure managers. While full validation remains ongoing, our contributions establish a rigorous foundation for geometric analysis of network resilience and cascade vulnerability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deconstruction of the Anisotropic Magnetic Interactions from Spin‐Entangled Optical Excitations in van der Waals Antiferromagnets

Magneto-optical excitations in antiferromagnetic d systems can originate from a multiplicity of light-spin and spin-spin interactions, as the light and spin degrees of freedom can be entangled. This is exemplified in van der Waals systems with attendant strong anisotropy between in-plane and out-of-plane directions, such as MnPS 3 and NiPS 3 films studied here. The rich interplay between the magnetic ordering and sub-bandgap optical transitions poses a challenge to resolve the mechanisms driving spin-entangled optical transitions, as well as the single-particle bandgap itself. Here, a high-fidelity ab initio theory is applied to find a realistic estimation of the bandgap by elucidating the atom- and orbital-resolved contributions to the fundamental sub-bands. It is further demonstrated that the spin-entangled excitations, observable as photoluminescence and absorption resonances, originate from an on-site spin-flip transition confined to a magnetic atom (Mn or Ni). The evolution of the spin-flip transition in a magnetic field is used to deduce the effective exchange coupling and anisotropy constants.

2D materials↗
DOE OSTI2026

Distinct magneto-optical response of Frenkel and Wannier excitons in CrSBr

Excitons in recently discovered two-dimensional magnetic semiconductors have emerged as a promising vehicle for optoelectronic and spin-photonic applications. To exploit novel possibilities magnetic degrees of freedom offer, insight into the interplay of magnetism, lattice and optical excitations becomes essential. We consider Chromium Sulphur Bromide, which has two kinds of excitons, X B at 1.8 eV and X A at 1.38 eV. Here we show, through a combination of many body perturbation theory and experiment, that X B is an order of magnitude more sensitive to magnetic and lattice perturbations than X A . We trace the difference to the latter being localised (Frenkel-like), while the former is delocalised (Wannier-Mott-like) – a coexistence rarely seen in two-dimensional materials. This finding is supported by the strong temperature and magnetic field (up to 85 Tesla) dependent shifts in optical response for X B (much smaller for X A ), and we show it is related to X B ’s tendency for delocalisation (in-plane and out-of-plane) and enhanced coupling with Ag phonon modes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Excitonic Anisotropy in Single‐Crystalline 2D Silver Phenylchalcogenides

2D materials exhibiting in‐plane anisotropy enable new applications in directional energy transport and polarized optical response. Silver phenylchalcogenides (AgEPh) – including mithrene (AgSePh), tethrene (AgTePh), and thiorene (AgSPh) – represent an exciting new addition to this family, with optical response spanning the visible to near‐UV. Here, excitonic anisotropy is predicted and characterized in this family of materials using a combination of ab initio theory and optical micro‐spectroscopy of single‐crystalline flakes. Using density functional theory and GW with the Bethe–Salpeter equation calculations, it is revealed that all AgEPh compounds exhibit anisotropic electronic band structure and host multiple delocalized excitons with in‐plane anisotropy. Room‐temperature polarization‐resolved optical micro‐spectroscopy shows that orthogonally polarized excitons with similar energy lead to nearly isotropic absorption in AgSPh, whereas energy separation between excitonic resonances in AgSePh and AgTePh leads to strong absorption and emission anisotropy. Cryogenic reflectance micro‐spectroscopy further reveals exciton fine structure in AgSePh, reconciling the discrepancies between room‐temperature experiments and theoretical predictions. Finally, it is demonstrated that the optical response of thicker AgEPh crystals is influenced by photonic effects arising from finite crystal size. Overall, this work advances the understanding of the relationship between anisotropic structure, composition, and excitonic properties in AgEPh, providing a foundation for technological integration.

2D↗
DOE OSTI2026

Electrostatic gate-controlled quantum interference in a high-mobility two-dimensional electron gas at the (La 0.3 ⁢Sr 0.7 )(Al 0.65 ⁢Ta 0.35 )O 3 /SrTiO 3 interface

Here, we report quantum oscillations in magnetoresistance that are periodic in magnetic field (𝐵), observed at the interface between (La 0.3 ⁢Sr 0.7 )(Al 0.65 ⁢Ta 0.35 )O 3 and SrTiO 3 . Unlike Shubnikov–de Haas oscillations, which appear at magnetic fields > 7 T and diminish quickly as the temperature rises, these 𝐵-periodic oscillations emerge at low fields and persist up to 10 K. Their amplitude decays exponentially with both temperature and field, specifying dephasing of quantum interference. Increasing the carrier density through electrostatic gating results in a systematic reduction in both the amplitude and frequency of the oscillations, with complete suppression beyond a certain gate voltage. We attribute these oscillations to the Altshuler-Aronov-Spivak effect, likely arising from naturally formed closed-loop paths due to the interconnected quasi-one-dimensional conduction channels along SrTiO 3 domain walls. The relatively long phase coherence length (≃ 1.8 µ⁢m at 0.1 K), estimated from the oscillation amplitude, highlights the potential of complex oxide interfaces as a promising platform for exploring quantum interference effects and advancing device concepts in quantum technologies, such as mesoscopic interferometers and quantum sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go waves,” these instabilities are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system, referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment, the MegaVanderTest (MVT), leveraged a heterogeneous fleet of 100 longitudinally controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this article. The MegaController is a hierarchical control architecture that consists of two main layers. The upper layer is called the Speed Planner and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock onboard sensors. The Speed Planner ingests live data feeds provided by third parties as well as data from our own control vehicles and uses both to perform the speed assignment. The architecture of the Speed Planner allows for the modular use of standard control techniques, such as optimal control, model predictive control (MPC), kernel methods, and others. The architecture of the local controller allows for the flexible implementation of local controllers. Corresponding techniques include deep reinforcement learning (RL), MPC, and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers or only some. Likewise, control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars to electronic selection of adaptive cruise control (ACC) setpoints in others. The proposed architecture technically allows for the combination of all possible settings proposed previously, that is {Speed Planner algorithms} × {local Vehicle Controller algorithms} × {full or partial sensing} × {torque or speed control}. As a result, most configurations were tested throughout the ramp up to the MegaVandertest (MVT).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

FunDiff: diffusion models over function spaces for physics-informed generative modeling

Recent advances in generative modeling-particularly diffusion models and flow matching-have been widely used for synthesizing discrete data such as images and videos. However, adapting these models to physical applications remains challenging, as the quantities of interest are continuous functions governed by complex physical laws. To address this, we introduce FunDiff, an efficient and robust framework for generative modeling in function spaces. FunDiff combines a latent diffusion process with a function autoencoder architecture to handle input functions with varying discretizations, generates continuous functions that can be evaluated at arbitrary locations, and seamlessly incorporate physical priors. These priors are enforced through architectural constraints or physics-informed loss functions, ensuring that generated samples satisfy fundamental physical laws. We theoretically establish minimax optimality guarantees for density estimation in function spaces, demonstrating that diffusion-based estimators achieve optimal convergence rates under suitable regularity conditions. We further demonstrate the practical effectiveness of FunDiff across diverse applications in fluid dynamics and solid mechanics. Empirical results indicate that our method can generate physically consistent samples with high fidelity to the target distribution, and exhibit robustness to noisy and low-resolution data.

Wang, Sifan [Yale University, New Haven, CT (Unite↗
DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Extremely Durable Concrete using Methane Decarbonization Nanofiber Co-products with Hydrogen

This project successfully developed a scalable, low-cost co-production process for hydrogen (H₂) and carbon nanofibers (CNFs) using methane through catalytic chemical vapor deposition (CVD). CNFs are high-value materials with exceptional mechanical, electrical, and chemical properties, while hydrogen is a critical clean energy resource. By leveraging vapor deposition to create highly dispersed metal catalysts, this work addressed the dual challenge of producing low-cost hydrogen and enhancing the durability of concrete using co-produced CNFs. Unlike prior approaches, which required separating the carbon product from the catalyst, this innovative method integrated the carbon product, catalyst, and silica support as a crack-bridging additive for Portland cement. This novel application aimed to advance the performance of high-performance concrete (HPC) by improving its flexural toughness, durability, and resistance to environmental degradation.

08 HYDROGEN↗
DOE OSTI2025

Modular Processing of Flare Gas for Carbon Nanoproducts

This project demonstrated the technical viability and economic promise of a modular system for converting flared natural gas into valuable carbon nanoproducts (CNPs) through catalytic chemical vapor deposition (CVD). All major project milestones were successfully completed, including reactor design and commissioning, catalyst development, process optimization, technoeconomic analysis, and application testing in concrete systems. The overarching goal was to create a scalable, field-deployable process that valorizes stranded methane by producing high-value carbon materials for use in cementitious composites. At the lab scale, the team designed and built a fluidized bed reactor optimized for use with silica fume-supported nickel catalysts synthesized via atomic layer deposition (ALD). A statistically designed sintering study enabled precise tuning of nickel nanoparticle size, identifying the influence of oxygen partial pressure, time, and temperature on catalyst morphology and performance. These insights allowed the team to target catalyst conditions that maximize carbon nanofilament growth. Subsequent CVD experiments achieved up to 31.8 wt% carbon deposition under optimized conditions, with TEM confirming the presence of nanofilament structures and sustained hydrogen evolution during reaction. Reactor upgrades and empirical fluidization studies supported the development of reliable, repeatable experimental protocols. The modular pilot-scale skid reactor was fully constructed, instrumented, and commissioned. Capable of operating at 675–800°C and pressures up to 290 psig, the system was designed for continuous operation at a carbon production rate of 1 kg/hr. Initial demonstration runs confirmed solids handling, thermal control, and system leak-tightness, although a critical reactor component (the downfeed tube) was inadvertently omitted during final assembly. This omission limited gas–solid contact and prevented meaningful carbon deposition during pilot-scale CVD runs. Nonetheless, the system operated safely under design conditions, and the root cause of performance limitations was clearly identified. Complementary work on UHPC formulations demonstrated that small additions of carbon nanoproducts, including those derived from flare gas, can significantly enhance mechanical performance while preserving workability. A comprehensive study of CNF dispersion techniques and mix design optimization led to a clear protocol for integrating these nanomaterials into concrete. Incorporation of CNPs improved flexural toughness and reduced porosity, supporting their use in high-performance infrastructure applications. A technoeconomic analysis (TEA) confirmed that this process can produce CNP-loaded catalyst material at a levelized cost below $\$$7/kg across a range of catalyst loadings and reaction yields. With estimated market values for the carbon composite product ranging from $\$$14 to over $\$$60/kg, and the ability to blend CNPs into concrete at sub-percent levels with less than 10% added cost, the system presents a compelling economic case. While additional engineering work is needed to optimize fluidization and heat transfer at scale, this project establishes a strong foundation for commercial development. The process is not only technically sound but also economically promising, representing a viable pathway for flare gas mitigation through modular carbon nanomaterial production.

03 NATURAL GAS↗