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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Technology-enabled Airborne Spacing and Merging

Over the last several decades, advances in airborne and groundside technologies have allowed the Air Traffic Service Provider (ATSP) to give safer and more efficient service, reduce workload and frequency congestion, and help accommodate a critically escalating traffic volume. These new technologies have included advanced radar displays, and data and communication automation to name a few. In step with such advances, NASA Langley is developing a precision spacing concept designed to increase runway throughput by enabling the flight crews to manage their inter-arrival spacing from TRACON entry to the runway threshold. This concept is being developed as part of NASA s Distributed Air/Ground Traffic Management (DAG-TM) project under the Advanced Air Transportation Technologies Program. Precision spacing is enabled by Automatic Dependent Surveillance-Broadcast (ADS-B), which provides air-to-air data exchange including position and velocity reports; real-time wind information and other necessary data. On the flight deck, a research prototype system called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR) processes this information and provides speed guidance to the flight crew to achieve the desired inter-arrival spacing. AMSTAR is designed to support current ATC operations, provide operationally acceptable system-wide increases in approach spacing performance and increase runway throughput through system stability, predictability and precision spacing. This paper describes problems and costs associated with an imprecise arrival flow. It also discusses methods by which Air Traffic Controllers achieve and maintain an optimum interarrival interval, and explores means by which AMSTAR can assist in this pursuit. AMSTAR is an extension of NASA s previous work on in-trail spacing that was successfully demonstrated in a flight evaluation at Chicago O Hare International Airport in September 2002. In addition to providing for precision inter-arrival spacing, AMSTAR provides speed guidance for aircraft on converging routes to safely and smoothly merge onto a common approach. Much consideration has been given to working with operational conditions such as imperfect ADS-B data, wind prediction errors, changing winds, differing aircraft types and wake vortex separation requirements. A series of Monte Carlo simulations are planned for the spring and summer of 2004 at NASA Langley to further study the system behavior and performance under more operationally extreme and varying conditions. This will coincide with a human-in-the-loop study to investigate the flight crew interface, workload and acceptability.

Hull, James↗
NASA NTRS2010

Three-Dimensional Morphology of a Coronal Prominence Cavity

We present a three-dimensional density model of coronal prominence cavities, and a morphological fit that has been tightly constrained by a uniquely well-observed cavity. Observations were obtained as part of an International Heliophysical Year campaign by instruments from a variety of space- and ground-based observatories, spanning wavelengths from radio to soft-X-ray to integrated white light. From these data it is clear that the prominence cavity is the limb manifestation of a longitudinally-extended polar-crown filament channel, and that the cavity is a region of low density relative to the surrounding corona. As a first step towards quantifying density and temperature from campaign spectroscopic data, we establish the three-dimensional morphology of the cavity. This is critical for taking line-of-sight projection effects into account, since cavities are not localized in the plane of the sky and the corona is optically thin. We have augmented a global coronal streamer model to include a tunnel-like cavity with elliptical cross-section and a Gaussian variation of height along the tunnel length. We have developed a semi-automated routine that fits ellipses to cross-sections of the cavity as it rotates past the solar limb, and have applied it to Extreme Ultraviolet Imager (EUVI) observations from the two Solar Terrestrial Relations Observatory (STEREO) spacecraft. This defines the morphological parameters of our model, from which we reproduce forward-modeled cavity observables. We find that cavity morphology and orientation, in combination with the viewpoints of the observing spacecraft, explains the observed variation in cavity visibility for the east vs. west limbs

Gibson, S. E.↗
NASA NTRS2022

Reevaluating How Charged Particles Cause Space Weathering on Airless Bodies

Many experiments have attempted to simulate how charged particles cause space weathering on airless bodies throughout the Solar System. Researchers have typically applied these experimental results by assuming that high laboratory fluxes cause the same effects as do the significantly lower fluxes found in nature. New work, however, shows that this assumption may often be invalid. In particular, experiments using charged particle fluences cm−2 without adequate steps to neutralize the targets risk causing dielectric breakdown, or “sparking”—a process that may affect some airless bodies. Consequently, it is critical to understand the laboratory conditions under which breakdown occurs, both to ensure that experiments properly simulate the effects of charged particles and to study the possibility that dielectric breakdown can, in some locations, contribute to space weathering.

A P Jordan↗
DOE OSTI2020

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗
NASA NTRS2005

Utilization of the Building-Block Approach in Structural Mechanics Research

In the last 20 years NASA has worked in collaboration with industry to develop enabling technologies needed to make aircraft safer and more affordable, extend their lifetime, improve their reliability, better understand their behavior, and reduce their weight. To support these efforts, research programs starting with ideas and culminating in full-scale structural testing were conducted at the NASA Langley Research Center. Each program contained development efforts that (a) started with selecting the material system and manufacturing approach; (b) moved on to experimentation and analysis of small samples to characterize the system and quantify behavior in the presence of defects like damage and imperfections; (c) progressed on to examining larger structures to examine buckling behavior, combined loadings, and built-up structures; and (d) finally moved to complicated subcomponents and full-scale components. Each step along the way was supported by detailed analysis, including tool development, to prove that the behavior of these structures was well-understood and predictable. This approach for developing technology became known as the "building-block" approach. In the Advanced Composites Technology Program and the High Speed Research Program the building-block approach was used to develop a true understanding of the response of the structures involved through experimentation and analysis. The philosophy that if the structural response couldn't be accurately predicted, it wasn't really understood, was critical to the progression of these programs. To this end, analytical techniques including closed-form and finite elements were employed and experimentation used to verify assumptions at each step along the way. This paper presents a discussion of the utilization of the building-block approach described previously in structural mechanics research and development programs at NASA Langley Research Center. Specific examples that illustrate the use of this approach are included from recent research and development programs for both subsonic and supersonic transports.

Rouse, Marshall↗
DOE OSTI2024

The National Criticality Experiments Research Center: Capability Expansion and Experiments in the Last Three Years

The National Criticality Experiments Research Center (NCERC) is a general purpose criticality experiments facility located inside the Device Assembly Facility (DAF) at the Nevada National Security Site (NNSS). Critical experiments containing any special nuclear material, any enrich ment/separation, most physical forms, and any configuration are possible within the constraints of the defined safety basis. NCERC draws upon physical assets and experimental knowledge to solve some of the most difficult problems with respect to criticality safety, reactor physics, and reactor kinetics. In terms of physical assets, NCERC houses hundreds of kilograms of special nuclear material with a majority consisting of highly enriched uranium (HEU) and weapons grade plutonium (WGPu). NCERC is home to four critical assembly machines: Comet, Planet, Flattop, and Godiva IV. To support various derivative diagnostics on fissioning systems, NCERC houses a count room to measure irradiated samples and dosimeters. This paper will step through each of these capabilities explaining recently completed work and upgrades.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

APSO-enhanced algebraic derivative estimation approach for real-time traffic flow prediction on critical road sections during wildfire evacuation

In rapid-onset disaster scenarios such as wildfires, evacuation traffic often significantly deviates from historical patterns, rendering conventional data-driven forecasting methods less effective. To address this challenge, we propose an improved algebraic derivative estimation (ADE) incorporating particle swarm optimization (PSO) for real-time traffic flow prediction. Our approach dynamically adjusts the ADE prediction time window at each step by minimizing a cost function based on the mean and variance of accumulated forecasting errors within the window, thereby balancing bias and variability. We evaluate the method using traffic data from the January 2025 California wildfires, focusing on key road segments critical for large-scale evacuations. The results demonstrate that our approach surpasses established machine learning and deep learning models—XGBoost, LSTM, and GRU—in predictive accuracy and maintains high computational efficiency. Notably, the proposed method eliminates the need for offline model training. Moreover, rapid PSO-based tuning enables real-time deployment, which provides a crucial advantage in scenarios where evacuation timings and road closures change dynamically. In conclusion, these findings highlight the benefits of the PSO-enhanced ADE framework for emergency traffic management, where rapid, data-sparse forecasts are essential for effective evacuation planning.

Algebraic derivative estimation↗
NASA NTRS2013

A Technology Development Roadmap for a Near-Term Probe-Class X-ray Astrophysics Mission

This document presents a roadmap, including proposed budget and schedule, for maturing the instrumentation needed for an X-ray astrophysics Probe-class mission. The Physics of the Cosmos (PCOS) Program Office was directed to create this roadmap following the December 2012 NASA Astrophysics Implementation Plan (AIP). Definition of this mission is called for in the AIP, with the possibility of selection in 2015 for a start in 2017. The overall mission capabilities and instrument performance requirements were defined in the 2010 Astronomy and Astrophysics Decadal Survey report, New Worlds, New Horizons in Astronomy and Astrophysics (NWNH), in connection with the highly ranked International X-ray Observatory (IXO). In NWNH, recommendations were provided regarding the size of, and instrumentation needed by, the next large X-ray observatory. Specifically, the key instrumental capability would be an X-ray calorimeter spectrometer at the focus of a large mirror with angular resolution of 10 arc seconds (arcsec) or better. If possible, a grating spectrometer should also be incorporated into the instrument complement. In response to these recommendations, four instrumentation technologies are included in this roadmap. Three of these are critical for an X-ray mission designed to address NWNH questions: segmented X-ray mirrors, transition edge sensor calorimeters, and gratings. Two approaches are described for gratings, which represent the least mature technology and thus most in need of a parallel path for risk reduction. Also, while current CCD detectors would likely meet the mission needs for grating spectrum readout, specific improvements are included as an additional approach for achieving the grating system effective area requirement. The technical steps needed for these technologies to attain technology readiness levels (TRL) of 5 and 6 are described, as well as desirable modest risk reduction steps beyond TRL-6. All of the technology development efforts are currently funded through the NASA Physics of the Cosmos (PCOS) Strategic Astrophysics Technology (SAT) program; some through the end of FY13, others though FY14. These technology needs are those identified as critical for a near-term mission and briefly described in the 2012 NASA X-ray Mission Concepts Study. This Technology Development Roadmap (TDR) provides a more complete description of each, updates the status, and describes the steps to mature them. For each technology, a roadmap is presented for attaining TRL-6 by 2020 at the latest, and 2018 for most. The funding required for each technology to attain TRL-5 and TRL-6 is presented and justified through a description of the steps needing completion. The total funding required for these technologies to reach TRL-6 is relatively modest, and is consistent with the planned PCOS SAT funding over the next several years. The approximate annual cost through 2018 is $8M. The total cost for all technologies to be matured is $62M (including funding already awarded for FY13 and FY14). This can be contrasted to the $180M recommended by NWNH for technology development for IXO, primarily for the maturation of the mirror technology. The technology described in Section 3 of this document is exclusively that needed for a near-term Probe-class mission, to start in 2017, or for a mission that can be recommended by the next Decadal survey committee for an immediate start. It is important to note that there are other critical X-ray instrumentation technologies under development that are less mature than the ones discussed here, but are essential for a major X-ray mission that might start in the late 2020s. These technologies, described briefly in Section 4, are more appropriately funded through the Astronomy and Physics Research and Analysis (APRA) program.

Development↗
NASA NTRS1993

(abstract) Galileo Optical Link Takes a Step Towards Deep-Space Optical Communications

The Galileo Optical Experiment (GOPEX) is the first in a series of JPL optical communications experiments that are planned to 1) demonstrate the application of critical concepts, subsystems, and components to optical communications technology, 2) validate optical communications performance models, and 3) improve the conceptual design of a deep-space and near-Earth optical communications network. Such a network is envisioned to be global in extent, and will require construction of optical stations on several continents. Industry can play a role in the development of this new breaking technology by assisting in addressing some of the current technology challenges.

optical communications experiment space communicat↗
DOE OSTI2025

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗
DOE OSTI2020

Mechanistic understanding of catalytic conversion of ethanol to 1-butene over 2D-pillared MFI zeolite

Ethanol is an important C2 platform molecule for producing value-added chemicals and distillate hydrocarbon fuels (e.g., jet and diesel). Among these, catalytic upgrading of ethanol to butenes can generate valuable commodity chemicals (e.g., 1-butene) and provide C4 olefin intermediates that can be further upgraded to jet/diesel fuels. 2D zeolites offer hierarchical mesoporous structures, leading to improved mass transport and reduced diffusion length, which can help to address the coking challenges faced by ethanol conversion to hydrocarbons over 3D zeolites. In this study, we investigate the acid-catalyzed conversion of ethanol to 1-butene over the Brønsted acid sites (BAS) in 2D-pillared MFI zeolite (2D-PMFI) using ab initio molecular dynamics (AIMD) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and calorimetric measurements. A detailed thermodynamic analysis, using quasi-harmonic approximation (QHA), on the Gibbs free energy pathway of ethanol conversion shows that the consideration of entropy is critical to accurately capture the detailed thermodynamic profiles. The formation of bulky ethoxy-ethene complex is found to be a potential rate-determining step (RDS), proceeding via stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through a careful control of number of BAS and operating temperatures. The accuracy of computational model is confirmed through the comparison of calculated vibrational density of states (VDOS) against the experimental DRIFTS measurements. Overall, our study provides mechanistic insights into ethanol upgrading over the 2D-PMFI and shows the importance of evaluating entropic effects in such confined system.

Ethanol conversion, 2D-pillared zeolite, MFI, Anha↗
DOE OSTI2021

Green’s functions on a renormalized lattice: An improved method for the integer quantum Hall transition

Highlights: • Speed up of numerical calculations by exact renormalization group steps. • Practical approach to handle delicate scaling analysis. • Absence of evidence to prefer marginal corrections over power-law corrections. We introduce a performance-optimized method to simulate localization problems on bipartite tight-binding lattices. It combines an exact renormalization group step to reduce the sparseness of the original problem with the recursive Green’s function method. We apply this framework to investigate the critical behavior of the integer quantum Hall transition of a tight-binding Hamiltonian defined on a simple square lattice. In addition, we employ an improved scaling analysis that includes two irrelevant exponents to characterize the shift of the critical energy as well as the corrections to the dimensionless Lyapunov exponent. We compare our findings with the results of a conventional implementation of the recursive Green’s function method, and we put them into broader perspective in view of recent development in this field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Risk assessment of wellbore leakage during underground hydrogen storage

The expansion of renewable energy sources would require large-scale energy storage options to overcome the intermittent nature of these sources. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs offers a scalable and practical energy storage solution. These reservoirs are chosen for their availability and large capacity, but the unique properties of hydrogen raise concerns about potential leakage pathways, particularly through wellbores. In this study, we develop and apply, for the first time, reduced-order models (ROMs) specifically designed for efficient leakage risk prediction in UHS systems operating in depleted hydrocarbon reservoirs. Using 3,000 high-fidelity simulation scenarios, we examine the influence of 11 key parameters, including reservoir and aquifer depths, wellbore permeability and porosity, initial saturations of water, oil and gas fractions (hydrogen, light, intermediate, and heavy hydrocarbons), reservoir pressure multiplier, and the aquifer-to-reservoir volume ratio, to simulate leakage behavior over a 1,000-year timescale. We train ROMs using a two-step classification-regression approach, achieving R 2 values exceeding 99 % across all targets. These ROMs effectively capture the leakage evolution and identify critical controls of leakage, guiding the design of mitigation strategies. Results indicate that gas leakage occurs in about 27 % of scenarios as early as five years post-operation, reaching volumes of up to 106 ft3. Oil leakage is less frequent (~17 %) and typically begins decades later. Our findings also show that hydrogen often migrates first, owing to its smaller molecular size and higher buoyancy, followed by heavier hydrocarbons. Over time, these heavier components contribute significantly to the total leaked volume, reinforcing the need for targeted monitoring and remediation strategies. Our analysis highlights that deeper storage reservoirs, shallower aquifers, and low-permeability wellbores significantly reduce leakage risks. In conclusion, this work offers a robust framework for risk-informed UHS deployment, supporting energy security through reliable large-scale hydrogen storage while safeguarding environmental integrity.

08 HYDROGEN↗
DOE OSTI2020

Second Coordination Sphere Effects in an Evolved Ru Complex Based on Highly Adaptable Ligand Results in Rapid Water Oxidation Catalysis

A new Ru complex containing the deprotonated 2,2':6',2"-terpyridine-6,6"-diphosphonic acid (H 4 tPa) and pyridine (py) of general formula [Ru II (H 3 tPa-κ-N 3 O)(py) 2 ] + , 2 + , has been prepared and thoroughly characterized by means of spectroscopic and electrochemical techniques, X-ray diffraction analysis, and density functional theory (DFT) calculations. Complex 2 + presents a dynamic behavior in the solution that involves the synchronous coordination and the decoordination of the dangling phosphonic groups of the tPa 4– ligand. Yet, at oxidation state IV, complex 2 + becomes seven coordinated with the two phosphonic groups now bonded to the metal center. Further, at this oxidation state at neutral and basic pH, the Ru complex undergoes the coordination of an exogenous OH – group from the solvent that leads to an intramolecular aromatic O atom insertion into the CH bond of one of the pyridyl groups, forming the corresponding phenoxo-phosphonate Ru complex [Ru III (tPaO-κ-N 2 O P O C )(py) 2 ] 2– , 4 2– , where tPaO 5– is the 3-(hydroxo-[2,2':6',2"-terpyridine]-6,6"-diyl)bis(phosphonate) ligand. This new in situ generated Ru complex, 4 2– , has been isolated and spectroscopically and electrochemically characterized. In addition, a crystal structure has been also obtained using single-crystal X-ray diffraction techniques. Complex 4 2– turns out to be an exceptional water oxidation catalyst achieving record maximum turnover frequencies (TOF max ) on the order of 16 000 s –1 . A mechanistic analysis complemented with DFT calculations has further been carried out, showing the critical role of intramolecular second coordination sphere effects exerted by the phosphonate groups in lowering the activation energy at the rate-determining step.

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

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Robustness of the Galactic Center excess morphology against masking

The Galactic Center excess (GCE) remains an enduring mystery, with leading explanations being annihilating dark matter or an unresolved population of millisecond pulsars. Analyzing the morphology of the GCE provides critical clues to identify its exact origin. We investigate the robustness of the inferred GCE morphology against the effects of masking, an important step in the analysis where the gamma-ray emission from point sources and the galactic disk are excluded. Using different masks constructed from Fermi point source catalogs and a wavelet method, we find that the GCE morphology, particularly its ellipticity and cuspiness, is relatively independent of the choice of mask for energies above 2–3 GeV. The GCE morphology systematically favors an approximately spherical shape, as expected for dark matter annihilation. Compared to various stellar bulge profiles, a spherical dark matter annihilation profile better fits the data across different masks and galactic diffuse emission backgrounds, except for the stellar bulge profile which provides a similar fit to the data. Modeling the GCE with two components, one from dark matter annihilation and one tracing the Coleman bulge, we find this two-component model outperforms any single component or combinations of dark matter annihilation and other stellar bulge profiles. Uncertainty remains about the exact fraction contributed by each component across different background models and masks. Furthermore, when the Coleman bulge dominates, its corresponding spectrum lacks characteristics typically associated with millisecond pulsars, suggesting that it mostly models the emission from other sources instead of the GCE that is still present and spherically symmetric.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Intrinsic even-odd thickness-driven anomalous Hall effect in epitaxial MnBi2⁢Te4 thin films

We demonstrate precise control of magnetism in MnBi2⁢Te4 thin films through careful synthesis by molecular beam epitaxy, achieving minimal defects and accurate layer thickness control. By optimizing Mn-Bi-Te ratios and growth temperatures, we minimize detrimental self-doping effects and accurately target integer-layer films. X-ray diffraction and reflectivity provide quantitative measures of film quality and thickness. When these macroscale probes of structure and thickness are integrated with magnetotransport measurements, a striking even-odd layer dependence of the anomalous Hall effect is revealed. Odd-layer films exhibit a large hysteresis up to the Néel temperature (∼25K), consistent with noncompensated antiferromagnetism, while even-layer films show minimal response, as expected for an antiferromagnet. The sign of the anomalous Hall effect exhibits a sign reversal for intrinsic magnetism versus magnetism associated with defects. This work identifies critical factors for inducing pure, noncompensated ferromagnetism and reveals the characteristics of the intrinsic anomalous Hall effect in MnBi2⁢Te4, which together is a step toward realizing the zero-field quantum anomalous Hall effect in topological materials.

Mallick, Deb [ORNL] (ORCID:000900005806411X)↗
DOE OSTI2023

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

17 WIND ENERGY↗