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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimizing HAARP Beam Pattern for Generation of Strong F‐Region Field‐Aligned Irregularities

Field-aligned irregularities (FAIs) are the signatures of plasma turbulence and convection in the mid- and high-latitude F-region ionosphere, and also provide coherent backscatter targets for HF radars. To serve irregularity generation and characterization studies, we conducted experiments at the High-frequency Active Auroral Research Program (HAARP) in August 2023 with the goal of identifying the optimal HAARP beam pattern for reliable generation of intense FAIs over a large geographic region. The HAARP beam patterns we tested were the commonly-used narrow beam, also known as L0, as well as the wider L1 and L2 “twisted” beam patterns. The size and intensity of the FAI region generated by each HAARP beam pattern was quantified using the Kodiak Island Super Dual Auroral Radar Network (SuperDARN) radar. Stimulated electromagnetic emissions (SEE) from heater wave-FAI scattering were also recorded using a receiver located near HAARP. The L1 beam pattern was found to produce the strongest SuperDARN backscatter over the largest region. Although the heater frequency was intended to be tuned a few hundred kHz below the F-region critical frequency (foF2) during each experiment, difficulty in estimating foF2 during the campaign likely resulted in HAARP heating at significantly different frequency ranges around foF2 during each experiment. Although this additional free parameter complicated data analysis for this study, the SuperDARN and SEE measurements have led to further inquiry into the role heater frequency plays in the artificial generation of FAIs.

58 GEOSCIENCES↗
DOE OSTI2025

Efficient on-chip terahertz generation and detection with GaN photoconductive emitters

Photoconductive emitters for terahertz generation hold promise for highly efficient down-conversion of optical photons because it is not constrained by the Manley-Rowe relation. Existing terahertz photoconductive devices, however, faces limits in efficiency due to the semiconductor properties of commonly used GaAs materials. Here, we demonstrate that large bandgap semiconductor GaN, characterized by its high breakdown electric field, facilitates the highly efficient generation of terahertz waves in a coplanar stripline waveguide. Towards this goal, we investigated the excitonic contribution to the electro-optic response of GaN under static electric field both through experiments and first-principles calculations, revealing a robust excitonic Stark shift. Using this electro-optic effect, we developed a novel ultraviolet pump-probe spectroscopy for in-situ characterization of the terahertz electric field strength generated by the GaN photoconductive emitter. Our findings show that terahertz power scales quadratically with optical excitation power and applied electric field over a broad parameter range. We achieved an optical-to-terahertz conversion efficiency approaching 100% within the 0.03–1 THz bandwidth at the highest bias field (116 kV/cm) in our experiment. Further optimization of GaN-based terahertz generation devices could achieve even greater optical-to-terahertz conversion efficiencies.

Uzundal, Can B↗
DOE OSTI2021

A Deep Gravity model for mobility flows generation

The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. When information about mobility flows is not available for a particular region of interest, we must rely on mathematical models to generate them. In this work, we propose Deep Gravity, an effective model to generate flow probabilities that exploits many features (e.g., land use, road network, transport, food, health facilities) extracted from voluntary geographic data, and uses deep neural networks to discover non-linear relationships between those features and mobility flows. Our experiments, conducted on mobility flows in England, Italy, and New York State, show that Deep Gravity achieves a significant increase in performance, especially in densely populated regions of interest, with respect to the classic gravity model and models that do not use deep neural networks or geographic data. Deep Gravity has good generalization capability, generating realistic flows also for geographic areas for which there is no data availability for training. Finally, we show how flows generated by Deep Gravity may be explained in terms of the geographic features and highlight crucial differences among the three considered countries interpreting the model’s prediction with explainable AI techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Observation of a new type of self-generated current in magnetized plasmas

A tokamak, a torus-shaped nuclear fusion device, needs an electric current in the plasma to produce magnetic field in the poloidal direction for confining fusion plasmas. Plasma current is conventionally generated by electromagnetic induction. However, for a steady-state fusion reactor, minimizing the inductive current is essential to extend the tokamak operating duration. Several non-inductive current drive schemes have been developed for steady-state operations such as radio-frequency waves and neutral beams. However, commercial reactors require minimal use of these external sources to maximize the fusion gain, Q, the ratio of the fusion power to the external power. Apart from these external current drives, a self-generated current, so-called bootstrap current, was predicted theoretically and demonstrated experimentally. Here, we reveal another self-generated current that can exist in a tokamak and this has not yet been discussed by present theories. We report conclusive experimental evidence of this self-generated current observed in the KSTAR tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Giant electric field-induced second harmonic generation in polar skyrmions

Electric field-induced second harmonic generation allows electrically controlling nonlinear light-matter interactions crucial for emerging integrated photonics applications. Despite its wide presence in materials, the figures-of-merit of electric field-induced second harmonic generation are yet to be elevated to enable novel device functionalities. Here, we show that the polar skyrmions, a topological phase spontaneously formed in PbTiO3/SrTiO3 ferroelectric superlattices, exhibit a high comprehensive electric field-induced second harmonic generation performance. The second-order nonlinear susceptibility and modulation depth, measured under non-resonant 800 nm excitation, reach ~54.2 pm V −1 and ~664% V −1 , respectively, and high response bandwidth (higher than 10 MHz), wide operating temperature range (up to ~400 K) and good fatigue resistance (>10 10 cycles) are also demonstrated. Through combined in-situ experiments and phase-field simulations, we establish the microscopic links between the exotic polarization configuration and field-induced transition paths of the skyrmions and their electric field-induced second harmonic generation response. Our study not only presents a highly competitive thin-film material ready for constructing on-chip devices, but opens up new avenues of utilizing topological polar structures in the fields of photonics and optoelectronics.

Nonlinear optics↗
DOE OSTI2024

True random number generation using the spin crossover in LaCoO 3

While digital computers rely on software-generated pseudo-random number generators, hardware-based true random number generators (TRNGs), which employ the natural physics of the underlying hardware, provide true stochasticity, and power and area efficiency. Research into TRNGs has extensively relied on the unpredictability in phase transitions, but such phase transitions are difficult to control given their often abrupt and narrow parameter ranges (e.g., occurring in a small temperature window). Here we demonstrate a TRNG based on self-oscillations in LaCoO 3 that is electrically biased within its spin crossover regime. The LaCoO 3 TRNG passes all standard tests of true stochasticity and uses only half the number of components compared to prior TRNGs. Assisted by phase field modeling, we show how spin crossovers are fundamentally better in producing true stochasticity compared to traditional phase transitions. As a validation, by probabilistically solving the NP-hard max-cut problem in a memristor crossbar array using our TRNG as a source of the required stochasticity, we demonstrate solution quality exceeding that using software-generated randomness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Octupole moment driven free charge generation in partially chlorinated subphthalocyanine for planar heterojunction organic photodetectors

In this study, high-performance organic photodetectors are presented which utilize a pristine chlorinated subphthalocyanine photoactive layer. Optical and optoelectronic analyses indicate that the device photocurrent is primarily generated through direct charge generation within the chlorinated subphthalocyanine layer, rather than exciton separation at layer interfaces. Molecular modelling suggests that this direct charge generation is facilitated by chlorinated subphthalocyanine high octupole moment (-80 DÅ 2 ), which generates a 200 meV shift in molecular energetics. Increasing the thickness of chlorinated subphthalocyanine leads to faster response time, correlated with a decrease in trap density. Notably, photodetectors with a 50 nm thick chlorinated subphthalocyanine photoactive layer exhibit detectivities approaching 10 13 Jones, with a dark current below 10 -7 A cm -2 up to -5 V. Based on these findings, we conclude that high octupole moment molecular semiconductors are promising materials for high-performance organic photodetectors employing single-component photoactive layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

AI-assisted rapid crystal structure generation towards a target local environment

In material design, traditional crystal structure prediction approaches are expensive as they require extensive structural sampling through expensive energy minimization methods. Emerging artificial intelligence (AI) generative models have shown great promise in rapidly generating realistic crystals, but they typically handle only a few tens of atoms per unit cell. To overcome this limitation, we introduce a symmetry-informed approach, the Local Environment Geometry-Oriented Crystal Generator (LEGO-xtal). Our method generates initial structures using AI models trained on an augmented dataset, and then optimizes them using structure descriptors rather than energy-based optimization. We demonstrate its effectiveness by expanding from 25 known low-energy sp2 carbon allotropes to over 1700, all within 0.5 eV/atom of the ground-state energy of graphite. This framework offers a generalizable strategy for the targeted design of materials with modular building blocks, such as metal-organic frameworks and battery materials.

Ridwan, Osman Goni [University of North Carolina a↗
DOE OSTI2024

Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.

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

Addressing the Safety of Next-Generation Batteries

Owing to increasing demand for low-cost energy storage with secure material supply chains, the battery community is approaching a pivotal shift beyond conventional lithium-ion (Li-ion) towards next-generation cells. Technologies that include alkali-metal anodes, solid electrolytes and earth-abundant materials such as sodium (Na) and sulfur (S) are reaching commercialization in cells. The abuse tolerance and thermal runaway hazards of such technologies diverge from conventional Li-ion cells. Consequently, designing safe batteries with next-generation materials requires a holistic approach to characterize cells and to understand their responses to abuse conditions from the beginning to the end of life. Here we provide a Perspective on how the safety and abuse tolerance of cells are likely to change for up-and-coming technologies; challenges and opportunities for reimagining safe cell and battery designs; gaps in our knowledge; capabilities for understanding the hazards of thermal runaway and how to address them; how standard abuse tests may need to adapt to new challenges; and how research needs to support affected professionals, from pack designers to first responders, to manage hazards and ensure safe roll-out of next-generation cells into applications like electric vehicles (EVs). Finally, given the large number of next-generation technologies being explored, we encourage giving priority to safety-focused research in proportion to the rate of manufacturing scale-up of each specific technology.

25 ENERGY STORAGE↗
DOE OSTI2022

A thermoelectric materials database auto-generated from the scientific literature using ChemDataExtractor

An auto-generated thermoelectric-materials database is presented, containing 22,805 data records, automatically generated from the scientific literature, spanning 10,641 unique extracted chemical names. Each record contains a chemical entity and one of the seminal thermoelectric properties: thermoelectric figure of merit, ZT; thermal conductivity, κ; Seebeck coefficient, S; electrical conductivity, σ; power factor, PF; each linked to their corresponding recorded temperature, T. The database was auto-generated using the automatic sentence-parsing capabilities of the chemistry-aware, natural language processing toolkit, ChemDataExtractor 2.0, adapted for application in the thermoelectric-materials domain, following a rule-based sentence-simplification step. Data were mined from the text of 60,843 scientific papers that were sourced from three scientific publishers: Elsevier, the Royal Society of Chemistry, and Springer. To the best of our knowledge, this is the first automatically-generated database of thermoelectric materials and their properties from existing literature. The database was evaluated to have a precision of 82.25% and has been made publicly available to facilitate the application of data science in the thermoelectric-materials domain, for analysis, design, and prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The X-Ray Emission Effectiveness of Plasma Mirrors: Reexamining Power-Law Scaling for Relativistic High-Order Harmonic Generation

Ultrashort pulsed lasers provide uniquely detailed access to the ultrafast dynamics of physical, chemical, and biological systems, but only a handful of wavelengths are directly produced by solid-state lasers, necessitating efficient high-power frequency conversion. Relativistic plasma mirrors generate broadband power-law spectra, that may span the gap between petawatt-class infrared laser facilities and x-ray free-electron lasers; despite substantial theoretical work the ultimate efficiency of this relativistic high-order-harmonic generation remains unclear. We show that the coherent radiation emitted by plasma mirrors follows a power-law distribution of energy over frequency with an exponent that, even in the ultrarelativistic limit, strongly depends on the ratio of laser intensity to plasma density and exceeds the frequently quoted value of -8/3 over a wide range of parameters. The coherent synchrotron emission model, when adequately corrected for the finite width of emitting electron bunches, is not just valid for p-polarized light and thin foil targets, but generally describes relativistic harmonic generation, including at normal incidence and with finite-gradient plasmas. Our numerical results support the ω-4/3 scaling of the synchrotron emission model as a limiting efficiency of the process under most conditions. The highest frequencies that can be generated with this scaling are usually restricted by the width of the emitting electron bunch rather than the Lorentz factor of the fastest electrons. The theoretical scaling relations developed here suggest, for example, that with a 20-PW 800-nm driving laser, 1 TW/harmonic can be produced for 1-keV photons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Expanding the use of ethanol as a feedstock for cell-free synthetic biochemistry by implementing acetyl-CoA and ATP generating pathways

Abstract Ethanol is a widely available carbon compound that can be increasingly produced with a net negative carbon balance. Carbon-negative ethanol might therefore provide a feedstock for building a wider range of sustainable chemicals. Here we show how ethanol can be converted with a cell free system into acetyl-CoA, a central precursor for myriad biochemicals, and how we can use the energy stored in ethanol to generate ATP, another key molecule important for powering biochemical pathways. The ATP generator produces acetone as a value-added side product. Our ATP generator reached titers of 27 ± 6 mM ATP and 59 ± 15 mM acetone with maximum ATP synthesis rate of 2.8 ± 0.6 mM/h and acetone of 7.8 ± 0.8 mM/h. We illustrated how the ATP generating module can power cell-free biochemical pathways by converting mevalonate into isoprenol at a titer of 12.5 ± 0.8 mM and a maximum productivity of 1.0 ± 0.05 mM/h. These proof-of-principle demonstrations may ultimately find their way to the manufacture of diverse chemicals from ethanol and other simple carbon compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Tilted spin current generated by the collinear antiferromagnet ruthenium dioxide

Symmetry plays a central role in determining the polarization of spin currents induced by electric fields. It also influences how these spin currents generate spin-transfer torques in magnetic devices. Here, we show that an out-of-plane damping-like torque can be generated in ruthenium oxide (RuO 2 )/permalloy devices when the Néel vector of the collinear antiferromagnet RuO 2 is canted relative to the sample plane. By measuring characteristic changes in all three components of the electric-field-induced torque vector as a function of the angle of the electric field relative to the crystal axes, we find that the RuO 2 generates a spin current with a well-defined tilted spin orientation that is approximately parallel to the Néel vector. A maximum out-of-plane damping-like spin torque efficiency per unit electric field of 7±1 × 10 3 Ω -1 m -1 is measured at room temperature. Here, the observed angular dependence indicates that this is an antiferromagnetic spin Hall effect with symmetries that are distinct from other mechanisms of spin-current generation reported in antiferromagnetic and ferromagnetic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture

Metal-organic frameworks (MOFs) exhibit great promise for CO 2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework for the rational and accelerated design of MOFs with high CO 2 adsorption capacity and synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled with one of three pre-selected metal nodes (Cu paddlewheel, Zn paddlewheel, Zn tetramer) into MOFs in a primitive cubic topology. GHP-MOFassemble screens and validates AI-generated MOFs for uniqueness, synthesizability, structural validity, uses molecular dynamics simulations to study their stability and chemical consistency, and crystal graph neural networks and Grand Canonical Monte Carlo simulations to quantify their CO 2 adsorption capacities. We present the top six AI-generated MOFs with CO 2 capacities greater than 2m mol g -1 , i.e., higher than 96.9% of structures in the hypothetical MOF dataset.

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

Reweighting configurations generated by transferable, machine learned models for protein sidechain backmapping

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the atomistic ensemble of interest. We demonstrate conditions for which backmapped configurations may be reweighted to exactly recover the desired atomistic ensemble. By training separate decoding models for each sidechain type, we develop an algorithm based on normalizing flows and geometric algebra attention to autoregressively propose backmapped configurations for any protein sequence. Critical for reweighting with modern protein force fields, our trained models include all hydrogen atoms in the backmapping and make probabilities associated with atomistic configurations directly accessible. We also demonstrate, however, that reweighting is extremely challenging despite state-of-the-art performance on recently developed metrics and generation of configurations with low energies in atomistic protein force fields. Through detailed analysis of configurational weights, we show that machine-learned backmappings must not only generate configurations with reasonable energies, but also correctly assign relative probabilities under the generative model. These are broadly important considerations in generative modeling of atomistic molecular configurations.

Monroe, Jacob I. [Univ. of Arkansas, Fayetteville,↗
DOE OSTI2022

Adiabatic and isothermal configurations for Re 4 Si 7 transverse thermoelectric power generators

We report that transverse thermoelectric generators (TTEGs) have the potential to overcome two challenging problems that limit the commercial application of classical thermoelectric generators (TEGs): the significant irreversible efficiency losses in the contacts and the thermal degradation of the contacts at the hot end. TTEGs are built from a single material that can generate a thermoelectric current in a direction that is orthogonal to a temperature gradient. They only require a single set of contacts that are displaced away from the hot end. Here, we experimentally explore the device design considerations for optimizing the performance of this far less explored class of thermal-to-electric generation devices. We fabricate Re 4 Si 7 TTEGs and show that there is no measurable loss in efficiency with a single set of contacts that are midway between the hot and cold ends. We show that a new effect must be considered: the appearance of transverse thermal gradients that lead to significant differences between the performance of TTEGs implemented in isothermal and adiabatic geometries. The isothermal TTEG configuration leads to much higher device efficiencies. Overall, this work highlights how different the design of TTEGs is from that of conventional TEGs and the importance of controlling the device geometry for optimum waste heat recovery.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Aerodynamic-whistles-based ultrasonic tone generators for bat deterrence

Novel ultrasonic bat deterrents based on aerodynamic whistles are proposed and investigated experimentally and numerically for their ability to generate ultrasound. The baseline deterrent, a single-whistle design inspired by Beeken [“Fluid ultrasonic generator,” U.S. patent 3,432,804 (1969)], is examined first. It consists of two resonating cavities/chambers. The whistle is “powered” by a regulated high-pressure air supply, and the performance of the whistle is examined for a range of supply pressures. Far-field acoustic measurements in the 20 Hz–50 kHz frequency range are made in an anechoic chamber. The noise measurements are supplemented with two- and three-dimensional unsteady Reynolds-averaged Navier–Stokes (uRANS) simulations to investigate the mechanisms of ultrasound generation. The Ffowcs Williams–Hawkings acoustic analogy is used with the three-dimensional uRANS results to predict the far-field radiation. The far-field acoustic predictions are in good agreement with the measurements in the anechoic chamber. The peak frequency (fundamental) of the radiated ultrasound of the baseline deterrent is approximately 23 kHz. Harmonics and a sub-harmonic of the fundamental tone are also observed. The numerical simulations show that the two resonating chambers of the baseline deterrent operate out-of-phase and Helmholtz resonance determines the whistling frequency over the range of supply air pressure considered. A six-whistle deterrent targeting a broad spectral coverage in the 20–50 kHz frequency range is designed, fabricated, and tested in the anechoic chamber. Each whistle in the deterrent is obtained by geometrically scaling the baseline whistle. Measurements show that the six-whistle ultrasound deterrent generates ultrasound with six dominant peaks in the designed frequency range when the supply air pressure exceeds 5 psig. The proposed ultrasound devices can be used for a variety of purposes including bat deterrence at wind turbines.

42 ENGINEERING↗