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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Large-eddy simulation of non-vaporizing sprays using the spectral-element method

Predictive simulations of high-pressure sprays require accurate representation of the turbulent gaseous flow field generated by liquid jet. Typically, the accuracy that can be obtained with low-order numerical methods (e.g. finite volume, finite element) is limited by stability issues in fine grids and the order of convergence of the method. In this work, we resolve the turbulent flow field in an Eulerian manner using the high-order spectral element method, coupled with a Lagrangian parcels approach to model the atomizing liquid jet. Large eddy simulations of single-hole sprays under non-evaporative conditions were conducted and compared against experimental data from Margot et al. (2008) and Spray A data from the Engine Combustion Network. The sensitivity of liquid penetration and droplet sizes to different breakup model parameters was studied. The effect of different numerical parameters, such as polynomial order of the solution (grid resolution), on liquid penetration was also analyzed. The method achieved grid-independent results using p-refinement, achieving finer resolution (by a factor of x 1.7 - x 3.5) in the gas-phase solution than in state-of-the-art simulations using the finite-volume method. Here the results showed good agreement with experimental data, demonstrating the ability of the current method to accurately capture liquid penetration and the shape of the spray.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

U.S. advanced and novel accelerator beam test facilities

Demonstrating the viability of Advanced Accelerator Concepts (AAC) relies on experimental validation. Over the last three decades, the U.S. has maintained a portfolio of advanced and novel accelerator test facilities to support research critical to AAC. The facilities have enabled pioneering developments in a wide variety of beam and accelerator physics, including plasma-wakefield and structure-wakefield acceleration. This work provides an overview of the current portfolio of U.S. facilities possessing charged particle drive beams with high energies, on the order of tens of joules per pulse, or drive lasers with high peak powers, on the order of a petawatt, and are actively conducting AAC research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

US Advanced and Novel Accelerator Beam Test Facilities

Demonstrating the viability of Advanced Accelerator Concepts (AAC) relies on experimental validation. Over the last three decades, the US has maintained a portfolio of advanced and novel accelerator test facilities to support research critical to AAC. The facilities have enabled pioneering developments in a wide variety of beam and accelerator physics, including plasma-wakefeld and structure-wakefeld acceleration. This paper provides an overview of the current portfolio of US facilities possessing charged particle drive beams with high energies, on the order of tens of joules per pulse, or drive lasers with high peak powers, on the order of a petawatt, and are actively conducting AAC research.

Clarke, Christine↗
DOE OSTI2021

Realizing continuous cation order-to-disorder tuning in a class of high-energy spinel-type Li-ion cathodes

Conventional Li-ion cathode materials are dominated by well-ordered structures, in which Li and transition metals occupy distinct crystallographic sites. Here, we show in this paper that profoundly new degrees of freedom for the optimization of electrochemical properties may be accessed if controllable cation disorder is introduced. In a class of high-capacity spinel-type cathode materials, we identify cation to anion ratio in synthesis as a key parameter for tuning the structure continuously from a well-ordered spinel, through a partially ordered spinel, to rocksalt. We find that the varying degree of cation disorder modifies the voltage profile, rate capability, and charge-compensation mechanism in a rational and predictable way. Our results indicate that spinel-type order is most beneficial for achieving high-rate performance as long as the cooperative 8a to 16c phase transition is suppressed, while more rocksalt-like disorder facilitates O redox, which can increase capacity. Our findings reveal an important tuning handle for achieving high energy and power in the vast space of partially ordered cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2023

Emergence of high piezoelectricity from competing local polar order-disorder in relaxor ferroelectrics

Relaxor ferroelectrics are known for outstanding piezoelectric properties, finding a broad range of applications in advanced electromechanical devices. Decoding the origins of the enhanced properties, however, have long been complicated by the heterogeneous local structures. Here, we employ the advanced big-box refinement method by fitting neutron-, X-ray-based total scattering, and X-ray absorption spectrum simultaneously, to extract local atomic polar displacements and construct 3D polar configurations in the classical relaxor ferroelectric Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 . Our results demonstrate that prevailing order-disorder character accompanied by the continuous rotation of local polar displacements commands the composition-driven global structure evolution. The omnidirectional local polar disordering appears as an indication of macroscopic relaxor characteristics. Combined with phase-field simulations, it demonstrates that the competing local polar order-disorder between different states with balanced local polar length and direction randomness leads to a flattening free-energy profile over a wide polar length, thus giving rise to high piezoelectricity. Our work clarifies that the critical structural feature required for high piezoelectricity is the competition states of local polar rather than relaxor.

42 ENGINEERING↗
DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Discovery of Charge Order in the Transition Metal Dichalcogenide Fe x NbS 2

The Fe intercalated transition metal dichalcogenide (TMD), Fe 1/3 NbS 2 , exhibits remarkable resistance switching properties and highly tunable spin ordering phases due to magnetic defects. We conduct synchrotron x-ray scattering measurements on both underintercalated ( x = 0.32 ) and overintercalated ( x = 0.35 ) samples. We discover a new charge order phase in the overintercalated sample, where the excess Fe atoms lead to a zigzag antiferromagnetic order. The agreement between the charge and magnetic ordering temperatures, as well as their intensity relationship, suggests a strong magnetoelastic coupling as the mechanism for the charge ordering. In conclusion, our results reveal the first example of a charge order phase among the intercalated TMD family and demonstrate the ability to stabilize charge modulation by introducing electronic correlations, where the charge order is absent in bulk 2H - NbS 2 compared to other pristine TMDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Determination of permeability for hydrocarbon release due to excavation-induced stress redistribution in rock salt

Due to a stress redistribution after the excavation of an underground tunnel for radioactive waste disposal, an Ed/DZ (excavation disturbed/damaged zone) will be generated in the near field of the opening, resulting in significant changes in the hydraulic and mechanical properties of the rock mass in the zone. Initially more or less randomly distributed hydrocarbons at grain boundaries in rock salt, which sometimes can only be observed with ultraviolet light, can then be mobilised and migrate at a potentially significant rate towards the excavation. Within the international cooperative project DECOVALEX 2019, the migration mechanism of such fluid inclusions in rock salt is being studied intensively. Specifically, a multi-scale modelling strategy has been developed. A macroscale coupled hydro-mechanical modelling of an underground excavation was performed to determine hydraulic and time-dependent deviatoric stress conditions, by taking into account the rock salt creep behaviour. Under the obtained macro-scale constraints, micro-scale modelling of a pathway dilation along halite grain boundaries was performed using different model strategies: a) coupled hydromechanical modelling with a consideration of hydraulic pressure-induced dilatant deformation, b) nonlinear dynamic model taking account of fluid migration, stress-dependent grain boundary wetting and shear-induced dilatancy of salt, and c) phase-field modelling of flow pathway propagation. The permeability increase resulting from the pathway dilation is estimated to be as high as two orders of magnitude. Based on the permeability determined, a series of pressure buildups measured from a borehole with a high hydrocarbon release rate, a total of 430 build-ups within a monitoring time of 938 days, can be simulated with a macro-scale compressible flow model accounting for different zones around the opening.

58 GEOSCIENCES↗
DOE OSTI2021

Two Polymorphs of BaZn 2 P 2 : Crystal Structures, Phase Transition, and Transport Properties

Here, the novel α-BaZn 2 P 2 structural polymorph has been synthesized and structurally characterized for the first time. Its structure, elu-cidated from single crystal X-ray diffraction, indicates that the compound crystallizes in the orthorhombic α-BaCu 2 S 2 structure type, with unit cell parameters a = 9.7567(14) Å, b = 4.1266(6) Å, and c = 10.6000(15) Å. With β-BaZn 2 P 2 being previously iden-tified as belonging to the ThCr 2 Si 2 family, and with the precedent of structural phase transitions between the α-BaCu 2 S 2 type and the ThCr 2 Si 2 type, the potential for the pattern to be extended to the two different structural forms of BaZn 2 P 2 was explored. Thermal analysis suggest that a first order phase transition occurs at ~1123 K, whereby the low-temperature orthorhombic α-phase transforms to a high-temperature tetragonal β-BaZn 2 P 2 ; the structure of which was also studied and confirmed by single-crystal X-ray diffraction. Preliminary transport properties and band structure calculations indicate that α-BaZn 2 P 2 is a p-type, narrow-gap semiconductor with a direct bandgap (Eg) of 0.5 eV. The Seebeck coefficient, S(T), for the material increases steadily from the room temperature value of 119 µV/K to 184 µV/K at 600 K. The electrical resistivity of α-BaZn 2 P 2 is relatively high, on the order of 40 mΩ·cm, and the ρ(T) dependence shows gradual decrease upon heating. Such behavior is comparable to those of the typical semimetals or degenerate semiconductors. Although the observed values of the as-synthesized samples are not optimal, the carrier concentration can apparently be tuned to fall between the values of metals and semiconductors, thus providing an open window for optimizing this phase towards achieving an enhanced thermoelectric figure of merit zT. The calculated indirect band gap for the β-BaZn 2 P 2 phase is Eg = 0.03 eV which is about an order of magnitude lower than that of α-BaZn 2 P 2 . It is expected that the cage-like structural motif and layered structure possessed by α-BaZn 2 P 2 and β-BaZn 2 P 2 phases, respectively, would promote the realiza-tion of a low thermal conductivity in both compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Morphological Ordering of the Organic Layer for High-Performance Hybrid Thermoelectrics

Inorganic-organic hybrids, such as Te-PEDOT:PSS core/shell nanowires, have emerged as a class of promising thermoelectric materials with combined attributes of mechanical flexibility and low cost. However, the poorly understood structure-property relationship calls for further investigation for performance enhancement. Here, through precise treatments of focused electron beam irradiation and thermal annealing on individual Te-PEDOT:PSS nanowires, new, nonchemical mechanisms are introduced to specifically engineer the organic phase, and the measured results provide an unprecedented piece of evidence, confirming the dominant role of organic shell in charge transport. Paired with the Kang-Snyder model and molecular dynamics simulations, this work provides mechanistic insights in terms of heating-enabled morphological ordering of the polymer chains. The measured results show that thermal annealing on the 42 nm nanowire results in a ZT value of 0.78 at 450 K. In conclusion, through leveraging the interfacial self-assembly of the organic phase to construct a high electrical conductivity domain, this work lays out a clear framework for the development of next-generation soft thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tracking carrier and exciton dynamics in mixed-cation lead mixed-halide perovskite thin films

Mixed-cation lead mixed-halide perovskites simultaneously possess structural stability and high power conversion efficiency. A thorough study of both carrier and exciton dynamics is needed to understand the photophysical properties that underpin its superior photovoltaic performance. By utilizing a broadband transient absorption spectroscopy, we observe the carrier and exciton dynamics in a FA 0.85 Cs 0.15 Pb(I 0.97 Br 0.03 ) 3 (FCPIB) perovskite by simultaneously resolving the carrier and exciton contribution to the transient change of the absorption spectra, from which the carrier density and exciton oscillator strength can be determined. Our data reveal a quick and significant conversion of the photogenerated carriers to excitons, on top of the usual carrier recombination process. Moreover, the decay of carrier density shows a change of kinetics from a second-order recombination at high pump fluence to a third-order recombination at low pump fluence. Our analysis utilizes band anharmonicity, presents an independent determination of electronic temperature and quasi-Fermi energy, and reveals an interesting interplay among the processes of carrier cooling, exciton formation/decay and carrier recombination, all as a function of time after photoexcitation. Our work demonstrates the use of pump fluence as a knob to tune the relative populations of carriers and excitons in halide perovskite materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electron Energization by Inertial Alfvén Waves in Density Depleted Flux Tubes at Jupiter

Juno satellite observations have illustrated substantial examples of broadband electron energization up to 10 5 –10 6 eV levels. In order to explain these observations, we use a hybrid gyrofluid kinetic-electron model in an untilted dipolar topology to illustrate energization to high levels in weak current conditions by inertial Alfvén waves close to the Jupiter ionosphere for ambient plasma densities and magnetic field perturbations inferred from Juno satellite observations. The key to the high energization is the extremely low densities evident in the observations which necessitates the acceleration of electrons to very high velocities in order to carry the field-aligned current.

58 GEOSCIENCES↗
DOE OSTI2022

High resolution diagnostic tools for superconducting radio frequency cavities

Superconducting radio-frequency (SRF) cavities are one of the fundamental building blocks of modern particle accelerators. To achieve the highest quality factors (10 10 –10 11 ), SRF cavities are operated at liquid helium temperatures. Magnetic flux trapped on the surface of SRF cavities during cool-down below the critical temperature is one of the leading sources of residual RF losses. Instruments capable of detecting the distribution of trapped flux on the cavity surface are in high demand in order to better understand its relation to the cavity material, surface treatments and environmental conditions. We have designed, developed, and commissioned two high-resolution diagnostic tools to measure the distribution of trapped flux at the surface of SRF cavities. One is a magnetic field scanning system, which uses cryogenic Hall probes and anisotropic magnetoresistance sensors that fit the contour of a 1.3 GHz cavity. This setup has a spatial resolution of ~ 13 μm in the azimuthal direction and ~ 1 cm along the cavity contour. The second setup is a stationary, combined magnetic and temperature mapping system, which uses anisotropic magnetoresistance sensors and carbon resistor temperature sensors, covering the surface of a 3 GHz SRF cavity. This system has a spatial resolution of 5 mm close to the iris and 11 mm at the equator. Initial results show a non-uniform distribution of trapped flux on the cavities’ surfaces, dependent on the magnitude of the applied magnetic field during field-cooling below the critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2020

PyDDA: A Pythonic Direct Data Assimilation Framework for Wind Retrievals

This software assimilates data from an arbitrary number of weather radars together with other spatial wind fields (eg numerical weather forecasting model data) in order to retrieve high resolution three dimensional wind fields. PyDDA uses NumPy and SciPy’s optimization techniques combined with the Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART) in order to create wind fields using the 3D variational technique (3DVAR). PyDDA is hosted and distributed on GitHub at https://github.com/openradar/PyDDA. PyDDA has the potential to be used by the atmospheric science community to develop high resolution wind retrievals from radar networks. These retrievals can be used for the evaluation of numerical weather forecasting models and plume modelling. This paper shows how wind fields from 2 NEXt generation RADar (NEXRAD) WSR-88D radars and the High Resolution Rapid Refresh can be assimilated together using PyDDA to create a high resolution wind field inside Hurricane Florence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Neural operators for stochastic modeling of nonlinear structural system response to natural hazards

Traditionally, neural networks have been employed to learn the mapping between finite-dimensional Euclidean spaces. However, recent research has opened up new horizons, focusing on the utilization of deep neural networks to learn operators capable of mapping infinite-dimensional function spaces. Here, in this work, we employ two state-of-the-art neural operators, the deep operator network (DeepONet) and the Fourier neural operator (FNO) for the prediction of the nonlinear time history response of structural systems exposed to natural hazards, such as earthquakes and windstorms. Specifically, we propose two architectures, a self-adaptive FNO and a fast Fourier transform-based DeepONet (DeepFNOnet), where we employ a FNO beyond the DeepONet to learn the discrepancy between the ground truth and the solution predicted by the DeepONet. To demonstrate the efficiency and applicability of the architectures, two problems are considered. In the first, we use the proposed model to predict the seismic nonlinear dynamic response of a six-story shear building subject to stochastic ground motions. In the second problem, we employ the operators to predict the wind-induced nonlinear dynamic response of a high-rise building while explicitly accounting for the stochastic nature of the wind excitation. In both cases, the trained metamodels achieve high accuracy while being orders of magnitude faster than their corresponding high-fidelity models.

DeepONet↗
DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗