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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermo-mechanical modeling and experimental validation for multilayered metallic microstructures

This paper presents thermo-mechanical modeling on multilayered metallic microstructures consisting of two bilayers that enable 3D deployment once being Joule heated. Additionally, a representative design of such microstructures, as well as their working principle is introduced. Furthermore, a mathematical model is derived using Euler–Bernoulli beam theory, and analytical solutions describing out-of-plane displacement of the multilayered microstructures when uniformly heated, which is validated by finite element analysis. Parametric analysis on thermal load and dimensional change of beam shows a good agreement between the analytical solutions and results given by finite element analysis. The phases of the near-equiatomic NiTi layer are analyzed by EDS and XRD, which prove to be austenite during the Joule heating process. The mechanical properties of austenite NiTi are incorporated into the analytical solutions that provides a good estimation of 3D deployment of microstructures made of NiTi and aluminum. The experimental results provide an approximately 7 µm out-of-plane deployment by applying a uniform temperature increase of 132 K, and parametric analysis on the dimension of top aluminum beam offers another promising approach to larger 3D deployment. The proposed mathematical model provides an efficient tool for predicting the out-of-plane deployment of such multilayered microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2020

Accelerated version of NUBEAM capabilities in DIII-D using neural networks

A neural network model of the effects of neutral beam injection on DIII-D has been developed. The training and testing data used by the model have been generated by the NUBEAM module of TRANSP for experimental discharges from the 2018 DIII-D campaign. Using a principle component analysis to reduce the dimensionality of profile data, the model has been shown to reproduce the results of the Monte Carlo code NUBEAM with a high level of accuracy and an execution time orders of magnitude faster than the execution time of NUBEAM. Furthermore, this makes the neural network model uniquely suited to applications in model-based scenario planning (off-line) and active control (on-line), where a large number of simulation runs are required by the associated optimization tasks that need to be performed before and during the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Raman Spectroscopy Analysis of the Structure and Surface Chemistry of Ti3C2Tx MXene

Raman spectroscopy is one of the most useful tools for the analysis of two-dimensional (2D) materials. While MXenes are a very large family of 2D transition metal carbides and nitrides, there have been just a few Raman studies of materials from this family. Here, we report on a systematic study of the most widely used and most important MXene to date: Ti 3 C 2 T x . By synthesizing material using different methods, we show that Raman spectra of Ti 3 C 2 T x are affected not only by the composition and surface groups but also by intercalated species and stacking. Due to a plasmonic peak of Ti 3 C 2 T x around 785 nm, resonant conditions are achieved, enabling us to observe an extra peak at ~120 cm –1 , when excited with a red diode laser. We report differences in Raman spectra collected from single flakes of Ti 3 C 2 T x , colloidal solutions, and multilayer films. Lastly, we show how an undesirable photoluminescent background could serve as evidence of material degradation, which leads to the formation of defective titania and amorphous carbon. Overall, this study shows how Raman spectroscopy can be used for the characterization of important emerging 2D materials: MXenes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2024

3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions

Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The scaling of kinetic and transport behaviors in the solution-phase chemistry of a plasma–liquid interface

The reactions at a plasma–liquid interface often involve species such as the solvated electron or the hydroxyl radical, which initiate the reduction or oxidation of solution-phase reactants (so-called scavengers) or are consumed by their own second-order recombination. Here, the mathematical scaling of the reaction–diffusion equations at the interface is used to obtain a characteristic time that can be used to determine the transition from highly efficient scavenger reduction or oxidation to lower efficiencies due to transport limitations. The characteristic time (tc) is validated using numerical solutions of the reaction–diffusion equations. When the scavenger kinetics are faster than second-order recombination, this characteristic transition time scales proportionally with the scavenger diffusivity (Ds) and the square of the scavenger bulk concentration (SB) and inversely proportional to the electron flux (J) squared; that is, t c = D s S B 2 F 2 /J 2 , where F is Faraday’s constant. However, when the scavenger kinetics are comparable or slower than second-order recombination, this scaling does not hold. Extending this analysis to three-dimensional systems shows that the profile of the electron flux on the surface affects the spatial location where reactions are most effective. Finally, the assessment of the implications of these behaviors for the reactor design highlights how effectively controlling the electron flux and solution transport may be necessary to improve the efficiency of scavenger reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A variational method for the sheath potential of hypersonic leading edges with space-charge limitations

Electron transpiration cooling for the leading edges (LE) of hypersonic aircraft utilizes thermionic emission; however, space-charge effects limit the electron emission rate, potentially diminishing the efficiency of this cooling mechanism. We develop a variational weak form of the Poisson equation that describes the sheath potential and then numerically solve it using the finite element method. This formulation has two main benefits: (1) the space-charge limit condition can be incorporated as a constraint and (2) it allows for the analysis of three-dimensional geometries with complex boundary conditions. We demonstrate that the current emitted from the surface of an LE is generally a small fraction of the Child–Langmuir limit due to space charge. We then propose several methods to enhance the emitted current from the surface and to boost the cooling effect of thermionic emission. These include increasing the plasma density, applying a negative surface potential, and using fringe fields under suitable geometric conditions. For a LaB6 emitting LE, the total emitted current is shown to be minimal and independent of the temperature of a surface with floating potential. However, when a negative potential is applied and the surface is heated, the emitted current follows the Richardson–Dushman relationship up to a critical temperature, beyond which it remains constant. At an applied surface potential of −5 V, the critical temperature is around 1700 K.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Properties of different LLM-105 preparations

LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) has been prepared at several different size quantities (~10–70 Kg) and not subjected to further purification, such as recrystallization. Chemical and physical properties were compared—small-scale safety testing (impact, friction, ESD), thermal (chemical reactivity, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), one-dimensional time-to-explosion (ODTX)), morphological (particle-size distribution (PSD), scanning electron microscopy (SEM), powder x-ray diffraction (PXRD), skeletal density). Each preparation had similar properties to the other preparations except for PSD and PXRD. For PSD, all preparations exhibited a mono-modal distribution with a variation in median values from ~ 40 μm to over 80 μm. All PXRD values indicated the same morphology with minor variations in crystal orientations. Possible polymorphism was also observed in a few cases. SEM images and PXRD indicate all preparations to be diamond-type and X-type crystals with some twinning. Impact, friction, and ESD and thermal sensitivities values are consistent with these type of crystal habits as seen in vast literature studies.

Explosive characterization↗
DOE OSTI2021

Plasma-assisted catalysis for ammonia synthesis in a dielectric barrier discharge reactor: key surface reaction steps and potential causes of low energy yield

Ammonia synthesis experiments were carried out in a coaxial dielectric barrier discharge (DBD) reactor packed with several different supports and metal catalysts. There was a marked increase in the reaction rate, over that obtained in an empty DBD plasma reactor, upon introduction of a packed bed of γ-Al 2 O 3 , Ru/γ-Al 2 O 3 , or SiO 2 particles. The difference in the reaction rates over γ-Al 2 O 3 and Ru/γ-Al 2 O 3 was minimal. Complementary zero-dimensional plasma kinetic model analysis was also performed using inputs from experimental data. This kinetic analysis allowed for gas phase reactions, Eley–Rideal (E–R) reactions, and direct adsorption of radical species on the γ-Al 2 O 3 surface. On the metal surface, dissociative adsorption of N 2 and H 2 , and Langmuir–Hinshelwood reactions were also included. This analysis revealed that, under the conditions of our experiments, ammonia synthesis proceeds principally by the formation of reactive radicals in the gas phase, which then adsorb and participate in E–R reactions on both the metal and support material surfaces. Furthermore, this finding illustrates a challenge for substantially increasing the energy yield for plasma-assisted ammonia synthesis in typical DBD reactors containing packed catalyst beads.

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

Krylov complexity in mixed phase space

We investigate the Krylov complexity of thermofield double states in systems with mixed phase space, uncovering a direct correlation with the Brody distribution, which interpolates between Poisson and Wigner statistics. Our analysis spans two-dimensional random matrix models featuring (I) GOE-Poisson and (II) GUE-Poisson transitions and extends to higher-dimensional cases, including a stringy matrix model (GOE-Poisson) and the mass-deformed SYK model (GUE-Poisson). Krylov complexity consistently emerges as a reliable marker of quantum chaos, displaying a characteristic peak in the chaotic regime that gradually diminishes as the Brody parameter approaches zero, signaling a shift toward integrability. These results establish Krylov complexity as a powerful diagnostic of quantum chaos and highlight its interplay with eigenvalue statistics in mixed phase systems.

chaos & nonlinear dynamics↗
DOE OSTI2024

Nanoscale structural correlations in a model cuprate superconductor

Understanding the extent and role of inhomogeneity is a pivotal challenge in the physics of cuprate superconductors. While it is known that structural and electronic inhomogeneity is prevalent in the cuprates, it has proven difficult to disentangle compound-specific features from universally relevant effects. Here, in this study, we combine advanced neutron and x-ray diffuse scattering with numerical modeling to obtain insight into bulk structural correlations in HgBa 2 ⁢ CuO 4+δ . This cuprate exhibits a high optimal transition temperature of nearly 100 K, pristine charge-transport behavior, and a simple average crystal structure without long-range structural instabilities, and is therefore uniquely suited for investigations of intrinsic inhomogeneity. We uncover diffuse reciprocal-space patterns that correspond to prominent nanoscale correlations of atomic displacements perpendicular to the CuO 2 planes. The real-space nature of the correlations is revealed through three-dimensional pair distribution function analysis and complementary numerical refinement. We find that relative displacements of ionic and CuO 2 layers play a crucial role, and that the structural inhomogeneity is not directly caused by the presence of conventional point defects. The observed correlations are therefore intrinsic to HgBa 2 ⁢ CuO 4+δ , and thus likely important for the physics of cuprates more broadly. It is possible that the structural correlations are closely related to the unusual superconducting fluctuations and Mott-localization in these complex oxides. As advances in scattering techniques yield increasingly comprehensive data, the experimental and analysis tools developed here for large volumes of diffuse scattering data can be expected to aid future investigations of a wide range of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Kolmogorov-Arnold wavefunctions

Here, this work investigates Kolmogorov-Arnold network-based (KAN) wave-function Ansätz as viable representations for quantum Monte Carlo simulations. Through systematic analysis of one-dimensional model systems, we evaluate their computational efficiency and representational power against established methods. Our numerical experiments suggest some efficient training methods and we explore how the computational cost scales with desired precision, particle number, and system parameters. Roughly speaking, KANs seem to be 10 times cheaper computationally than other neural-network-based Ansätz . We also introduce a novel approach for handling strong short-range potentials—a persistent challenge for many numerical techniques—which generalizes efficiently to higher-dimensional, physically relevant systems with short-ranged strong potentials common in atomic and nuclear physics.

1-dimensional systems↗
DOE OSTI2020

Fourfold alkyl wrapping of a copper(II) porphyrin thwarts macrocycle π–π stacking in a compact supramolecular package

Porphyrins are valuable constituents in optoelectronic, catalytic, and other applications, yet control of intermolecular π–π stacking is invariably essential to attain the desired properties. Superstructures built onto the porphyrin, often via meso -aryl groups, can afford facial encumbrance that suppresses π–π stacking, although some molecular designs have provided insufficient facial coverage and many have entailed cumbersome syntheses. In this study, a copper(II) porphyrin bearing four meso substituents, namely, {10,20-bis[2,6-bis(octyloxy)phenyl]-5,15-dibromoporphinato}copper(II), [Cu(C 64 H 82 Br 2 N 4 O 4 )], was prepared by metalation of the corresponding free-base porphyrin and was characterized by single-crystal X-ray diffraction. The crystal structure reveals a dihedral angle of 111.1 (2)° for the plane of the meso -aryl group relative to the plane of the porphyrin, with both aryl groups tilted in the same direction. Each of the four octyloxy groups exhibits a gauche conformation for the –OCH 2 CH 2 – unit but is extended with four or five anti (–CH 2 CH 2 –/H) conformations thereafter, causing each octyl group to span the dimension of the macrocycle. In a global frame of reference where the two Br atoms define the north/south poles and the two aryl groups are at antipodes on the equator, two octyl groups of one aryl unit project over the northern hemisphere (covering pyrroles A and B ), whereas those of the other aryl unit project over the southern hemisphere (covering pyrroles C and D ). Together, the four octyl groups ensheath the two faces of the porphyrin in a self-wrapped assembly. The closest approach of the Cu atom to an octyl methylene C atom (position 6) is 3.5817 (18) Å, the mean separations of neighboring porphyrin planes are 8.059 (4) and 4.693 (8) Å along the a and c axes, respectively, and the center-to-center distances between the Cu atoms of neighboring porphyrins are 10.2725 (4), 12.2540 (6), and 12.7472 (6) Å along the a , b , and c axes, respectively. The Hirshfeld surface analysis and two-dimensional (2D) fingerprint plots provide information concerning contact interactions in the supramolecular assembly of the solid crystal.

Chemistry↗
DOE OSTI2022

Laminated Permanent Magnets Enable Compact Magnetic Components in Current-Source Converters

Magnetic components have become one of the primary barriers to high power density converters, especially to current-source converters (CSCs). In CSCs, the inductors/transformers have a predominantly dc flux to store energy, which can be offset by standard permanent magnets (PMs). However, eddy currents in standard PMs induce significant losses and thermal stress for medium-frequency applications. This article proposes using laminated PMs to offset the dc flux while reducing eddy currents, leading to significant reductions in the size, cost, and losses of inductors/transformers. Furthermore, the laminated PMs’ optimal location, orientation, and distribution are investigated to generalize this approach for maximum benefits. Here, three-dimensional finite-element analysis simulation and hardware experiments are presented to validate the effectiveness of the proposed approach in a medium-frequency transformer (MFT) for CSCs. Compared with standard PMs, the proposed use of laminated PMs reduces aggregate core-plus-PM losses by 85% in experiments, and thus, relaxes the MFT thermal design. Finally, the proposed approach is experimentally validated in a 40 kVA flyback-type MFT for a soft-switching solid-state transformer. Compared to the traditional design without any PMs, the proposed design increases the saturation current by 46% while inducing only 5% more losses, leading to significant savings in magnetics cost and size.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Cross Section Evaluation for Exclusive Channels of K+Λ and K+Σ0 Electroproduction off Protons Using CLAS Detector Data

In this work, a method for evaluating the cross sections of electroproduction of K+Λ0 and K+Σ0 off protons in the region of invariant masses of final hadrons MK + MY <W < 2.65 GeV (MK and MY being the masses of the kaon and hyperon, respectively) and squares of four-momentum transfers of virtual photons, i.e., photon virtualities 0 < Q2 < 5 GeV2, is developed based on experimental data of these exclusive channels’ cross sections measured by the CLAS detector in Hall B at Jefferson Lab. A set of algorithms has been implemented to evaluate the differential cross sections of these channels, along with their statistical and systematic uncertainties. A program was developed for the evaluation of differential cross sections and structure functions using C++ and Python libraries. An interactive website was created for working with the program, enabling the analysis of one-dimensional and two-dimensional dependences of structure functions and differential cross sections. The evaluation of differential cross sections for the K+Λ and K+Σ0 electroproduction channels is necessary for extracting the structure function σLT from the data on the polarization asymmetry of electroproduction reactions of these final states with longitudinally polarized electrons. The obtained results are also important for the development of realistic Monte Carlo event generators in planning future experiments and for evaluating the efficiency of detecting final particles when extracting reaction cross sections from experimental data.

Golda, A. V.↗
DOE OSTI2023

ASME Irradiation Model

ASME Irradiation Model: How to deal with irradiation data in ASME code rules. Includes discussion on challenges to nuclear graphite, such as lack of sufficient irradiation data to qualify graphite for nuclear application for all grades and temperatures, variety of grades, and time/room in available MTRs to get all the required data. Discussion of Irradiation behavior, Leveraging data generated by GIF countries the past 20 years, Dimensional Change Theory, behavior, analysis, turnaround, and data. Future discussions include Arrhenius approach to predict turnaround behavior for the ASME MDS requirements for all nuclear graphite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗