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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Quantitative and sensitive analysis of CN molecules using laser induced low pressure He plasma

We report the results of experimental study on CN 388.3 nm and C I 247.8 nm emission characteristics using 40 mJ laser irradiation with He and N{sub 2} ambient gases. The results obtained with N{sub 2} ambient gas show undesirable interference effect between the native CN emission and the emission of CN molecules arising from the recombination of native C ablated from the sample with the N dissociated from the ambient gas. This problem is overcome by the use of He ambient gas at low pressure of 2 kPa, which also offers the additional advantages of cleaner and stronger emission lines. The result of applying this favorable experimental condition to emission spectrochemical measurement of milk sample having various protein concentrations is shown to yield a close to linear calibration curve with near zero extrapolated intercept. Additionally, a low detection limit of 5 μg/g is found in this experiment, making it potentially applicable for quantitative and sensitive CN analysis. The visibility of laser induced breakdown spectroscopy with low pressure He gas is also demonstrated by the result of its application to spectrochemical analysis of fossil samples. Furthermore, with the use of CO{sub 2} ambient gas at 600 Pa mimicking the Mars atmosphere, this technique also shows promising applications to exploration in Mars.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Management of light absorption in extraordinary optical transmission based ultra-thin-film tandem solar cells

Although ultra-thin-film solar cells can be attractive in reducing the cost, they suffer from low absorption as the thickness of the active layer is usually much smaller than the wavelength of incident light. Different nano-photonic techniques, including plasmonic structures, are being explored to increase the light absorption in ultra-thin-film solar cells. More than one layer of active materials with different energy bandgaps can be used in tandem to increase the light absorption as well. However, due to different amount of light absorption in different active layers, photo-generated currents in different active layers will not be the same. The current mismatch between the tandem layers makes them ineffective in increasing the efficiency. In this work, we investigate the light absorption properties of tandem solar cells with two ultra-thin active layers working as two subcells and a metal layer with periodically perforated holes in-between the two subcells. While the metal layer helps to overcome the current mismatch, the periodic holes increase the absorption of incident light by helping extraordinary optical transmission of the incident light from the top to the bottom subcell, and by coupling the incident light to plasmonic and photonic modes within ultra-thin active layers. We extensively study the effects of the geometry of holes in the intermediate metal layer on the light absorption properties of tandem solar cells with ultra-thin active layers. We also study how different metals in the intermediate layer affect the light absorption; how the geometry of holes in the intermediate layer affects the absorption when the active layer materials are changed; and how the intermediate metal layer affects the collection of photo-generated electron-hole pairs at the terminals. We find that in a solar cell with 6,6-phenyl C61-butyric acid methyl ester top subcell and copper indium gallium selenide bottom subcell, if the periodic holes in the metal layer are square or polygon, total absorption remains approximately the same. However, the total absorption suffers significantly if the holes are triangle. The transmission spectra of incident light into the bottom subcell, and hence the absorption, change significantly for square and circle holes if the active materials change to cadmium selenide (CdSe) and cadmium telluride (CdTe) in the top and bottom subcells, respectively. Although the intermediate metal layer may induce electron-hole pair recombination due to surface defects, the short-circuit current density of an ultra-thin plasmonic solar cell with an intermediate metal layer with two-dimensional hole array is >9% of that of a structure without the intermediate metal layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Transitional properties of supersolitons in a two electron temperature warm multi-ion plasma

The existence domain of an ion acoustic supersoliton and its transition to a regular kind of solitary wave have been explored in detail using Sagdeev pseudopotential technique for a two electron temperature warm multi-ion plasma having two species of ions. It was found that both the cold to hot electron temperature ratio and their respective ambient densities play a deterministic role for the existence of a supersoliton, as well as its transitional processes to a regular solitary wave. Analogous to a double layer solution, which often marks the boundary of the existence domain of a regular solitary wave, a “curve of inflection” determines the boundary of the existence domain of a supersoliton. The characteristics of the “curve of inflection,” in turn, depend on the respective concentrations of the two ion species. It is observed that the supersolitons are actually a subset of a more general kind of solutions which are characterized by a fluctuation in the corresponding charge separation which precedes their maximum amplitude. It is also observed that these novel kinds of solitary structures, including supersolitons, occur only for a very narrow range of parameters near constant amplitude beyond which the wave breaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Observation of x-ray radiation pressure effects on nanocrystals

Bragg coherent diffractive imaging is a powerful technique that can be used to explore the internal structure and strain of nanoscale crystalline objects. During the data collection process, the Bragg peak typically stays within a small range of pixels on the x-ray sensitive area detector. Here, we report abrupt and irreversible Bragg peak movement during the coherent x-ray data collection process for both Pd nanocubes and a Ni nanowire. Here, we report that this phenomenon can be attributed to x-ray momentum transfer, also known as radiation pressure, to the nanocrystals. Understanding this effect is crucial given the anticipated coherent flux increases at next-generation synchrotron sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

3D micromechanical simulation of PBX composites

Previous research studied the constitutive response and interface strength of a bonded bicrystal system containing two HMX explosive grains bound with a HTPB polymer binder by performing FE simulations on real geometry imaged with micro Computed Tomography (µCT). The parameters generated from this past study were successfully applied to 2D mesoscale simulations of µCT imaged HMX-HTPB polycrystal samples. Presently, the mechanical response of PBXs containing a Nitro-Plasticized Estane (NPE) binder with similar microstructural geometry to the HMX-HTPB polycrystal samples were studied. Imaging of a HMX-NPE bicrystal sample allowed for simulation of the new material pairing. However, imaging using µCT techniques on the new polycrystal samples was difficult due to the decrease in contrast between the HMX grains and the NPE binder. Mesoscale polycrystal simulations utilizing a single µCT imaged microstructure were performed on a 3D representative volume element (RVE) comparing the delamination behavior and mechanical response of both HMX-HTPB and HMX-NPE PBXs. Furthermore, this technique shows the ability to virtually explore the mechanical response of a range of hypothetical materials that share common microstructural geometric characteristics in addition to studying numerically altered geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Beyond optimization—supervised learning applications in relativistic laser-plasma experiments

We explore the applications of machine learning techniques in relativistic laser-plasma experiments beyond optimization purposes. We predict the beam charge of electrons produced in a laser wakefield accelerator given the laser wavefront change caused by a deformable mirror. Machine learning enables feature analysis beyond merely searching for an optimal beam charge, showing that specific aberrations in the laser wavefront are favored in generating higher beam charges. Supervised learning models allow characterizing the measured data quality as well as recognizing irreproducible data and potential outliers. Furthermore, we also include virtual measurement errors in the experimental data to examine the model robustness under these conditions. This work demonstrates how machine learning methods can benefit data analysis and physics interpretation in a highly nonlinear problem of relativistic laser-plasma interaction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Uncovering surface plasmon optical resonances in nanohole arrays through interferometric photoemission electron microscopy

In this work, the role of surface plasmon polaritons (SPPs) in nanohole array optical extinction spectra is explored using a time-resolved technique capable of isolating the air/metal interfacial SPP contribution to the typical Fano profile in optical transmission curves. A pair of interferometrically locked broad-band femtosecond pulses is used to launch SPPs from lithographically patterned plasmonic nanohole arrays. SPPs launched in the co- and counter-propagating directions are probed using a third probe pulse in a photoemission electron microscope. Using this approach, we record interferometric SPP–SPP linear autocorrelations that selectively report on the resonances of SPPs launched from arrays of varying pitches and hole diameters. Aside from advancing an approach to selective SPP spectroscopy, we illustrate that resonant coupling in the counter-propagating direction may be exploited to control the spatial, temporal, and spectral characteristics of SPPs. For the counter-propagating direction, we show that tuning the array pitch near the fundamental plasmon resonance generates color-tuned (~770–820 nm), narrow bandwidth SPPs, and the bandwidth may be controlled by changing the ratio of pitch to hole diameter. The SPP resonances we recover through Fourier transforms of the interferometric autocorrelations shed light on the classical problem of Fano interference in nanohole array extinction spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Evaluation of Digital Nautical Chart data for confirmation and expansion of GeoNames data

Here, this work examines how Digital Nautical Chart (DNC) data may contribute to the evolution and refinement of GeoNames data for near-shore features. GeoNames features are point data with one or more possible place names. DNC Earth Cover Text (ECRText) objects are map labels positioned nearby their real word counterpart. ECRText feature map position strikes a compromise between association with real features and cartographic readability. This work explores whether ECRText features can confirm (or expand names for) existing locations or contribute new locations through data conflation. Due to name variations and spatial position, conflating these data are nontrivial. Previous work engaged in a brief examination using the trigram string matching algorithm under coarse proximity constraints, indicating that ECRText could provide additional value to GeoNames. This work builds on that study, by engaging in a deeper examination of spatial proximity and exploring conflation agreement across an ensemble of string matching approaches. The result finds strong ensemble agreement about ECRText features which already exist in GeoNames but mixed results about which features contribute new information, as well as exploring why some of these matching techniques fail. With an eye toward automation, computational efficiency was found not to be a constraint in sustaining updates.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

MEASURING THE DIRECTION AND ANGULAR VELOCITY OF A BLACK HOLE ACCRETION DISK VIA LAGGED INTERFEROMETRIC COVARIANCE

We show that interferometry can be applied to study irregular, rapidly rotating structures, as are expected in the turbulent accretion flow near a black hole. Specifically, we analyze the lagged covariance between interferometric baselines of similar lengths but slightly different orientations. For a flow viewed close to face-on, we demonstrate that the peak in the lagged covariance indicates the direction and angular velocity of the emission pattern from the flow. Even for moderately inclined flows, the covariance robustly estimates the flow direction, although the estimated angular velocity can be significantly biased. Importantly, measuring the direction of the flow as clockwise or counterclockwise on the sky breaks a degeneracy in accretion disk inclinations when analyzing time-averaged images alone. We explore the potential efficacy of our technique using three-dimensional, general relativistic magnetohydrodynamic simulations, and we highlight several baseline pairs for the Event Horizon Telescope (EHT) that are well-suited to this application. These results indicate that the EHT may be capable of estimating the direction and angular velocity of the emitting material near Sgr A*, and they suggest that a rotating flow may even be utilized to improve imaging capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Searching for WISPy cold dark matter with a dish antenna

The cold dark matter of the Universe may be comprised of very light and very weakly interacting particles, so-called WISPs. Two prominent examples are hidden photons and axion-like particles. In this note we propose a new technique to sensitively search for this type of dark matter with dish antennas. The technique is broadband and allows to explore a whole range of masses in a single measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗
DOE OSTI2024

Qutrit circuits and algebraic relations: A pathway to efficient spin-1 Hamiltonian simulation

Quantum information processing has witnessed significant advancements through the application of qubit-based techniques within universal gate sets. Recently, exploration beyond the qubit paradigm to d -dimensional quantum units or qudits has opened new avenues for improving computational efficiency. This paper delves into the qudit-based approach, particularly addressing the challenges presented in the high-fidelity implementation of qudit-based circuits due to increased complexity. As an innovative approach towards enhancing qudit circuit fidelity, we explore algebraic relations, such as the Yang-Baxter-like turnover equation, which may enable circuit compression and optimization. The paper introduces the turnover relation for the three-qutrit time propagator and its potential use in reducing circuit depth. We further investigate whether this relation can be generalized for higher-dimensional quantum circuits, including a focused study on the one-dimensional spin-1 Heisenberg model. Our paper outlines both rigorous and numerically efficient approaches to potentially achieve this generalization, providing a foundation for further explorations in the field of qudit-based quantum computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
DOE OSTI2018

Visualizing effective potentials and using the IBM-Q to study quantum field theory models in 0+1 dimensions

This work explores the utility of two novel techniques applied to studying quantum field theory, namely quantum computing and visualizing effective potentials. We studied the ground state properties of the anharmonic oscillator and the Wess-Zumino model using the variational quantum eigensolver algorithm. We performed calculations for three and four qubit systems using IBM’s open source quantum computing simulation software. Using effective potentials, we study a simple dark mat-ter system with a Higgs and dark Higgs like particle interacting through a porthole fermion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows

Quantum Natural Language Processing (QNLP) develops natural language processing (NLP) models for deployment on quantum computers. We explore feature and data prototype selection techniques to address challenges posed by encoding high dimensional features. Our study builds quantum circuit classifiers that includes classical feature pre-processing, quantum embedding and quantum model training. The quantum models are built on 4 or 6 qubits and the quantum neural network (QNN) uses the established bricklayer design. We compare the dependence of model performance (in terms of accuracy and F1 scores) on feature length, embedding gates and parameterized unitary design. We compare the performance of quantum machine learning models to classical convolution neural network model (CNN) on binary and multi-class classification tasks using two datasets of synthetic features and labels. The first is the ECP-CANDLE P3B3 dataset a corpus of synthetically generated cancer pathology reports. The second dataset is extracted from well-known benchmark dataset (MADELON) - features are generated with a combination of informative, repeated and uninformative features. Both datasets are used for binary classification and multi-class classification with 3 classes. We observe robust, accurate performance from all models on the binary classification tasks, but multiclass classification is a challenge for the quantum models-there is a notable decrease in accuracy when using 3 classes. Overall the performance is comparable in terms of recall and accuracy between QNNs and CNNs, even with large datasets. These results provide a point of comparison between quantum and classical models on real-world datasets.

Hamilton, Kathleen↗
DOE OSTI2024

Spike-and-Slab Shrinkage Priors for Structurally Sparse Bayesian Neural Networks

Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a sparse representation of the underlying target function by reducing heavily overparameterized deep neural networks. Specifically, deep neural architectures compressed via structured sparsity (e.g., node sparsity) provide low-latency inference, higher data throughput, and reduced energy consumption. In this article, we explore two well-established shrinkage techniques, Lasso and Horseshoe, for model compression in Bayesian neural networks (BNNs). To this end, we propose structurally sparse BNNs, which systematically prune excessive nodes with the following: 1) spike-and-slab group Lasso (SS-GL) and 2) SS group Horseshoe (SS-GHS) priors, and develop computationally tractable variational inference, including continuous relaxation of Bernoulli variables. We establish the contraction rates of the variational posterior of our proposed models as a function of the network topology, layerwise node cardinalities, and bounds on the network weights. Furthermore, we empirically demonstrate the competitive performance of our models compared with the baseline models in prediction accuracy, model compression, and inference latency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Paint and Click: Unified Interactions for Image Boundaries

Image boundaries are a fundamental component of many interactive digital photography techniques, enabling applications such as segmentation, panoramas, and seamless image composition. Interactions for image boundaries often rely on two complementary but separate approaches: editing via painting or clicking constraints. In this work, we provide a novel, unified approach for interactive editing of pairwise image boundaries that combines the ease of painting with the direct control of constraints. Rather than a sequential coupling, this new formulation allows full use of both interactions simultaneously, giving users unprecedented flexibility for fast boundary editing. To enable this new approach, we provide technical advancements. In particular, we detail a reformulation of image boundaries as a problem of finding cycles, expanding and correcting limitations of the previous work. Our new formulation provides boundary solutions for painted regions with performance on par with state-of-the-art specialized, paint-only techniques. In addition, we provide instantaneous exploration of the boundary solution space with user constraints. Finally, we provide examples of common graphics applications impacted by our new approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Effectiveness of nondestructive methods for the Evaluation of structures affected by internal swelling reactions: a review of electric, seismic and acoustic methods based on laboratory and site experiences

Internal swelling reactions (ISR) (which mainly comprise alkali-silica reaction, alkali-carbonate reaction, delayed ettringite formation, etc) are damage processes that affect the long-term durability of concrete structures. The reactions are apparently characterized by series of closely spaced, tight map cracks with wide cracks appearing at regular intervals, and excessive tensile stresses in rebars. These phenomena are alarming for affected structure managers as they deal with people safety and structures operation. Moreover, there is no easily implemented way to stop the reactions. Prediction of concrete expansion, structural degradation, and assessment of efficiency and periodicity of repair works are crucial issues. The aim of this work is to explore the applicability of some nondestructive techniques (NDT) of investigations (electric, seismic, and acoustic methods) to differentiate the structure zones affected or not by the ISR for different exposure conditions. The collected experience highlights that the coupling between some of those nondestructive (ND) methods can reduce the measurement uncertainty and eliminates the factors that may influence the characterization of the structure parts affected by ISR. Nevertheless, for a complete structure reassessment, it is also desirable to refer to global geometrical/topographical survey and to destructive analysis methods on some cored samples for chemical analysis, petrography, and residual expansion measurements.

42 ENGINEERING↗