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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

All-epitaxial long-range surface plasmon polariton structures with integrated active materials

We demonstrate all-epitaxial structures capable of supporting short- and long-range surface plasmon polariton (SRSPP and LRSPP) modes in the long-wave infrared region of the electromagnetic spectrum. The SRSPP and LRSPP modes are bound to the interfaces of a buried heavily doped (n ++ ) semiconductor layer and surrounding quantum-engineered type-II superlattice (T2SL) materials. The surrounding T2SLs are designed to allow optical transitions across the frequency dispersion of the SPP modes. We map the SPP dispersion in our structure using grating-coupled angle- and polarization-dependent reflection and photoluminescence spectroscopy. The epitaxial structures are analytically described using a simplified three-layer system (T2SL/n ++ /T2SL) and modeled using rigorous coupled wave analysis with excellent agreement to our experimental results. The presented structures offer the potential to serve as long-range interconnects or waveguides in all-epitaxial plasmonic/optoelectronic systems operating in the long-wave infrared.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthetically non-Hermitian nonlinear wave-like behavior in a topological mechanical metamaterial

Topological mechanical metamaterials have enabled new ways to control stress and deformation propagation. Exemplified by Maxwell lattices, they have been studied extensively using a linearized formalism. Herein, we study a two-dimensional topological Maxwell lattice by exploring its large deformation quasi-static response using geometric numerical simulations and experiments. We observe spatial nonlinear wave-like phenomena such as harmonic generation, localized domain switching, amplification-enhanced frequency conversion, and solitary waves. We further map our linearized, homogenized system to a non-Hermitian, nonreciprocal, one-dimensional wave equation, revealing an equivalence between the deformation fields of two-dimensional topological Maxwell lattices and nonlinear dynamical phenomena in one-dimensional active systems. Our study opens a regime for topological mechanical metamaterials and expands their application potential in areas including adaptive and smart materials and mechanical logic, wherein concepts from nonlinear dynamics may be used to create intricate, tailored spatial deformation and stress fields greatly transcending conventional elasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of dissipative regions of a N-doped superconducting radio-frequency cavity

We report radio-frequency measurements of quality factors and temperature mapping of a nitrogen doped Nb superconducting RF cavity. Cavity cutouts of hot and cold spots were studied with low temperature scanning tunneling microscopy and spectroscopy, X-ray photoelectron spectroscopy and secondary electron microscopy. Temperature mapping revealed a substantial reduction of the residual resistance upon cooling the cavity with a greater temperature gradient and hysteretic losses at the quench location, pointing to trapped vortices as the dominant source of residual surface resistance. Analysis of the tunneling spectra in the framework of a proximity effect theory shows that hot spots have a reduced pair potential and a wider distribution of the contact resistance between the Nb and the top Nb oxide. Alone, these degraded superconducting properties account for a much weaker excess dissipation as compared with the vortex contribution. Based on the correlation between the quasiparticle density of states and temperature mapping, we suggest that degraded superconducting properties may facilitate vortex nucleation or settling of trapped flux during cooling the cavity through the critical temperature.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Deep neural operators can predict the real-time response of floating offshore structures under irregular waves

The use of neural operators in a digital twin model of an offshore floating structure holds the potential for a significant shift in the prediction of structural responses and health monitoring, offering valuable real-time control insights. In this work, we investigate the effectiveness of three neural operators, namely the deep operator network (DeepONet), the Fourier neural operator (FNO), and the Wavelet neural operator (WNO), to accurately capture the responses of a floating structure under six different sea state codes (3 − 8) based on the wave characteristics described by the World Meteorological Organization (WMO). To further enhance the accuracy of the vanilla architecture of the neural operators, novel extensions, such as wavelet-DeepONet and self-adaptive WNO, are proposed in this paper. The results demonstrate that these high-precision neural operators can deliver structural responses more efficiently, up to two orders of magnitude faster than a dynamic analysis using conventional numerical solvers. Additionally, compared to gated recurrent units (GRUs), a commonly used recurrent neural network for time-series estimation, neural operators are both more accurate and efficient, especially in situations with limited data availability. Taken together, our study shows that FNO outperforms all other operators for approximating the mapping of one input functional space to the output space as well as for responses that have small bandwidth of the frequency spectrum. Conversely, DeepONet, with historical states, proves most accurate in learning the mapping of multiple input functions to the output space and capturing responses within a broad frequency spectrum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Flood Susceptibility Mapping Using Machine Learning and Geospatial-Sentinel-1 SAR Integration for Enhanced Early Warning Systems

This study presents a comprehensive framework for flood susceptibility mapping by integrating geospatial factors with both statistical and machine learning models. Thirteen Flood-related factors, including DEM, slope, TWI, NDVI, etc., are extracted as features of models, and historical flood data derived from Sentinel-1 SAR from 2018 to 2023 are used as the target variables of the models. These datasets are analyzed using a frequency-based statistical model and three machine learning models, including Random Forest, XGBoost, and CNN, to generate flood susceptibility maps. The performance of each model is evaluated through AUC; and SHAP scores are separately generated for Machine learning (ML) models to explain each feature contribution in the ML model. The generated susceptibility maps are validated by high-flood-risk locations monitored by flood sensors, BLE inundation models, and flood-prone areas suggested by the Local Community Task Force. The results indicate that the XGBoost model outperforms all other models, with an AUC of 0.92 and demonstrates the highest alignment with recommended high-flood-risk locations, while the frequency-based statistical model showed the weakest performance with an AUC of 0.65. SHAP value graphs highlight the elevation, slope, and TWI as the most influential features across all models. The susceptibility maps generated by the machine learning model show strong agreement with the BLE map and high-flood-risk areas identified by the local Community Task Force.

Google Engine↗
DOE OSTI2020

Thermochemical Data Fusion Using Graph Representation Learning

Large databases are required for “Big Data” applications in catalysis and materials science. Thermochemical databases can be created by combining data from various sources and by correcting low-fidelity datasets to higher accuracy with minimal computation. To achieve this “data fusion”, thermochemical quantities of interest, calculated at various levels of density functional theory (DFT), need to be mapped to the same, high levels of theory. In this work, a graph theoretical, statistical framework is proposed for such tasks. Subgraph frequencies are shown to provide a natural representation for learning these fusion maps. The maps are linear and are learnt with automated descriptor selection. Using a dataset of as few as ~1% from the QM9 database of 133,885 molecules, these models can predict multiple thermochemical quantities at a higher level of theory with an accuracy of 1 kcal/mol. Here, the method is explainable, generalizable, and provides a diagnostic tool for outlier identification

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

Vibronic mixing enables ultrafast energy flow in light-harvesting complex II

Since the discovery of quantum beats in the two-dimensional electronic spectra of photosynthetic pigment-protein complexes over a decade ago, the origin and mechanistic function of these beats in photosynthetic light-harvesting has been extensively debated. The current consensus is that these long-lived oscillatory features likely result from electronic-vibrational mixing, however, it remains uncertain if such mixing significantly influences energy transport. Here, we examine the interplay between the electronic and nuclear degrees of freedom (DoF) during the excitation energy transfer (EET) dynamics of light-harvesting complex II (LHCII) with two-dimensional electronic-vibrational spectroscopy. Particularly, we show the involvement of the nuclear DoF during EET through the participation of higher-lying vibronic chlorophyll states and assign observed oscillatory features to specific EET pathways, demonstrating a significant step in mapping evolution from energy to physical space. These frequencies correspond to known vibrational modes of chlorophyll, suggesting that electronic-vibrational mixing facilitates rapid EET over moderately size energy gaps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probing plexciton emission from 2D materials on gold nanotrenches

Probing strongly coupled quasiparticle excitations at their intrinsic length scales offers unique insights into their properties and facilitates the design of devices with novel functionalities. In this work, we investigate the formation and emission characteristics of plexcitons, arising from the interaction between surface plasmons in narrow gold nanotrenches and excitons in monolayer WSe 2 . We study this strong plasmon–exciton coupling in both the far-field and the near-field. Specifically, we observe a Rabi splitting in the far-field reflection spectra of about 80 meV under ambient conditions, consistent with our theoretical modeling. Using a custom-designed near-field probe, we find that plexciton emission originates predominantly from the lower-frequency branch, which we can directly probe and map its local field distribution. We precisely determine the plexciton's spatial extension, similar to the trench width, with nanometric precision by collecting spectra at controlled probe locations. Our work opens exciting prospects for nanoscale mapping and engineering of plexcitons in complex nanostructures with potential applications in nanophotonic devices, optoelectronics, and quantum electrodynamics in nanoscale cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extragalactic CO emission lines in the CMB experiments: A forgotten signal and a foreground

High resolution cosmic microwave background (CMB) experiments have allowed us to precisely measure the CMB temperature power spectrum down to very small scales (multipole ℓ ~ 3000). Such measurements at multiple frequencies enable separating the power spectrum of the primary CMB anisotropies with the power spectrum of other signals like CMB lensing, thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ), and cosmic infrared background (CIB). Here, in this paper, we explore another signal of interest at these frequencies that should be present in the CMB maps: extragalactic CO molecular rotational line emissions, which are the most widely used tracers of molecular gas in the line intensity mapping experiments. Using the SIDES simulations adopted for top hat bandpasses at 150 and 220 GHz, we show that the cross-correlation of the CIB with CO lines has a contribution similar to the CIB-tSZ correlation and the kSZ power, thereby contributing a non-negligible amount to the total power at these scales. This signal, therefore, may significantly impact the recently reported ≥3σ detection of the kSZ power spectrum from the South Pole Telescope collaboration, as the contribution of the CO lines is not considered in such analyses. Our results also provide a new way of measuring the CO power spectrum in cross-correlation with the CIB. Finally, these results show that the CO emissions present in the CMB maps will have to be accounted for in all the CMB auto-power spectrum and cross-correlation studies involving a large-scale structure tracer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Infrared Galaxies Detected by the Atacama Cosmology Telescope

We report on 167 infrared (IR) galaxies selected by AKARI and IRAS and detected in the Atacama Cosmology Telescope (ACT) Data Release 5 (DR5) sky maps at the 98, 150, and 220 GHz frequency bands. Of these detections, 134 (80%) of the millimeter counterparts are first-time identifications with ACT. We expand the previous ACT extragalactic source catalogs, by including new 98 GHz detections and measurements from ACT DR5. We also report flux density measurements at the 98, 150, and 220 GHz frequency bands. We compute α 98-150 , α 98-220 , and α 150-220 millimeter-wave spectral indices and far-IR to millimeter-wave spectral indices between 90 μm and 98, 150, and 220 GHz. We specify the galaxy type, based on α 150-220 . We combine publicly available multiwavelength data—including ultraviolet, optical, near-IR, mid-IR, far-IR, and the millimeter measurements obtained in this work—and perform spectral energy distribution (SED) fitting with CIGALE. With the radio emission decomposition advantage of CIGALE V2022.0, we identify the origins of the millimeter emissions for 69 galaxies in our sample. Our analysis also shows that millimeter data alone indicates the need for a radio synchrotron component in the SEDs that are produced by active galactic nuclei (AGNs) and/or star formation. We present SEDs and measured physical properties of these galaxies, such as the dust luminosity, AGN luminosity, the total IR luminosity, and the ratio of the IR and radio luminosity. We quantify the relationships between the total IR luminosity and the millimeter-band luminosities, which can be used in the absence of SED analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗
DOE OSTI2023

Accelerated thermal property mapping of TRISO advanced nuclear fuel

TRistructural ISOtropic (TRISO) fuel is a leading-edge nuclear fuel form representing a departure from the more traditional nuclear fuel forms utilized in the reactor fleet of today. Rather than a monolithic fuel pellet of uranium dioxide, integral fuel forms containing TRISO fuel are composed of thousands of microencapsulated uranium-bearing fuel kernels and individually coated with multiple layers of pyrolytic carbon and silicon carbide. These multilayered ceramic coatings serve as an environmental barrier to ensure radioactive and chemically reactive fission products are contained within the reactor fuel elements, but also participate in the transfer of heat generated in the nuclear fuel to the coolant – the primary purpose of a nuclear reactor. Since traditional thermal property measurement techniques, such as laser flash analysis, would be unable to resolve the thermal properties of the individual TRISO coating layers, a simplified frequency-domain thermoreflectance technique has been developed to rapidly map the thermal properties of TRISO particles. Using this technique, the thermal properties of TRISO particles have been mapped from room temperature up to 1000 °C to examine the spatial variation and temperature-dependency of the thermal properties within each layer. Additionally, spatial-domain thermoreflectance was used to examine the anisotropy of the thermal properties for each layer at different locations within a single TRISO particle, and across multiple TRISO particles to assess the intra- and inter-particle uniformity of thermal properties, respectively. To elucidate the underlying causes for the measured variations in thermal properties, scanning electron microscopy and Raman spectroscopy were used to examine variations in microstructure and chemical bonding within the different coating layers. Results from this work are then compared with previous examinations of TRISO fuel particles and microstructurally driven mechanisms for the variations in the measured thermal properties of the different carbonaceous layers are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Data processing pipeline for Tianlai experiment

The Tianlai project is a 21cm intensity mapping experiment for detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily aected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline called tlpipe to process the drift scan survey data from the Tianlai experiment. It performs oine data processing tasks such as radio frequency interference (RFI) agging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis. In this paper we describe the design and implementation of the pipeline and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Numerical Model for the Dynamics of Pickup Ions Outside the Heliopause and IBEX “Ribbon” Observation

The leading mechanism for the origin of the Interstellar Boundary Explorer (IBEX) “ribbon” of enhanced energetic neutral atoms (ENAs) from the outer heliosphere is the so-called secondary ENA process. In this mechanism, neutralized ions escape the heliosphere, and after several times of charge exchange collision,s some propagate back toward Earth in directions nearly perpendicular to the local interstellar magnetic field. However, the physical processes governing the distribution of the pickup ions (PUIs) outside the heliopause are still unclear. In this study, we build a new global model of the IBEX ribbon, where a key component is to calculate the dynamics of the PUIs outside the heliopause by solving the gyrophase-averaged focused transport equations on top of the background magnetohydrodynamic-kinetic model for the heliosphere-interstellar medium interaction. We discuss how the properties of the simulated ribbon change with different scattering parameters and show simulation results of the ENA sky maps, ribbon centers, ribbon profiles at several azimuthal slices, the ribbon ENA source region, and the velocity distribution of PUIs in the ENA source region for different scattering frequencies. Our results show that the model can provide reasonable ribbon sky maps comparable to the observed ribbon when the PUI mean free path is on the order of several thousand astronomical units.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Analog In-Memory Computing for the Synthetic Aperture Radar Polar Format Algorithm

As the utility of synthetic aperture radar (SAR) systems increases in autonomous vehicles, satellites, and other power- and space-constrained edge applications, there is a growing need for processors that can form SAR images at low power. In recent years, analog in-memory compute (AIMC) has shown immense promise for accelerating neural networks and other matrix-vector multiplication (MVM) heavy workloads at the edge. Here, in this work, we examine how the polar format algorithm (PFA), a popular SAR image formation algorithm, can be mapped to these AIMC systems. The PFA maps readily onto analog MVMs because it primarily consists of two linear operations: interpolation of frequency-domain data to a Cartesian grid, followed by a 2-D Fourier transform. This work presents two approaches to map the interpolation operation onto MVMs in analog hardware: a chirp transform and a modified form of sinc interpolation. These mappings introduce algorithmic errors, and their effect on the quality of SAR image formation is examined, both quantitatively and qualitatively. In addition, the impact of errors introduced by the analog hardware is explored to determine which approach is optimal under varying assumptions about the underlying analog memory devices and circuits.

Analog computing↗
DOE OSTI2022

Optical readout of singlet fission biexcitons in a heteroacene with photoluminescence detected magnetic resonance

Molecular spin systems based on photoexcited triplet pairs formed via singlet fission (SF) are attractive as carriers of quantum information because of their potentially pure and controllable spin polarization, but developing systems that offer optical routes to readout as well as initialization is challenging. Herein, we characterize the electron spin magnetic resonance change in the photoluminescence intensity for a tailored organic molecular crystal while sweeping a microwave drive up to 10 GHz in a broadband loop structure. We observe resonant transitions for both triplet and quintet spin sublevel populations showing their optical sensitivity and revealing the zero-field parameters for each. We map the evolution of these spectra in both microwave frequency and magnetic field, producing a pattern of optically detected magnetic resonance (ODMR) peaks. Fits to these data using a suitable model suggest significant spin polarization in this system with orientation selectivity. Unusual excitation intensity dependence is also observed, which inverts the sign of the ODMR signal for the triplet features, but not for the quintet. These observations demonstrate optical detection of the spin sublevel population dictated by SF and intermolecular geometry, and highlight anisotropic and multi-scale dynamics of triplet pairs.

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

The Atacama Cosmology Telescope: Detection of the pairwise kinematic Sunyaev-Zel’dovich effect with SDSS DR15 galaxies

We present a 5.4$\sigma$ detection of the pairwise kinematic Sunyaev-Zel'dovich (kSZ) effect using Atacama Cosmology Telescope (ACT) and $\it{Planck}$ CMB observations in combination with Luminous Red Galaxy samples from the Sloan Digital Sky Survey (SDSS) DR15 catalog. Results are obtained using three ACT CMB maps: co-added 150 GHz and 98 GHz maps, combining observations from 2008-2018 (ACT DR5), which overlap with SDSS DR15 over 3,700 sq. deg., and a component-separated map using night-time only observations from 2014-2015 (ACT DR4), overlapping with SDSS DR15 over 2,089 sq. deg. Comparisons of the results from these three maps provide consistency checks in relation to potential frequency-dependent foreground contamination. A total of 343,647 galaxies are used as tracers to identify and locate galaxy groups and clusters from which the kSZ signal is extracted using aperture photometry. We consider the impact of various aperture photometry assumptions and covariance estimation methods on the signal extraction. Theoretical predictions of the pairwise velocities are used to obtain best-fit, mass-averaged, optical depth estimates for each of five luminosity-selected tracer samples. A comparison of the kSZ-derived optical depth measurements obtained here to those derived from the thermal SZ effect for the same sample is presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

First Constraints on the Epoch of Reionization Using the Non-Gaussianity of the Kinematic Sunyaev-Zel’dovich Effect from the South Pole Telescope and Herschel-SPIRE Observations

We report results from an analysis aimed at detecting the trispectrum of the kinematic Sunyaev-Zel’dovich (kSZ) effect by combining data from the South Pole Telescope (SPT) and Herschel-SPIRE experiments over a 100 deg 2 field. The SPT observations combine data from the previous and current surveys, namely SPTpol and SPT-3G, to achieve depths of 4.5, 3, and 16 μ K - arcmin in bands centered at 95, 150, and 220 GHz. For SPIRE, we include data from the 600 and 857 GHz bands. We reconstruct the velocity-induced large-scale correlation of the small-scale kSZ signal with a quadratic estimator that uses two cosmic microwave background (CMB) temperature maps, constructed by optimally combining data from all the frequency bands. We reject the null hypothesis of a zero trispectrum at 10.3 σ level. However, the measured trispectrum contains contributions from both the kSZ and other undesired components, such as CMB lensing and astrophysical foregrounds, with kSZ being sub-dominant. We use the agora simulations to estimate the expected signal from CMB lensing and astrophysical foregrounds. After accounting for the contributions from CMB lensing and foreground signals, we do not detect an excess kSZ-only trispectrum and use this nondetection to set constraints on reionization. By applying a prior based on observations of the Gunn-Peterson trough, we obtain an upper limit on the duration of reionization of Δ z re , 50 < 4.5 (95% confidence level). We find these constraints are fairly robust to foregrounds assumptions. This trispectrum measurement is independent of, but consistent with, Planck’s optical depth measurement. This result is the first constraint on the epoch of reionization using the non-Gaussian nature of the kSZ signal.

79 ASTRONOMY AND ASTROPHYSICS↗