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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Circumbinary Disk Accretion into Spinning Black Hole Binaries

Supermassive black hole binaries are likely to accrete interstellar gas through a circumbinary disk.Shortly before merger, the inner portions of this circumbinary disk are subject to general relativisticeffects. To study this regime, we approximate the spacetime metric of close orbiting black holes bysuperimposing two boosted Kerr-Schild terms. After demonstrating the quality of this approximation,we carry out very long-term general relativistic magnetohydrodynamic simulations of the circumbinarydisk. We consider black holes with spin dimensionless parameters of magnitude 0.9, in one simula-tion parallel to the orbital angular momentum of the binary, but in another anti-parallel. These arecontrasted with spinless simulations. We find that, for a fixed surface mass density in the inner cir-cumbinary disk, aligned spins of this magnitude approximately reduce the mass accretion rate by 14%and counter-aligned spins increase it by 45%, leaving many other disk properties unchanged.

Federico G Lopez Armengol↗
NASA NTRS2021

The JAGWAR Prowls LIGO/Virgo O3 Paper I: Radio Search of a Possible Multimessenger Counterpart of the Binary Black Hole Merger Candidate S191216ap

We present a sensitive search with the Karl G. Jansky Very Large Array for the radio counterpart of the gravitational wave candidate S191216ap, which is classified as a binary black hole merger and suggested to be a possible multimessenger event, based on the detection of a high-energy neutrino and a TeV photon. We carried out a blind search at C band (4–8 GHz) over 0.3 deg2 of the gamma-ray counterpart of S191216ap reported by the High-Altitude Water Cerenkov Observatory (HAWC). Our search, spanning three epochs over 130 days of postmerger and having a mean source-detection threshold of 75 μJy beam−1 (4σ), yielded five variable sources associated with active galactic nucleus activity and no definitive counterpart of S191216ap. We find <2% (3.0% ± 1.3%) of the persistent radio sources at 6 GHz to be variable on a timescale of <1 week (week–months), consistent with previous radio variability studies. Our 4σ radio luminosity upper limit of ∼1.2 × 1028 erg s−1 Hz−1 on the afterglow of S191216ap, within the HAWC error region, is 5–10 times deeper than previous binary black hole (BBH) radio afterglow searches. Comparing this upper limit with theoretical expectations given by Perna et al. for putative jets launched by BBH mergers, for on-axis jets with energy ≃1049 erg, we can rule out jet opening angles ≲ 20° (assuming that the counterpart lies within the 1σ HAWC region that we observed).

D Bhakta↗
NASA NTRS2022

Eta Carinae: An Evolving View of the Central Binary, Its Interacting Winds and Its Foreground Ejecta

FUV spectra of η Car, recorded across two decades with HST/STIS, document multiple changes in resonant lines caused by dissipating extinction in our line of sight. The FUV flux has increased nearly tenfold, which has led to increased ionization of the multiple shells within the Homunculus and photodestruction of H 2 . Comparison of observed resonant line profiles with CMFGEN model profiles allows separation of wind–wind collision and shell absorptions from the primary wind P Cygni profiles. The dissipating occulter preferentially obscured the central binary and interacting winds relative to the very extended primary wind. We are now able to monitor changes in the colliding winds with orbital phase. High-velocity transient absorptions occurred across the most recent periastron passage, indicating acceleration of the primary wind by the secondary wind, which leads to a downstream, high-velocity bow shock that is newly generated every orbital period. There is no evidence of changes in the properties of the binary winds.

Massive stars↗
DOE OSTI2020

Biosequence-based approach to analyzing binaries

In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Binary classification with noisy quantum circuits and noisy quantum data

We study the effects of single-qubit noises in the quantum circuit and the corruption in the quantum training data to the performance of binary classification problem. We find that under the presence of errors, the measurement at a qubit is affected only by the noise in the corresponding qubit, and that the errors on other qubits do not affect this outcome. Furthermore, for the task where we fit a binary classifier using a quantum training data, we show that the noise in the data can work as a regularizer, implying that we can benefit from the noise in certain cases. We support our findings with simulations.

Lee, Yonghoon↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Extending Power of Nature from Binary Problems to Real-Valued Graph Learning in Real World

Nature performs complex computations constantly at clearly lower cost and higher performance than digital computers. It is crucial to understand how to harness the unique computational power of nature in Machine Learning (ML). In the past decade, besides the development of Neural Networks (NNs), the community has also relentlessly explored nature-powered ML paradigms. Although most of them are still predominantly theoretical, a new practical paradigm enabled by the recent advent of CMOS-compatible room-temperature nature-based computers has emerged. By harnessing the nature's power of entropy increase, this paradigm can solve binary learning problems delivering immense speedup and energy savings compared with NNs, while maintaining comparable accuracy. Regrettably, its values to the real world are highly constrained by its binary nature. A clear pathway to its extension to real-valued problems remains elusive. This paper aims to unleash this pathway by proposing a novel end-to-end Nature-Powered Graph Learning (NP-GL) framework. Specifically, through a three-dimensional co-design, NP-GL can leverage the nature's power of entropy increase to efficiently solve real-valued graph learning problems. Experimental results across 4 real-world applications with 6 datasets demonstrate that NP-GL delivers, on average, 6970X speedup and 10^5x energy consumption reduction with comparable or even higher accuracy than Graph Neural Networks (GNNs).

artificial intelligence↗
NASA NTRS2022

Elevated Hot Gas and High-mass X-Ray Binary Emission in Low-metallicity Galaxies: Implications for Nebular Ionization and Intergalactic Medium Heating in the Early Universe

High-energy emission associated with star formation has been proposed as a significant source of interstellar medium (ISM) ionization in low-metallicity starbursts and an important contributor to the heating of the intergalactic medium (IGM) in the high-redshift (z ≳ 8) universe. Using Chandra observations of a sample of 30 galaxies at D ≈ 200–450 Mpc that have high specific star formation rates of 3–9 Gyr^(−1) and metallicities near Z ≈ 0.3Z_⊙, we provide new measurements of the average 0.5–8 keV spectral shape and normalization per unit star formation rate (SFR). We model the sample-combined X-ray spectrum as a combination of hot gas and high-mass X-ray binary (HMXB) populations and constrain their relative contributions. We derive scaling relations of log L^(HMXB)_(0.5-8keV) / SFR = 40.19 ± 0.06 and log L^(gas)_(0.5-2keV) / SFR = 39.58 ^(+0.17)_(-0.28), significantly elevated compared to local relations. The HMXB scaling is also somewhat higher than L^(HMXB)_(0.5-8keV) -SFR-Z relations presented in the literature, potentially due to our galaxies having relatively low HMXB obscuration and young and X-ray luminous stellar populations. The elevation of the hot gas scaling relation is at the level expected for diminished attenuation due to a reduction of metals; however, we cannot conclude that an L^(gas)_(0.5-2keV) -SFR-Z relation is driven solely by changes in ISM metal content. Finally, we present SFR-scaled spectral models (both emergent and intrinsic) that span the X-ray-to-IR band, providing new benchmarks for studies of the impact of ISM ionization and IGM heating in the early universe.

high-mass x-ray binary stars↗
NASA NTRS2023

JWST Observations of the Enigmatic Y Dwarf WISE 1828+2650: I. Limits to a Binary Companion

The Y-dwarf WISE 1828+2650 is one of the coldest known Brown Dwarfs with an effective temperature of ~300 K. Located at a distance of just 10 pc, previous model-based estimates suggest WISE 1828+2650 has a mass of ~5-10 M J , making it a valuable laboratory for understanding the formation, evolution and physical characteristics of gas giant planets. However, previous photometry and spectroscopy have presented a puzzle with the near-impossibility of simultaneously fitting both the short (0.9-2.0 μm) and long wavelength (3-5 μm) data. A potential solution to this problem has been the suggestion that WISE 1828+2650 is a binary system whose composite spectrum might provide a better match to the data. Alternatively, new models being developed to fit JWST/NIRSpec and MIRI spectroscopy might provide new insights. This article describes JWST/NIRCam observations of WISE 1828+2650 in 6 filters to address the binarity question and to provide new photometry to be used in model fitting. We also report Adaptive Optics imaging with the Keck 10 m telescope. We find no evidence for multiplicity for a companion beyond 0.5 AU with either JWST or Keck. Companion articles will present low and high resolution spectra of WISE 1828 obtained with both NIRSpec and MIRI.

Infrared spectroscopy↗
DOE OSTI2022

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC 71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling–intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. Finally, this work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

14 SOLAR ENERGY↗
DOE OSTI2024

Quantifying Epistemic Uncertainty in Binary Classification via Accuracy Gain

ABSTRACT Recently, a surge of interest has been given to quantifying epistemic uncertainty (EU), the reducible portion of uncertainty due to lack of data. We propose a novel EU estimator in the binary classification setting, as the posterior expected value of the empirical gain in accuracy between the current prediction and the optimal prediction. In order to validate the performance of our EU estimator, we introduce an experimental procedure where we take an existing dataset, remove a set of points, and compare the estimated EU with the observed change in accuracy. Through real and simulated data experiments, we demonstrate the effectiveness of our proposed EU estimator.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Binary optimal control by trust-region steepest descent

Abstract We present a trust-region steepest descent method for dynamic optimal control problems with binary-valued integrable control functions. Our method interprets the control function as an indicator function of a measurable set and makes set-valued adjustments derived from the sublevel sets of a topological gradient function. By combining this type of update with a trust-region framework, we are able to show by theoretical argument that our method achieves asymptotic stationarity despite possible discretization errors and truncation errors during step determination. To demonstrate the practical applicability of our method, we solve two optimal control problems constrained by ordinary and partial differential equations, respectively, and one topological optimization problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High dimensional binary classification under label shift: phase transition and regularization

Label Shift has been widely believed to be harmful to the generalization performance of machine learning models. Researchers have proposed many approaches to mitigate the impact of the label shift, e.g., balancing the training data. However, these methods often consider the underparametrized regime, where the sample size is much larger than the data dimension. The research under the overparametrized regime is very limited. Here, to bridge this gap, we propose a new asymptotic analysis of the Fisher Linear Discriminant classifier for binary classification with label shift. Specifically, we prove that there exists a phase transition phenomenon: Under certain overparametrized regime, the classifier trained using imbalanced data outperforms the counterpart with reduced balanced data. Moreover, we investigate the impact of regularization to the label shift: The aforementioned phase transition vanishes as the regularization becomes strong.

binary classification↗
DOE OSTI2023

Barrier-free predictions of short-range ordering/clustering kinetics in binary FCC solid solutions

We present comparisons of kinetic Monte Carlo (kMC) simulations of isothermal short-range ordering (SRO) and clustering (SRC) kinetics in binary FCC alloys with a mean-field concentration wave (CW) model. We find that the CW model is able to give order-of-magnitude agreement with kMC simulations for ordering/clustering relaxation times over a wide range of temperatures and compositions. The advantage of the CW model is that it does not require parameterization of vacancy hopping energy barriers, which, for a concentrated alloy, becomes prohibitive. We assess limits in the accuracy of the model and discuss the effect of cooling rates as well as the extension to multi-component systems. Ultimately, the simplicity and performance of the CW model compared to kMC simulations suggests that it is a useful tool to connect with models of properties dependent on SRO/SRC as well as for designing thermal treatments to control formation of SRO/SRC.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The repulsive Casimir-type forces in binary mixture of weakly interacting Bose–Einstein condensates gases

Highlights: • The equations of the state of a binary mixture weakly interacting Bose gases are established based on the Lagrangian of the system. • The formulae of the Casimir-type energy and the resulting Casimir-type force are produced from the quantum part of the grand canonical energy. • The results for the Casimir-type effect in the one-field case can be re-obtained by using the results of the two-field case. Within the framework of the quantum field theory (QFT) in the one-loop approximation, we investigate the Casimir-type effect in a mixture of two-component weakly interacting Bose-Einstein condensates (BECs) gases confined between two parallel plates at zero temperature. The Casimir-type forces in the miscible state of BECs for different boundary conditions (BCs) are discovered and compared to each other. The repulsive nature of the Casimir-type force in BECs is defined for the first time. Our calculations are finished in both grand canonical ensemble (GCE) and canonical ensemble (CE).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Solubility-Dependent Protective Effects of Binary Alloys for Lithium Anode

Recently, alloys have been widely utilized as protection layers for homogenized Li growth. However, the protective mechanisms for different alloys are not clearly understood. In this work, guided by the binary phase diagrams, Mg, Au, Zn, Al, Fe, and Cu protective layers have been selected for study of their protective abilities and mechanisms. The selected metals can be classified into three categories according to the nature of their associated alloy protective layers: (1) metals with high solubility in Li while not forming any intermediate line compounds, e.g., Mg, which is good for fast Li stripping; (2) metals with limited solid solubility but forming stable line compounds with Li upon the lithiation, e.g., Au, Zn, and Al, where the formed stable line compounds Li x Au, Li x Zn, and Li x Al will hamper Li kinetics; (3) metals with negligible mutual solubility and no line compound formation with Li, e.g., Fe and Cu, which block the Li stripping path and therefore result in the highest polarization voltage.

25 ENERGY STORAGE↗
DOE OSTI2024

Binary Cation Matrix Electrolyte and Its Effect on Solid Electrolyte Interphase Suppression and Evolution of Si Anode

An unstable solid electrolyte interphase (SEI) has been recognized as one of the biggest challenges to commercializing silicon (Si) anodes for high-energy-density batteries. This work thoroughly investigates a binary cation matrix of Mg 2+ +Li + electrolyte and its role in SEI development, suppression, and evolution of a Si anode. Findings demonstrate that introducing Mg ions dramatically reduces the SEI growth before lithiation occurs, primarily due to the suppression of solvent reduction, particularly ethylene carbonate (EC) reduction. The Mg 2+ alters the Li + cation solvation environment as EC preferably participates in the oxophyllic Mg 2+ solvation sheath, thereby altering the solvent reduction process, resulting in a distinct SEI formation mechanism. The initial SEI formation before lithiation is reduced by 70% in the electrolyte with the presence of Mg 2+ cations. While the SEI continues to develop in the postlithiation, the inclusion of Mg ions results in an approximately 80% reduction in the postlithiation SEI growth. Continuous electrochemical cycling reveals that Mg 2+ plays a crucial role in stabilizing the deep-lithiated Si phases, which effectively mitigates side reactions, resulting in controlled SEI growth and stable interphase while eliminating complex Li x Si y formation. Mg ions promote the development of a notably more rigid and homogeneous SEI, characterized by a reduced dissipation (ΔD) in the Mg 2+ +Li + ion matrix compared to the solely Li + system. In conclusion, this report reveals how the Mg 2+ +Li + ion matrix affects the SEI evolution, viscoelastic properties, and electrochemical behavior at the Si interface in real time, laying the groundwork for devising strategies to enhance the performance and longevity of Si-based next-generation battery systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Dust and gas absorption in the high mass X-ray binary IGR J16318-4848

With an absorption column density on the order of 10 24 cm -2 , IGR J16318-4848 is one of the most extreme cases of a highly obscured high mass X-ray binary. In addition to the overall continuum absorption, the source spectrum exhibits a strong iron and nickel fluorescence line complex at 6.4 keV. Previous empirical modeling of these features and comparison with radiative transfer simulations raised questions about the structure and covering fraction of the absorber and the profile of the fluorescence lines. We aim at a self-consistent description of the continuum absorption, the absorption edges, and the fluorescence lines to constrain the properties of the absorbing material, such as ionization structure and geometry. We further investigate the effects of dust absorption on the observed spectra and the possibility of fluorescence emission from dust grains. We used XMM-Newton and NuSTAR spectra to first empirically constrain the incident continuum and fluorescence lines. Next we used XSTAR to construct a customized photoionization model where we vary the ionization parameter, column density, and covering fraction. In the third step we modeled the absorption and fluorescence in a dusty olivine absorber and employed both a simple analytical model for the fluorescence line emission and a Monte Carlo simulation of radiative transfer that generates line fluxes, which are very close to the observational data. Our empirical spectral modeling is in agreement with previous works. Our second model, the single gas absorber does not describe the observational data. In particular, irrespective of the ionization state or column density of the absorber, a much higher covering fraction than previously estimated is needed to produce the strong fluorescence lines and the large continuum absorption. A dusty, spherical absorber (modeled as consisting of olivine dust, although the nature of dust cannot be constrained) is able to produce the observed continuum absorption and edges. A dense, dusty absorber in the direct vicinity of the source consisting of dust offers a consistent description of both the strong continuum absorption and the strong emission features in the X-ray spectrum of IGR J16318-4848. In particular, for low optical depth of individual grains, which is the case for typical volume densities and grain size distribution models, the dust will contribute significantly to the fluorescence emission.

79 ASTRONOMY AND ASTROPHYSICS↗