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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Probing the Incompressibility of Nuclear Matter at Ultrahigh Density through the Prompt Collapse of Asymmetric Neutron Star Binaries

Using 250 neutron star merger simulations with microphysics, we explore for the first time the role of nuclear incompressibility in the prompt collapse threshold for binaries with different mass ratios. We demonstrate that observations of prompt collapse thresholds, either from binaries with two different mass ratios or with one mass ratio but combined with the knowledge of the maximum neutron star mass or compactness, will constrain the incompressibility at the maximum neutron star density K max to within tens of percent. This otherwise inaccessible measure of K max can potentially reveal the presence of hyperons or quarks inside neutron stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Designing defect-based qubit candidates in wide-gap binary semiconductors for solid-state quantum technologies

We report that the development of novel quantum bits is key to extending the scope of solid-state quantum-information science and technology. Using first-principles calculations, we propose that large metal ion–vacancy pairs are promising qubit candidates in two binary crystals: 4H-SiC and w-AlN. In particular, we found that the formation of neutral Hf- and Zr-vacancy pairs is energetically favorable in both solids; these defects have spin-triplet ground states, with electronic structures similar to those of the diamond nitrogen-vacancy center and the SiC divacancy. Interestingly, they exhibit different spin-strain coupling characteristics, and the nature of heavy metal ions may allow for easy defect implantation in desired lattice locations and ensure stability against defect diffusion. To support future experimental identification of the proposed defects, we report predictions of their optical zero-phonon line, zero-field splitting, and hyperfine parameters. Lastly, the defect design concept identified here may be generalized to other binary semiconductors to facilitate the exploration of new solid-state qubits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Generalized master equation for particle transport in binary random media with renewal statistics

Particle transport in binary stochastic mixtures is classically modeled assuming Markovian or exponential mixing statistics but in many applications material memory invalidates the Markov assumption. For non-Markovian mixing characterized by alternating renewal processes, a transport-theoretic framework is presented that provides an exact description of transport in nonscattering random binary media with general non-exponential statistics. Our approach is to Markovianize the problem by augmenting the {material type, particle flux} state space with the age or distance from the last interface. A Chapman-Kolmogorov equation is formulated for the joint probability density of the material type, particle flux, and age, and subsequently reduced to a generalized Master equation (GME) in differential form. This constitutes the primary result of this work. A state-updating Monte Carlo algorithm consistent with the GME is developed and benchmarked against analytical solutions for multiple chord-length laws. For purely absorbing renewal statistical media, the GME reproduces analytical benchmarks for the equilibrium age distribution, interior mean/variance of material-conditioned fluxes, and boundary transmittance. Simulations further demonstrate that a Markov (exponential) approximation of non-exponential statistics can introduce large errors in transmittance and interior flux profiles. Lastly, the reintroduction of memory due to scattering is briefly addressed through heuristic considerations.

Fluctuations & noise↗
DOE OSTI2026

Magnetic flux emergence in binary neutron star remnants

Using high-resolution AthenaK simulations of a twisted toroidal flux tube, we study the flux emergence of magnetic structures in the shear layer of a hot massive neutron star typical of a binary neutron star remnant. High-resolution simulations demonstrate that magnetic buoyant instabilities allow for emergence only for extremely large magnetic fields significantly exceeding 10 17 G, and more typical fields around 10 16 G are instead dominated by hydrodynamic effects. Because merger remnants tend to be stable against hydrodynamic convection, our work places strong limitations on the mechanisms by which massive binary neutron star remnants can produce the magnetically-driven outflows needed to power jets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Variation Tolerant and Energy-Efficient Charge Domain Compute-in-Memory Array with Binary and Multi-Level Cell Ferroelectric FET

Here, in this work, we present a variation-tolerant and energy-efficient charge-domain Ferroelectric FET (FeFET) based Compute-in-Memory (CiM) array design that is compatible with both binary and multi-level cell memory sensing. We demonstrate that: 1) by exploiting FeFET as a nonvolatile switch, its high ON/OFF ratio in the subthreshold region can suppress the error introduced by the inaccurate ON state conductance, thus realizing robust CiM operations, unlike the current-domain CiM design where the computation results is highly sensitive to the device conductance variation; 2) by leveraging a dense dynamic random access memory (DRAM)-like 1FeFET1C cell structure, the proposed design benefits from the existing high density DRAM establishment while also significantly relaxing the capacitor retention and transistor leakage requirement; 3) the charge-domain CiM supports both binary FeFET with minimum overhead and MLC FeFET with tolerable latency for MLC state sensing, whose efficacy is validated experimentally on both cell-level and array-level; 4) the proposed CiM shows much better device variation resilience than conventional current-domain CiM, and also improves inference accuracy. Macro-level evaluation results demonstrate significantly higher energy efficiency and area efficiency compared to prior CiM works.

Duan, Jiahui [University of Notre Dame, IN (United↗
DOE OSTI2017

Hashed Binary Search Sampling for Convolutional Network Training with Large Overhead Image Patches

Very large overhead imagery associated with ground truth maps has the potential to generate billions of training image patches for machine learning algorithms. However, random sampling selection criteria often leads to redundant and noisy-image patches for model training. With minimal research efforts behind this challenge, the current status spells missed opportunities to develop supervised learning algorithms that generalize over wide geographical scenes. In addition, much of the computational cycles for large scale machine learning are poorly spent crunching through noisy and redundant image patches. We demonstrate a potential framework to address these challenges specifically, while evaluating a human settlement detection task. A novel binary search tree sampling scheme is fused with a kernel based hashing procedure that maps image patches into hash-buckets using binary codes generated from image content. The framework exploits inherent redundancy within billions of image patches to promote mostly high variance preserving samples for accelerating algorithmic training and increasing model generalization.

Lunga, Dalton↗
DOE OSTI2021

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers

Neuromorphic computers offer the opportunity for low-power, efficient computation. Though they have been primarily applied to neural network tasks, there is also the opportunity to leverage the inherent characteristics of neuromorphic computers (low power, massive parallelism, collocated processing and memory) to perform non-neural network tasks. Here, we demonstrate how an approach for performing sparse binary matrix-vector multiplication on neuromorphic computers. We describe the approach, which relies on the connection between binary matrix-vector multiplication and breadth first search, and we introduce the algorithm for performing this calculation in a neuromorphic way. We validate the approach in simulation. Finally, we provide a discussion of the runtime of this algorithm and discuss where neuromorphic computers in the future may have a computational advantage when performing this computation.

Schuman, Catherine↗
DOE OSTI2019

Polaritons of Triplet and Binary Hybrid Structures in a Microcavity

We analyze the properties of a triplet hybrid (semiconductor—organic layer–semiconductor) in a microcavity. Analysis is performed for excitation energies reduced in the triplet from the Wannier–Mott exciton with the highest energy to the Frenkel exciton with an intermediate energy and from the Frenkel exciton to the Wannier–Mott exciton with the lowest energy. The semiconductor components of the hybrid have the form of thin nanofilms; the organic component is represented by the layer of a finite thickness smaller than the diffusion length of the Frenkel exciton. We analyze the frequency dependence of polaritons formed during the general hybridization of the Wannier–Mott excitons, the Frenkel exciton, and the fundamental model of the microcavity. We have obtained the dispersion dependences of polaritons of reduced binary hybrids and the organic layer in the microcavity. Our results can be of interest for studying the energy transfer kinetics with a multiple change in the form of energy in triplet and binary hybrid systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Inter atomic force constants of binary and ternary tetrahedral semiconductors

In this paper, we present the expressions relating the inter atomic force constants like as bond-stretching force constant (α in N/m) and bond-bending force constant (β in N/m) for the binary (zinc blende structure) and ternary (chalcopyrite structure) semiconductors with the product of ionic charges (PIC) and crystal ionicity (f{sub i}). Interatomic force constants of these compounds exhibit a linear relationship; when plot a graph between Interatomic force constants and the nearest neighbor distance d (Å) with crystal ionicity (f{sub i}), but fall on different straight lines according to the product of ionic charges of these compounds. A fairly good agreement has been found between the observed and calculated values of the α and β for binary and ternary tetrahedral semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Electrical properties and transport mechanisms in phase change memory thin films of quasi-binary-line GeTe–Sb{sub 2}Te{sub 3} chalcogenide semiconductors

The temperature dependences of the resistivity and current–voltage (I–V) characteristics of phase change memory thin films based on quasi-binary-line GeTe–Sb{sub 2}Te{sub 3} chalcogenide semiconductors Ge{sub 2}Sb{sub 2}Te{sub 5}, GeSb{sub 2}Te{sub 5}, and GeSb{sub 4}Te{sub 7} are investigated. The effect of composition variation along the quasibinary line on the electrical properties and transport mechanisms of the thin films is studied. The existence of three ranges with different I–V characteristics is established. The position and concentration of energy levels controlling carrier transport are estimated. The results obtained show that the electrical properties of the thin films can significantly change during a shift along the quasi-binary line GeTe–Sb{sub 2}Te{sub 3}, which is important for targeted optimization of the phase change memory technology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Relaxation of Vibrationally Excited States in Solid Binary Carbonate-Sulfate Systems

The processes of molecular relaxation in solid binary carbonate-sulfate systems, such as Li{sub 2}CO{sub 3}-Li{sub 2}SO{sub 4}, Na{sub 2}CO{sub 3}-Na{sub 2}SO{sub 4}, K{sub 2}CO{sub 3}-K{sub 2}SO{sub 4}, have been studied by Raman spectroscopy. It has been revealed that the relaxation time of CO{sub 3}{sup 2-} anion vibration ν{sub 1}(A) in a binary system is higher than in an individual carbonate. It is shown that an increase in the relaxation rate may be explained by the existence of an additional mechanism of the relaxation of vibrationally excited states of a carbonate anion. This mechanism is associated with the excitation of the vibration of another anion (SO{sub 4}{sup 2-}) and the “birth” of a lattice phonon. It has been established that the condition for the implementation of such a relaxation mechanism is that the difference between the frequencies of these vibrations must correspond to the region of a rather high density of phonon spectrum states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Binary Phase SLMs Based on the LC Matrix of Video Projector

Binary phase modulation is demonstrated with the aid of commercially available LC matrix. Elements of plane diffraction optics (cylindrical and spherical lenses) are fabricated and experimentally studied. Limitations related to a finite size of a pixel of a binary diffraction SLM are considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Neutrino emission from binary neutron star mergers: characterising light curves and mean energies

Abstract Neutrinos are copiously emitted by neutron star mergers, due to the high temperatures reached by dense matter during the merger and its aftermath. Neutrinos influence the merger dynamics and shape the properties of the ejecta, including the resulting r -process nucleosynthesis and kilonova emission. In this work, we analyse neutrino emission from a large sample of binary neutron star merger simulations in Numerical Relativity, covering a broad range of initial masses, nuclear equation of state and viscosity treatments. We extract neutrino luminosities and mean energies, and compute quantities of interest such as the peak values, peak broadnesses, time averages and decrease time scales. We provide a systematic description of such quantities, including their dependence on the initial parameters of the system. We find that for equal-mass systems the total neutrino luminosity (several $$10^{53}{\hbox {erg}~{\hbox {s}}^{-1}}$$ 10 53 erg s - 1 ) decreases as the reduced tidal deformability increases, as a consequence of the less violent merger dynamics. Similarly, tidal disruption in asymmetric mergers leads to systematically smaller luminosities. Peak luminosities can be twice as large as the average ones. Electron antineutrino luminosities dominate (initially by a factor of 2-3) over electron neutrino ones, while electron neutrinos and heavy flavour neutrinos have similar luminosities. Mean energies are nearly constant in time and independent on the binary parameters. Their values reflect the different decoupling temperature inside the merger remnant. Despite present uncertainties in neutrino modelling, our results provide a broad and physically grounded characterisation of neutrino emission, and they can serve as a reference point to develop more sophisticated neutrino transport schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code

Highly optimized programs are prone to bit rot, where performance quickly becomes suboptimal in the face of new hardware and compiler techniques. In this paper we show how to automatically lift performance-critical stencil kernels from a stripped x86 binary and generate the corresponding code in the high-level domain-specific language Halide. Using Halide's state-of-the-art optimizations targeting current hardware, we show that new optimized versions of these kernels can replace the originals to rejuvenate the application for newer hardware. The original optimized code for kernels in stripped binaries is nearly impossible to analyze statically. Instead, we rely on dynamic traces to regenerate the kernels. We perform buffer structure reconstruction to identify input, intermediate and output buffer shapes. Here, we abstract from a forest of concrete dependency trees which contain absolute memory addresses to symbolic trees suitable for high-level code generation. This is done by canonicalizing trees, clustering them based on structure, inferring higher-dimensional buffer accesses and finally by solving a set of linear equations based on buffer accesses to lift them up to simple, high-level expressions. Helium can handle highly optimized, complex stencil kernels with input-dependent conditionals. We lift seven kernels from Adobe Photoshop giving a 75 % performance improvement, four kernels from Irfan View, leading to 4.97 x performance, and one stencil from the mini GMG multigrid benchmark netting a 4.25 x improvement in performance. We manually rejuvenated Photoshop by replacing eleven of Photoshop's filters with our lifted implementations, giving 1.12 x speedup without affecting the user experience.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Factorization of Binary Matrices: Rank Relations, Uniqueness and Model Selection of Boolean Decomposition

The application of binary matrices are numerous. Representing a matrix as a mixture of a small collection of latent vectors via low-rank decomposition is often seen as an advantageous method to interpret and analyze data. In this work, we examine the factorizations of binary matrices using standard arithmetic (real and nonnegative) and logical operations (Boolean and $\mathbb{Z}$ 2 ). We examine the relationships between the different ranks, and discuss when factorization is unique. In particular, we characterize when a Boolean factorization X = W$\land$H has a unique W, a unique H (for a fixed W), and when both W and H are unique, given a rank constraint. We introduce a method for robust Boolean model selection, called BMFk, and show on numerical examples that BMFk not only accurately determines the correct number of Boolean latent features but reconstruct the pre-determined factors accurately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Analysis of the Conformally Flat Approximation for Binary Neutron Star Initial Conditions

The spatially conformally flat approximation (CFA) is a viable method to deduce initial conditions for the subsequent evolution of binary neutron stars employing the full Einstein equations. Here in this paper, we analyze the viability of the CFA for the general relativistic hydrodynamic initial conditions of binary neutron stars. We illustrate the stability of the conformally flat condition on the hydrodynamics by numerically evolving ~100 quasicircular orbits. We illustrate the use of this approximation for orbiting neutron stars in the quasicircular orbit approximation to demonstrate the equation of state dependence of these initial conditions and how they might affect the emergent gravitational wave frequency as the stars approach the innermost stable circular orbit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗
DOE OSTI2024

Binary Quantum Control Optimization with Uncertain Hamiltonians

Optimizing the controls of quantum systems plays a crucial role in advancing quantum technologies. The time-varying noises in quantum systems and the widespread use of inhomogeneous quantum ensembles raise the need for high-quality quantum controls under uncertainties. In this paper, we consider a stochastic discrete optimization formulation of a discretized binary optimal quantum control problem involving Hamiltonians with predictable uncertainties. We propose a sample-based reformulation that optimizes both risk-neutral and risk-averse measurements of control policies, and solve these with two gradient-based algorithms using sum-up-rounding approaches. Furthermore, we discuss the differentiability of the objective function and prove upper bounds of the gaps between the optimal solutions to binary control problems and their continuous relaxations. We conduct numerical simulations on various sized problem instances based on two applications of quantum pulse optimization; we evaluate different strategies to mitigate the impact of uncertainties in quantum systems. In conclusion, we demonstrate that the controls of our stochastic optimization model achieve significantly higher quality and robustness compared with the controls of a deterministic model.

conditional value-at-risk (CVaR)↗