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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
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)↗
DOE OSTI2018

Direct binary search for improved coherent beam shaping and optical differentiation wavefront sensing

Spatially dithered distributions of binary amplitude pixels are optimized using a full direct binary search taking into account the experimental configuration for amplitude modulation of coherent waves. This design process is shown to yield a significant reduction of the noise induced by binarization and pixelation over the region of interest. In this study, we demonstrate this approach for beam shaping and optical differentiation wavefront sensing, where the region of interest is in an image plane of the pixel distribution and in the far field of the pixel distribution, respectively. Lastly, the observed reduction in error compared to a standard error diffusion algorithm is significant for both applications because it improves performance without the tighter fabrication tolerance and cost associated with smaller pixels.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Crystal Structures of Group B Streptococcus Glyceraldehyde-3-Phosphate Dehydrogenase: Apo-Form, Binary and Ternary Complexes

Glyceraldehyde 3-phosphate dehydrogenase or GAPDH is an evolutionarily conserved glycolytic enzyme. It catalyzes the two step oxidative phosphorylation of D-glyceraldehyde 3-phosphate into 1,3-bisphosphoglycerate using inorganic phosphate and NAD + as cofactor. GAPDH of Group B Streptococcus is a major virulence factor and a potential vaccine candidate. Moreover, since GAPDH activity is essential for bacterial growth it may serve as a possible drug target. Crystal structures of Group B Streptococcus GAPDH in the apo-form, two different binary complexes and the ternary complex are described here. The two binary complexes contained NAD + bound to 2 (mixed-holo) or 4 (holo) subunits of the tetrameric protein. The structure of the mixed-holo complex reveals the effects of NAD + binding on the conformation of the protein. In the ternary complex, the phosphate group of the substrate was bound to the new Pi site in all four subunits. Comparison with the structure of human GAPDH showed several differences near the adenosyl binding pocket in Group B Streptococcus GAPDH. The structures also reveal at least three surface-exposed areas that differ in amino acid sequence compared to the corresponding areas of human GAPDH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Establishing Malware Attribution and Binary Provenance Using Multicompilation Techniques

Malware is a serious problem for computer systems and costs businesses and customers billions of dollars a year in addition to compromising their private information. Detecting malware is particularly difficult because malware source code can be compiled in many different ways and generate many different digital signatures, which causes problems for most anti-malware programs that rely on static signature detection. Our project uses a convolutional neural network to identify malware programs but these require large amounts of data to be effective. Towards that end, we gather thousands of source code files from publicly available programming contest sites and compile them with several different compilers and flags. Building upon current research, we then transform these binary files into image representations and use them to train a long-term recurrent convolutional neural network that will eventually be used to identify how a malware binary was compiled. This information will include the compiler, version of the compiler and the options used in compilation, information which can be critical in determining where a malware program came from and even who authored it.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

BUILD: Binary Understanding and Integration Logic for Dependencies (Final Report)

Increasingly diverse mission needs, the emergence of AI and cloud, and increasing hardware diversity are driving HPC software to be more complex. Modern codes are built from hundreds of small, complex components, and much of the software development process involves integrating these components rather than developing new components from scratch. The goal of the BUILD project was to ease the task of software integration for developers across LLNL’s programs. The project focused on (1) modeling software compatibility, (2) modeling ABI compatibility with binary analysis, (3) developing solver techniques to reason about compatibility, and (4) developing AI/ML models to fill gaps in our understanding of software compatibility. The project has developed several key technologies that help developers—by accelerating development workflows, removing the need for rebuilds, and enabling faster, automatic, and less error-prone code sharing. These technologies are used in LLNL codes and will be ready for the new El Capitan Exascale system in Livermore Computing. Many of these technologies have been hardened and integrated with LLNL’s Spack package manager, and they are already in use by production code teams. Results of BUILD have laid the groundwork for future advances in software integration—the ML and binary modification techniques developed in this project still need to be operationalized but have great potential to further speed up software integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A New Vehicle-to-Vehicle Communication Technology Based on Binary Light Code

The proliferation of Connected and Autonomous Vehicles (CAVs) has necessitated the development of efficient, reliable communication methods between vehicles and their surroundings. This study presents a novel methodology, the VECTOR system, that addresses this need by converting dynamic vehicle data into a binary code and displaying it on an LED panel. The system involves a three-step process of data collection, polynomial fitting of velocity data, and encoding the polynomial parameters into binary form using a Cyclic Redundancy Check (CRC). The study also explores the practical application of this system by conducting experiments with modified Lincoln MKZ hybrids, demonstrating the feasibility and efficiency of this approach. The paper presents both the methodology and results of these experiments, further expanding upon the potential applications and implications for CAV technology. By comparing the final accuracy, we find this approach can achieve 80% of the original velocity data.

Ma, Ke↗
DOE OSTI2024

Harnessing photoautotroph-methanotroph interactions for biogas conversion to fuels and chemicals using binary consortia (Project Final Technical Report)

Industrial, municipal, and agricultural waste streams containing stranded organic carbon represent a significant and underutilized feedstock to produce fuels and chemicals. With anaerobic digestion deployed at large scales to capture organic waste streams, over 6 million tons of biogas are available today. However, the utilization of biogas represents a significant challenge due to its low pressure and presence of contaminants such as H 2 S, ammonia, and volatile organic carbon compounds. To tap into this immense potential, effective biotechnologies that co-utilize both CO 2 and CH 4 are needed. Recent studies demonstrated that, in nature, microbial communities have developed a highly efficient way to recover energy and capture carbon from both CH 4 and CO 2 through metabolic coupling of methane oxidation to oxygenic photosynthesis. Using two synthetic methanotroph – photoautotroph (M-P) co-cultures that exhibit stable growth under a broad range of cultivation conditions, in this project we proposed to harness the interspecies interactions within these cocultures for biogas conversion to fuels and chemicals. To facilitate this overarching objective, we aim to develop experimental and computational tools to gain qualitative and quantitative understandings on the interactions and dynamics of the coculture at both systems and molecular levels, and to validate our findings through experiments and mutant development. The fundamental understanding on the interactions and dynamics of the photoautotroph-methanotroph will lay the foundation for the design and optimization of synthetic binary consortia for production of fuels and chemicals from biogas. We expect the knowledge gained from this project may be generally applicable to other cross-feeding binary consortium, and the tools developed can be adapted to study the interactions and dynamics of other multi-organism platforms.

09 BIOMASS FUELS↗
DOE OSTI2016

Remnant Masses and Compact Binary Mergers

Compact binary mergers are rare events in the universe, but produce many of the brightest observed outbursts observed today. In addition, these mergers play an important role in the production of heavy elements, perhaps dominating the r-process nucleosynthesis as well as iron-peak elements. These mergers are also strong sources of gravitational waves and, if understand fully, can tie gravitational wave measurements to the understanding of matter at extreme conditions. One of the major uncertainties in our understanding of compact remnant mergers is the mass distribution. The mass distribution can help determine the relative rates of different compact binary mergers. Here I review our current understanding of the formation processes behind compact systems, focusing on the mass distribution of these objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Binary Control Pulse Optimization for Quantum Systems

Quantum control aims to manipulate quantum systems toward specific quantum states or desired operations. Designing highly accurate and effective control steps is vitally important to various quantum applications, including energy minimization and circuit compilation. In this paper we focus on discrete binary quantum control problems and apply different optimization algorithms and techniques to improve computational efficiency and solution quality. Specifically, we develop a generic model and extend it in several ways. We introduce a squared L 2 -penalty function to handle additional side constraints, to model requirements such as allowing at most one control to be active. We introduce a total variation (TV) regularizer to reduce the number of switches in the control. We modify the popular gradient ascent pulse engineering (GRAPE) algorithm, develop a new alternating direction method of multipliers (ADMM) algorithm to solve the continuous relaxation of the penalized model, and then apply rounding techniques to obtain binary control solutions. We propose a modified trust-region method to further improve the solutions. Our algorithms can obtain high-quality control results, as demonstrated by numerical studies on diverse quantum control examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗