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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗
DOE OSTI2016

Transport and Clogging of Particulate Flow in Fracture Systems

The aim of the project is to understand the effects of confinement in narrow rough-walled fractures on the transport behavior of fluids and suspended particles in subsurface hydro- carbon reservoirs. A key motivation for the study is that such fracture systems provide the highest throughput in oil and gas extraction and have been the focus of recent industrial activity. The scientific challenge is to understand how the confined geometry alters transport phenomena, and in particular its influence on (diagnostic) tracer transport and the effects of flow channeling and clogging on fluid motion. An important complicating feature of geological fractures is the self-affine fractal nature of their surface roughness, leading to irregular but correlated fluid and particle motion. The key technique used is computer simulation, augmented by analytical calculations and collaboration with outside experimental colleagues when possible. The principal topics studied were fluid permeability, tracer dispersion, flow channeling and anisotropy, particle transport in narrow channels and particle trapping in tight fractures.

58 GEOSCIENCES↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Field-induced transitions in the Kitaev material α - RuCl 3 probed by thermal expansion and magnetostriction

High-resolution thermal expansion and magnetostriction measurements were performed on single crystals of α - RuCl 3 in magnetic fields applied parallel to the Ru-Ru bonds. The length changes were measured in the direction perpendicular to the honeycomb planes. Here, our data show clear thermodynamic characteristics for the field-induced phase transition at the critical field μ 0 H c 1 = 7.8 ( 2 ) T where the antiferromagnetic zigzag order is suppressed. At higher fields, a kink in the magnetostriction coefficient signals an additional transition or crossover around μ 0 H c 2 ≈ 11 T . The extracted Grüneisen ratio shows typical hallmarks for quantum criticality near H c 1 but also displays anomalous behavior above H c 1 . We compare our experimental data with spin-wave calculations employing a minimal Kitaev-Heisenberg model in the semiclassical limit. Most of the salient features are in agreement with each other, however, the peculiar features in the region above H c 1 cannot be accounted for in our semiclassical modeling and hence suggest a genuine quantum nature. We construct a phase diagram for α - RuCl 3 in a magnetic field along the Ru-Ru bonds, displaying a zigzag ordered state below H c 1 , a quantum paramagnetic regime between H c 1 and H c 2 , and a semiclassical partially polarized state above H c 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Extracting $B_s\to D_s^*\ellν_\ell$ form factors

Semileptonic $B_{(s)}$ decays are of great phenomenological interest because they allow to determine e.g. CKM matrix elements or test lepton flavor universality. Taking advantage of already existing lattice data, we demonstrate the analysis steps to extract the four form factors describing exclusive semileptonic $B_s\to D_s^*\ellν_\ell$ decays using the narrow width approximation. Our data are based on RBC/UKQCD's set of 2+1 flavor gauge field ensembles with Shamir domain-wall fermion and Iwasaki gauge field action featuring inverse lattice spacings of $a^{-1}=$1.785, 2.383, and 2.785 GeV as well as pion masses between 268 and 433 MeV. Light, strange and charm quarks are simulated using domain-wall fermions, whereas bottom quarks are generated with the relativistic heavy quark (RHQ) action.

Boushmelev, Anastasia [Siegen U.] (ORCID:000000033↗
DOE OSTI2019

Tunable photonic crystal wavelength sampler with response in terahertz frequency range

Optical features of novel one dimensional photonic crystals with response in the terahertz frequency range are studied theoretically by outlining the transfer matrix method. Dependence of the ideal crystal reflectance to the size of the alternating SiO{sub 2} and InSb layers are studied systematically at the first step. Extracting the optimum values in which large photonic band gaps (PBGs) appear in the reflectance spectrum, two more defective structures are proposed by benefiting the electro-optical behaviors of Li:NbO{sub 3} crystal. Taking into account of the reflection alterations, tunability of the crystals’ response by the wave incident angle, external bias voltage applied to the defect layer(s) and the wave polarization is further studied. Results show that PBGs and resonant modes inside them are strongly dependent to all these controlling factors besides the dependence to the structural parameters. But however, to some extent different modes have different behaviors. The proposed crystals may satisfy the growing demands for development of the high speed photonic devices in the terahertz frequency range and have great potentials for applications such as tunable wavelength samplers/filters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Prediction of O and OH Adsorption on Transition Metal Oxide Surfaces from Bulk Descriptors

In the search for stable and active catalysts, density functional theory and machine learning (ML) based models can accelerate the screening of materials. While stability is conveniently addressed on the bulk level of computation, the modelling of catalytic activity requires expensive surface simulations. Here, in this work, we develop models for the surface adsorption energy of O and OH intermediates across a consistent and extensive dataset of pure transition metal oxide surfaces. We show that adsorption energies across metal oxidation states of +2 to +6 are well captured from the metal-oxygen bond strength extracted from the bulk level calculation. Specifically, we calculate the integrated crystal orbital Hamiltonian population (ICOHP) of the metal-oxygen bond in the bulk oxide and employ a simple normalization scheme to obtain a strong correlation with adsorption energetics. By combining our ICOHP descriptor with non DFT features in a Gaussian Process regression (GPR) model, we achieve high model accuracy with mean absolute errors of 0.166 and 0.219 eV for OH and O adsorption, respectively. By targeting the O-OH adsorption energy difference with our GPR model, we predict the the oxygen evolution reaction (OER) activity from bulk descriptors only. Furthermore, we utilize the strong correlation between the COHP and metal oxygen bond lengths to rapidly predict adsorption energetics and catalytic activity from the optimized bulk geometry. Our approach can enable an efficient search for active catalysts by eliminating the need for surface calculations in the initial screening phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Single-shot femtosecond laser-induced breakdown spectroscopy in low-density gases

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has been used to interrogate low-density gases of H 2 ⁠, CH 4 ⁠, CO 2 ⁠, and H 2 O ranging from 0.5 × 10 15 to 9.1 × 10 15 cm −3 (15–275 mTorr). Strong spectral signatures were observed above the noise baseline for each test gas at all densities considered. Unique molecular signatures were observed for both CH 4 and CO 2 along with atomic features for each gas. The LIBS intensity response with respect to density was determined for each species using Voigt lineshape fitting or numerical integration. Finally, the collection and analysis of LIBS spectra of composite mixtures of CH 4 –CO 2 and CH 4 –H 2 demonstrates that the extraction of individual densities from gas mixtures is feasible at low densities.

Artificial neural networks↗
DOE OSTI2020

Indicator-directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems

Modern high-performance and warehouse computing centers show strong interest in minimizing system power consumption while satisfying customers’ quality of service (QoS). Dynamic voltage and frequency scaling (DVFS) is effective for achieving this goal. Nevertheless, automating the process online and making it transparent to users must address three major challenges: (1) Complexity — today’s hardware components (e.g., CPUs, GPUs, memory, network, etc.) can be configured in several or dozens of frequency/voltage states for satisfying divergent system demands. Given their combination and the emergence of heterogeneity, searching the optimal configuration in the design space online can be timing consuming. (2) QoS guarantee — user-defined objectives such as power constraint and performance target must be monitored, predicted and ensured at the best effort. (3) Adaptability — various known and unknown workloads run on systems. Workloads characteristics should be quickly determined and configurations dynamically adjusted in accord with workloads and QoS. In this work, we focus on applications exhibiting an interesting feature – iterative or periodic, which is common among conventional HPC and emerging machine learning workloads. We propose an online dynamic power-performance (ODPP) management framework to dynamically adjust GPU DVFS configurations to meet performance and power objectives and constraints, without any code annotation or intrusion. Particularly, ODPP extracts the performance and power indicators for applications from their resources utilization profiles in a short episode. It further automatically constructs an accurate model that infers from the indicators how the application's performance and power vary with GPU core and memory frequencies. Aided with the model, for both seen and unseen applications, ODPP can quickly determine the most appropriate DVFS configuration for their execution. We evaluate ODPP on an NVIDIA GPU using multiple exascale computing (ECP) and deep learning applications.

Zou, Pengfei↗
DOE OSTI2015

Materials for Advanced Ultrasupercritical Steam Turbines Task 4: Cast Superalloy Development

The Steam Turbine critical stationary structural components are high integrity Large Shell and Valve Casing heavy section Castings, containing high temperature steam under high pressures. Hence to support the development of advanced materials technology for use in an AUSC steam turbine capable of operating with steam conditions of 760°C (1400°F) and 35 Mpa (5000 psia), Casting alloy selection and evaluation of mechanical, metallurgical properties and castability with robust manufacturing methods are mandated. Alloy down select from Phase 1 based on producability criteria and creep rupture properties tested by NETL-Albany and ORNL directed the consortium to investigate cast properties of Haynes 282 and Haynes 263. The goals of Task 4 in Phase 2 are to understand a broader range of mechanical properties, the impact of manufacturing variables on those properties. Scale up the size of heats to production levels to facilitate the understanding of the impact of heat and component weight, on metallurgical and mechanical behavior. GE Power & Water Materials and Processes Engineering for the Phase 2, Task 4.0 Castings work, systematically designed and executed casting material property evaluation, multiple test programs. Starting from 15 lbs. cylinder castings to world’s first 17,000 lbs. poured weight, heavy section large steam turbine partial valve Haynes 282 super alloy casting. This has demonstrated scalability of the material for steam Turbine applications. Activities under Task 4.0, Investigated and characterized various mechanical properties of Cast Haynes 282 and Cast Nimonic 263. The development stages involved were: 1) Small Cast Evaluation: 4 inch diam. Haynes 282 and Nimonic 263 Cylinders. This provided effects of liquidus super heat range and first baseline mechanical data on cast versions of conventional vacuum re-melted and forged Ni based super alloys. 2) Step block castings of 300 lbs. and 600 lbs. Haynes 282 from 2 foundry heats were evaluated which demonstrated the importance of proper heat treat cycles for Homogenization, and Solutionizing parameters selection and implementation. 3) Step blocks casting of Nimonic 263: Carried out casting solidification simulation analysis, NDT inspection methods evaluation, detailed test matrix for Chemical, Tensile, LCF, stress rupture, CVN impact, hardness and J1C Fracture toughness section sensitivity data and were reported. 4) Centrifugal Casting of Haynes 282, weighing 1400 lbs. with hybrid mold (half Graphite and half Chromite sand) mold assembly was cast using compressor casing production tooling. This test provided Mold cooling rates influence on centrifugally cast microstructure and mechanical properties. Graphite mold section out performs sand mold across all temperatures for 0.2% YS; %Elongation, %RA, UTS at 1400°F. Both Stress-LMP and conditional Fracture toughness plots data were in the scatter band of the wrought alloy. 5) Fundamental Studies on Cooling rates and SDAS test program. Evaluated the influence of 6 mold materials Silica, Chromite, Alumina, Silica with Indirect Chills, Zircon and Graphite on casting solidification cooling rates. Actual Casting cooling rates through Liquidus to Solidus phase transition were measured with 3 different locations based thermocouples placed in each mold. Compared with solidification simulation cooling rates and measurement of SDAS, microstructure features were reported. The test results provided engineered casting potential methods, applicable for heavy section Haynes 282 castings for optimal properties, with foundry process methods and tools. 6) Large casting of Haynes 282 Drawings and Engineering FEM models and supplemental requirements with applicable specifications were provided to suppliers for the steam turbine proto type feature valve casing casting. Molding, melting and casting pouring completed per approved Manufacturing Process Plan during 2014 Q4. The partial valve casing was successfully cast after casting methods were validated with solidification simulation analysis and the casting met NDT inspection and acceptance criteria. Heat treated and sectioned to extract trepan samples at different locations comparing with cast on coupons test data. Material properties requisite for design, such as tensile, creep/rupture, LCF, Fracture Toughness, Charpy V-notch chemical analysis testing were carried out. The test results will be presented in the final report. The typical Haynes 282 large size Steam Turbine production casting from Order to Delivery foundry schedule with the activity break up is shown in Figures 107 and 108. • From Purchase Order placement to Casting pouring ~ 26 weeks. 1. Sales and commercial review 3 2. Engineering Drawings/models review 4 3. Pattern and core box manufacturing 6 4. Casting process engineering review 4 5. FEM and solidification simulation analysis 4 6. Gating & Feeder Attachments, Ceramic tiling 2 7. Molding and coremaking production scheduling 6 8. Melting planning and schedule 3 9. Pouring, cooling and shake out 2 • From Pouring to casting Delivery ~ 29 weeks 10. Shot blast and riser cutting, gates removal 3 11. Homogenizing , solutionizing HT furnace prep 4 12. Grinding, Fettling 2 13. Aging HT Cycle, cooling 2 14. VT and LPT NDT inspections 2 15. Radiographic inspection 4 16. Mechanical testing, Chemical analysis test certs 4 17. Casting weld repair upgrades and Aging PWHT 4 18. NDT after weld repairs and casting upgrades 3 19. Casting Final Inspection and test certifications 3 20. Package and delivery 2 Hence the Total Lead time from P.O to Casting delivery is approximately 55 weeks. The Task 4.2 and Task 4.3 activities and reporting completed.

Thangirala, Mani↗
DOE OSTI2018

An Ultrahigh Capacity Graphite/Li 2 S Battery with Holey-Li 2 S Nanoarchitectures

The pairing of high-capacity Li 2 S cathode (1166 mAh g -1 ) and lithium-free anode (LFA) provides an unparalleled potential in developing safe and energy-dense next-generation secondary batteries. However, the low utilization of the Li 2 S cathode and the lack of electrolytes compatible to both electrodes are impeding the development. Here, a novel graphite/Li 2 S battery system, which features a self-assembled, holey-Li 2 S nanoarchitecture and a stable solid electrolyte interface (SEI) on the graphite electrode, is reported. The holey structure on Li 2 S is beneficial in decomposing Li 2 S at the first charging process due to the enhanced Li ion extraction and transfer from the Li 2 S to the electrolyte. In addition, the concentrated dioxolane (DOL)-rich electrolyte designed lowers the irreversible capacity loss for SEI formation. By using the combined strategies, the graphite/holey-Li 2 S battery delivers an ultrahigh discharge capacity of 810 mAh g -1 at 0.1 C (based on the mass of Li 2 S) and of 714 mAh g -1 at 0.2 C. Moreover, it exhibits a reversible capacity of 300 mAh g -1 after a record lifecycle of 600 cycles at 1 C. These results suggest the great potential of the designed LFA/holey-Li 2 S batteries for practical use.

25 ENERGY STORAGE↗
DOE OSTI2015

Photoluminescence studies of polycrystalline Cu(In,Ga)Se{sub 2}: Lateral inhomogeneities beyond Abbe's diffraction limit

We analyze Cu(In,Ga)Se{sub 2} absorbers with a scanning near-field optical microscope (SNOM) by photoluminescence (PL). Such measurements allow one to extract local fluctuations of the integral PL yield, the quasi-Fermi level splitting, and the material composition in the submicron range. However, the experimental findings depend strongly on the surface roughness of the absorber: If the surface is rough, artifact-prone correlations between surface contour and PL features measured by SNOM can be found that complicate the study of recombination effects. For smooth surfaces, such correlations no longer exist and the influence of grain boundaries on the integral PL yield and the quasi-Fermi level splitting is revealed. The method also allows a detailed determination of the local band gaps in neighboring grains and their spatial variation inside, and thus of possibly local changes in chemical composition of different grains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Learning to predict the cosmological structure formation

Matter evolved under the influence of gravity from minuscule density fluctuations. Nonperturbative structure formed hierarchically over all scales and developed non-Gaussian features in the Universe, known as the cosmic web. To fully understand the structure formation of the Universe is one of the holy grails of modern astrophysics. Astrophysicists survey large volumes of the Universe and use a large ensemble of computer simulations to compare with the observed data to extract the full information of our own Universe. However, to evolve billions of particles over billions of years, even with the simplest physics, is a daunting task. We build a deep neural network, the Deep Density Displacement Model ( D 3 M ), which learns from a set of prerun numerical simulations, to predict the nonlinear large-scale structure of the Universe with the Zel’dovich Approximation (ZA), an analytical approximation based on perturbation theory, as the input. Our extensive analysis demonstrates that D 3 M outperforms the second-order perturbation theory (2LPT), the commonly used fast-approximate simulation method, in predicting cosmic structure in the nonlinear regime. We also show that D 3 M is able to accurately extrapolate far beyond its training data and predict structure formation for significantly different cosmological parameters. Our study proves that deep learning is a practical and accurate alternative to approximate 3D simulations of the gravitational structure formation of the Universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Revealing the Coulomb interaction strength in a cuprate superconductor

Here, we study optimally doped Bi 2 Sr 2 Ca 0.92 Y 0.08 Cu 2 O 8 + δ (Bi2212) using angle-resolved two-photon photoemission spectroscopy. Three spectral features are resolved near 1.5, 2.7, and 3.6 eV above the Fermi level. By tuning the photon energy, we determine that the 2.7-eV feature arises predominantly from unoccupied states. The 1.5- and 3.6-eV features reflect unoccupied states whose spectral intensities are strongly modulated by the corresponding occupied states. These unoccupied states are thus consistent with the prediction from a cluster perturbation theory based on the single-band Hubbard model. Through this comparison, a Coulomb interaction strength U of 2.7 eV is extracted. Our study complements equilibrium photoemission spectroscopy and provides a direct spectroscopic measurement of the unoccupied states in cuprates. The determined Coulomb U indicates that the charge-transfer gap of optimally doped Bi2212 is 1.1 eV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Unraveling the Stereodynamics of Cold Controlled HD - H 2 Collisions

Measuring inelastic rates with partial-wave resolution requires temperatures close to a Kelvin or below, even for the lightest molecule. In a recent experiment, Perreault, Mukherjee, and Zare [Nat. Chem. 10, 561 (2018).] studied collisional relaxation of excited HD molecules in the v=1, j=2 state by para- and ortho-H2 at a temperature of about 1 K, extracting the angular distribution of scattered HD in the v=1, j=0 state. By state preparation of the HD molecules, control of the angular distribution of scattered HD was demonstrated. Here, we report a first-principles simulation of that experiment which enables us to attribute the main features of the observed angular distribution to a single L=2 partial-wave shape resonance. Finallly, our results demonstrate important stereodynamical insights that can be gained when numerically exact quantum scattering calculations are combined with experimental results in the few-partial-wave regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Target development for {sup 67}Cu, {sup 82}Sr radionuclide production at the RIC-80 facility

A high-current cyclotron C-80 capable of producing 40–80 MeV proton beams with a current of up to 200 μA has been constructed and commissioned at PNPI (Petersburg Nuclear Physics Institute). One of the main goals of cyclotron C-80 is the production of a wide spectrum of medical radionuclides for diagnostics and therapy. To date, the project development of a radioisotope facility RIC-80 (radioisotopes at cyclotron C-80) has been completed. The feature of the project is the use of a mass-separator combined with the ion-target device for obtaining ion beams of radioisotopes with a high purity of separation that is especially important for medical applications. The first results of а new high-temperature method for extracting {sup 82}Sr and {sup 67}Cu radioisotopes from irradiated targets have been presented.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Systematics of the chemical freeze-out line in the high baryon density regime explored at SIS100

The systematic uncertainties of chemical freeze-out fits at SIS100 energies (Au+Au reactions at $\sqrt{s_{NN}}$ = 3 – 5 GeV) are studied using UrQMD simulations. Although hadron production in UrQMD does not occur on a sharp chemical freeze-out hyper-surface, the extracted fit quality is shown to be very good. The extracted chemical parameters depend on the selected hadron species as well as the underlying equation of state (EoS) of the matter. Including light nuclei and anti-protons in the fit increases the expected freeze-out temperature, while a stiffer EoS increases the obtained chemical potential. Similarly, the baryon densities extracted by the thermal fits depend on the choice of hadrons as well as the underlying equation of state. These results are important for the upcoming CBM@FAIR physics program and highlight that a degree of caution is advised when one relates the chemical freeze-out curve to features on the QCD phase diagram like the critical endpoint or a possible phase transition.

Hofmann, Emma Lilith [GSI Helmholtzzentrum für Sch↗
DOE OSTI2023

Utah FORGE: Neubrex Well 16B(78)-32 Circulation Test Fiber Optics Monitoring Data and Reports - July, 2023

This dataset features Distributed Acoustic Sensing (DAS) and fiber optics monitoring data acquired by Neubrex Energy Services during the Utah FORGE Well 16B(78)-32 circulation test in July 2023. DAS and fiber optic monitoring data include absolute strain, strain change, strain change rate, distributed temperature sensing (DTS), and frequency band extraction (FBE). Data processing was completed between September and October 2023. The dataset includes the fiber optic sensing data collected during these operations, along with a data collection report, descriptions of the data, and instructions for reading the data files.

15 GEOTHERMAL ENERGY↗