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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Machine learning at the energy and intensity frontiers of particle physics

Our knowledge of the fundamental particles of nature and their interactions is summarized by the standard model of particle physics. Advancing our understanding in this field has required experiments that operate at ever higher energies and intensities, which produce extremely large and information-rich data samples. The use of machine-learning techniques is revolutionizing how we interpret these data samples, greatly increasing the discovery potential of present and future experiments. Here we summarize the challenges and opportunities that come with the use of machine learning at the frontiers of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Switchable wetting of oxygen-evolving oxide catalysts

The surface wettability of catalysts is typically controlled via surface treatments that promote catalytic performance. Here we report on potential-regulated hydrophobicity/hydrophilicity at cobalt-based oxide interfaces with an alkaline solution. The switchable wetting of single particles, directly related to their activity and stability towards the oxygen evolution reaction, was revealed by electrochemical liquid-phase transmission electron microscopy. Analysis of the movement of the liquid in real time revealed distinctive wettability behaviour associated with specific potential ranges. At low potentials, an overall reduction of the hydrophobicity of the oxides was probed. Upon reversible reconstruction towards the surface oxyhydroxide phase, electrowetting was found to cause a change in the interfacial capacitance. At high potentials, the evolution of molecular oxygen, confirmed by operando electron energy-loss spectroscopy, was accompanied by a globally thinner liquid layer. This work directly links the physical wetting with the chemical oxygen evolution reaction of single particles, providing fundamental insights into solid–liquid interfacial interactions of oxygen-evolving oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Ghost-imaging-enhanced noninvasive spectral characterization of stochastic x-ray free-electron-laser pulses

Abstract High-intensity ultrashort X-ray free-electron laser (XFEL) pulses are revolutionizing the study of fundamental nonlinear x-ray matter interactions and coupled electronic and nuclear dynamics. To fully exploit the potential of this powerful tool for advanced x-ray spectroscopies, a noninvasive spectral characterization of incident stochastic XFEL pulses with high resolution is a key requirement. Here we present a methodology that combines high-acceptance angle-resolved photoelectron time-of-flight spectroscopy and ghost imaging to enhance the quality of spectral characterization of x-ray free-electron laser pulses. Implementation of this noninvasive high-resolution x-ray diagnostic can greatly benefit the ultrafast x-ray spectroscopy community by functioning as a transparent beamsplitter for applications such as transient absorption spectroscopy in averaging mode as well as covariance-based x-ray nonlinear spectroscopies in single-shot mode where the shot-to-shot fluctuations inherent to a self-amplified spontaneous emission (SASE) XFEL pulse are a powerful asset.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics

Sampling from known probability distributions is a ubiquitous task in computational science, underlying calculations in domains from linguistics to biology and physics. Generative machine-learning (ML) models have emerged as a promising tool in this space, building on the success of this approach in applications such as image, text, and audio generation. Often, however, generative tasks in scientific domains have unique structures and features—such as complex symmetries and the requirement of exactness guarantees—that present both challenges and opportunities for ML. This Perspective outlines the advances in ML-based sampling motivated by lattice quantum field theory, in particular for the theory of quantum chromodynamics. Enabling calculations of the structure and interactions of matter from our most fundamental understanding of particle physics, lattice quantum chromodynamics is one of the main consumers of open-science supercomputing worldwide. Here, the design of ML algorithms for this application faces profound challenges, including the necessity of scaling custom ML architectures to the largest supercomputers, but also promises immense benefits, and is spurring a wave of development in ML-based sampling more broadly. In lattice field theory, if this approach can realize its early promise it will be a transformative step towards first-principles physics calculations in particle, nuclear and condensed matter physics that are intractable with traditional approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Direct-write liquid phase transformations with a scanning transmission electron microscope

The highly energetic electron beam from a scanning transmission electron microscope (STEM) can induce local changes in the state of matter, ranging from local knock-out and atomic movement, to amorphization/crystallization, and chemical/electrochemical reactions occuring at localized liquid-solid and gas-solid interfaces. To date, fundamental studies of e-beam induced phenomena and practical applications have been limited by conventional e-beam rastering modes that allow only for uniform e-beam exposures. Here we develop an automated liquid phase nanolithography method that is capable of directly writing nanometer scaled features within silicon nitride encapsulated liquid cells. An external beam control system, connected to the scan coils of an aberration-corrected STEM, is used to precisely control the position, dwell time, and scan velocity of a sub-nanometer STEM probe. Site-specific locations in a sealed liquid cell containing an aqueous solution of H 2 PdCl 4 are irradiated to controllably deposit palladium onto silicon nitride membranes. We determine the threshold electron dose required for the radiolytic deposition of metallic palladium, explore the influence of electron dose on the feature size and morphology of nanolithographically patterned nanostructures, and propose a feedback-controlled monitoring method for active control of the nanofabricated structures through STEM detector signal monitoring. As a result, this approach enables both fundamental studies of electron beam induced interactions with matter, as well as opens a pathway to fabricate nanostructures with tailored architectures and chemistries via shape-controlled nanolithographic patterning from liquid phase precursors.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Apex hydrogen bonds in dendron assemblies modulate close-packed mesocrystal structures

The close-packed mesocrystal structures from soft-matter assemblies have recently received attention due to their structural similarity to atomic crystals, displaying various sphere-packing Frank–Kasper (FK) and quasicrystal structures. Herein, diverse mesocrystal structures are explored in second-generation dendrons (G2-X) designed with identical wedges, in which the terminal functionalities X = CONH 2 and CH 2 NH 2 represent two levels of the strong and weak hydrogen-bonding apexes, respectively. The cohesive interactions at the core apex, referred to as the core interactions, are effectively modulated by forming heterogeneous hydrogen bonds between these two functional units. For the dendron assemblies compositionally close to each pure component of G2-CONH 2 and G2-CH 2 NH 2 , their own FK A15 and C14 phases dominate other phases, respectively. We show the existence of the wide-range FK σ including the dodecagonal quasicrystal (DDQC) phases from the dendron mixtures between G2-CONH 2 and G2-CH 2 NH 2 , providing an experimental phase sequence of A15–σ–DDQC–C14 as the core interactions are alleviated. Intriguingly, the temperature dependence of particle sizes shows that the high plateau values of particle sizes are maintained equivalently until each threshold temperature (T th ), followed by a prompt decrease above the T th . A decrease in T th by alleviating the core interactions and its composition dependence suggest that the more size-dispersed particles, the more susceptibility to chain exchange with increasing temperature. Here our results on the formation of supramolecular dendron assemblies provide a guide to understand the core-interaction-dependent mesocrystal structures toward the fundamental principle underlying the temperature dependence of their particle sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Living liquid crystals

Collective motion of self-propelled organisms or synthetic par­ticles, often termed •active fluid,• has attracted enormous atten­tion in the broad scientific community because of its fundamentally nonequilibrium nature. Energy input and interactions among the moving units and the medium lead to complex dynamics. Here,we introduce a class of active matter-living liquid crystals (UCs}­ that combines living swimming bacteria with a lyotropic liquid crystal. The physical properties of LLCs can be controlled by the amount of oxygen available to bacteria, by concentration of ingre­dients, or by temperature. Our studies reveal a wealth of intriguing dynamic phenomena. caused by the coupling between the activity-triggered flow and long-range orientational order of the medium. Among these are (i) nonlinear trajectories of bacterial motion guided by nonuniform director, (ii) local melting of the liquid crystal caused by the bacteria-produced shear flows, (iii) activity-triggered transition from a nonflowing uniform state into a flowing one-dimensional periodic pattern and its evolution into a turbulent array of topological defects, and (iv) birefringence­ enabled visualization of microflow generated by the nanometers­ thick bacterial flagella. Unlike their isotropic counterpart, the LLCs show collective dynamic effects at very low volume fraction of bacteria, on the order of 0.2%. Our work suggests an unorthodox design concept to control and manipulate the dynamic behavior of soft active matter and opens the door for potential biosensing and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Trivalent Lanthanide/Actinide Separation Using Aqueous-Modified TALSPEAK Chemistry

TALSPEAK is a liquid/liquid extraction process designed to separate trivalent lanthanides (Ln3+) from minor actinides (MAs) Am3+ and Cm3+. Traditional TALSPEAK organic phase is comprised of a monoacidic dialkyl bis(2-ethylhexyl)phosphoric acid extractant (HDEHP) in diisopropyl benzene (DIPB). The aqueous phase contains a soluble aminopolycarboxylate diethylenetriamine-N,N,N’,N”,N”-pentaacetic acid (DTPA) in a concentrated (1.0-2.0 M) lactic acid (HL) buffer with the aqueous acidity typically adjusted to pH 3.0. TALSPEAK balances the selective complexation of the actinides by DTPA against the electrostatic attraction of the lanthanides by the HDEHP extractant to achieve the desired trivalent lanthanide/actinide group separation. Although TALSPEAK is considered a successful separations scheme, recent fundamental studies have highlighted complex chemical interactions occurring in the aqueous and organic phases during the extraction process. Previous attempts to model the system have shown thermodynamic models do not accurately predict the observed extraction trends in the p[H+] range 2.5-4.8. In this study, the aqueous phase is modified by replacing the lactic acid buffer with a variety of simple and longer-chain amino acid buffers. The results show successful trivalent lanthanide/actinide group separation with the aqueous-modified TALSPEAK process at pH 2. The amino acid buffer concentrations were reduced to 0.5 M (at pH 2) and separations were performed without any effect on phase transfer kinetics. Successful modeling of the aqueous-modified TALSPEAK process (p[H+] 1.6-3.1) using a simplified thermodynamic model and an internally consistent set of thermodynamic data is presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Strong-field ionization with two-color circularly polarized laser fields

Strong-field ionization provides fundamental insight into light-matter interactions, encoding the structure of atoms and molecules on the subångström and subfemtosecond scales. Here, we explore an important regime: strong-field ionization by two-color circularly polarized laser fields. In contrast to past work using linearly polarized drivers, we probe electron trajectories that are driven in a two-dimensional plane, thus separating the tunneling angle from the rescattering angle. This allows us to make several findings. First, we observe a single-lobed electron distribution for co-rotating fields, and a three-lobed distribution for counter-rotating fields, providing experimental validation of the theoretical model explaining the generation of circularly polarized high harmonic light. Second, we discover that there is significant electron-ion rescattering using counter-rotating fields, but not with co-rotating fields. Finally, we show that the rescattered electrons are well separated from the directly ionized electrons, in striking contrast to similar low-energy structures seen with linearly polarized fields. These findings help overcome the long-standing problem of how to decouple the tunneling and rescattering steps in strong-field ionization, which will enable new dynamic probes of atomic and molecular structure.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

One-dimensional antilocalization of electrons from spin disorder probed by nonlinear Hall effect

In recent years, nonreciprocal transport measurement has emerged as a probe of spin orbit interaction, spin texture, superconductivity, and other fundamental properties of materials. Here, we study the nonlinear Hall effect (NLHE) in Bi 2 Se 3 /CoFeB heterostructures measured by second harmonic voltage method. Magneto-optical Kerr effect measurements demonstrate the origin of the NLHE to be the asymmetric magnon scattering mechanism. Moreover, a linear relation between the nonlinear Hall resistance and the electron phase coherence length of Bi 2 Se 3 is observed between 5 and 50 K. In this work, we propose a phenomenological model that explains the enhancement of the NLHE below 50 K as a result of one-dimensional antilocalization of electrons from spin disorder, enabled by spin-momentum locking and conservation of angular momentum.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Tuning spin dynamics and localization near the metal-insulator transition in Fe/GaAs heterostructures

We present a simultaneous investigation of coherent spin dynamics in both localized and itinerant carriers in Fe/GaAs heterostructures using ultrafast and spin-resolved pump-probe spectroscopy. We find that for excitation densities that push the transient Fermi energy of photocarriers above the mobility edge there exist two distinct precession frequencies in the observed spin dynamics, allowing us to simultaneously monitor both localized and itinerant states. For low magnetic fields (below 3.00 T) the beat frequency between these two excitations evolves linearly, indicating that the nuclear polarization is saturated almost immediately and that the hyperfine coupling to these two states is comparable, despite the 20 times enhancement in nuclear polarization provided by the presence of the Fe layer. At higher magnetic fields (above 3.00 T) the Zeeman energy drives reentrant localization of the photocarriers. Subtracting the constant hyperfine contribution from both sets of data allows us to extract the Lande g factor for each state and estimate their energy relative to the bottom of the conduction band, yielding -2.16 and 17 meV for localized and itinerant states, respectively. This work advances our fundamental understanding of spin-spin interactions between electron and nuclear spin species, as well as between localized and itinerant electronic states, and therefore has implications for future work in both spintronics and quantum information/computation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Exploring the Strong Interaction of Three-Body Systems at the LHC

Deuterons are atomic nuclei composed of a neutron and a proton held together by the strong interaction. Unbound ensembles composed of a deuteron and a third nucleon have been investigated in the past using scattering experiments, and they constitute a fundamental reference in nuclear physics to constrain nuclear interactions and the properties of nuclei. In this work, K + -d and p-d femtoscopic correlations measured by the ALICE Collaboration in proton-proton (pp) collisions at $\sqrt{s}$ = 13 TeV at the Large Hadron Collider (LHC) are presented. It is demonstrated that correlations in momentum space between deuterons and kaons or protons allow us to study three-hadron systems at distances comparable with the proton radius. The analysis of the K + -d correlation shows that the relative distances at which deuterons and protons or kaons are produced are around 2 fm. The analysis of the p-d correlation shows that only a full three-body calculation that accounts for the internal structure of the deuteron can explain the data. In particular, the sensitivity of the observable to the short-range part of the interaction is demonstrated. These results indicate that correlations involving light nuclei in pp collisions at the LHC will also provide access to any three-body system in the strange and charm sectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

QLiG: Query Like a Graph For Subgraph Matching

A graph is a natural and flexible modeling approach to represent entities and relationships between them in real-world. A Knowledge Graphs (KG) is a specialized graph with formal and structured representation of facts, relationships, annotated with semantic descriptions. Subgraph matching is one of the fundamental graph problems to identify relationships, interactions and activities of interest within a large graph. A query specification is a collection of abstract components, operations, and constraints to express a pattern. The specification can be implemented in different ways based on underlying data model. Various graph query specifications have been developed over the years and have led to the development of different open-sourced and vendor-specific query languages. Such specification are modeled as an extension of relational algebra used to develop relational query languages such as SQL. Such relational concepts do not inherently support graph queries. There is a need to represent graph queries in terms on graph-based components to expedite query construction by non-database experts. We present a graph-based query approach QLiG (pronounced cleeg), to perform subgraph matching in Labeled Property Graph. We present the query specifications, salient features, and a use case to show functional examples.

Purohit, Sumit↗
DOE OSTI2021

Microbial seasonality promotes soil respiratory carbon emission in natural ecosystems: A modeling study

Seasonality is a key feature of the biosphere and the seasonal dynamics of soil carbon (C) emissions represent a fundamental mechanism regulating the terrestrial–climate interaction. We applied a microbial explicit model—CLM-Microbe—to evaluate the impacts of microbial seasonality on soil C cycling in terrestrial ecosystems. Additionally, the CLM-Microbe model was validated in simulating belowground respiratory fluxes, that is, microbial respiration, root respiration, and soil respiration at the site level. On average, the CLM-Microbe model explained 72% (n = 19, p < 0.0001), 65% (n = 19, p < 0.0001), and 71% (n = 18, p < 0.0001) of the variation in microbial respiration, root respiration, and soil respiration, respectively. We then compared the model simulations of soil respiratory fluxes and soil organic C content in top 1 m between the CLM-Microbe model with (CLM-Microbe) and without (CLM-Microbe_wos) seasonal dynamics of soil microbial biomass in natural biomes. Removing soil microbial seasonality reduced model performance in simulating microbial respiration and soil respiration, but led to slight differences in simulating root respiration. Compared with the CLM-Microbe, the CLM-Microbe_wos underestimated the annual flux of microbial respiration by 0.6%–32% and annual flux of soil respiration by 0.4%–29% in natural biomes. Correspondingly, the CLM-Microbe_wos estimated higher soil organic C content in top 1 m (0.2%–7%) except for the sites in Arctic and boreal regions. Our findings suggest that soil microbial seasonality enhances soil respiratory C emissions, leading to a decline in SOC storage. An explicit representation of soil microbial seasonality represents a critical improvement for projecting soil C decomposition and reducing the uncertainties in global C cycle projection under the changing climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Accelerated Leach Testing of GLASS (ALTGLASS): I. Informatics approach to high level waste glass gel formation and aging

Glass corrosion data from the ALTGLASS™ database were used to determine if gel compositions, which evolve as glass systems corrode, are correlated with the generation of zeolites and subsequent increase in the glass dissolution rate at long times. The gel compositions were estimated based on the difference between the elemental glass starting compositions and the measured elemental leachate concentrations from the long-term product consistency tests (ASTM C1285) at various stages of dissolution, ie, reaction progress. A well-characterized subset of high level waste glasses from the database was selected: these glasses had been leached for 15-20 years at reaction progresses up to ~80%. The gel composition data, at various reaction progresses, were subjected to a step-wise regression, which demonstrated that hydrogel compositions with Si*/Al* ratios of <1.0 did not generate zeolites and maintained low dissolution rates for the duration of the experiments. Glasses that formed hydrogel compositions with Si^*/Al^* ratios ≥1, generated zeolites accompanied by a resumption in the glass dissolution rate. Finally, the role of the gel Si/Al ratio, and the interactions with the leachate, provides the fundamental understanding needed to predict if and when the glass dissolution rate will increase due to zeolitization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Direct Numerical Simulation of Transitional and Turbulent Flows Over Multi-Scale Surface Roughness—Part II: The Effect of Roughness on the Performance of a High-Pressure Turbine Blade

Abstract Turbine blades generally present surface roughness introduced in the manufacturing process or caused by in-service degradation, which can have a significant impact on aero-thermal performance. A better understanding of the fundamental physical mechanisms arising from the interaction between the roughness and the turbine flow at engine-relevant conditions can provide insights for the design of blades with improved efficiency and longer operational life. To this end, a high-fidelity numerical framework combining a well-validated solver for direct numerical simulation and a second-order accurate immersed boundary method is employed to predict roughness-induced aero-thermal effects on an LS89 high-pressure turbine (HPT) blade at engine-relevant conditions. Different amplitudes and distributions of surface roughness are investigated and a reference smooth-blade simulation under the same flow conditions is conducted for comparison. Roughness of increasing amplitude progressively shifts the blade suction side boundary layer transition upstream, producing larger values of the turbulent kinetic energy and higher total wake losses. The on-surface data-capturing capabilities of the numerical framework provide direct measurements of the heat flux and the skin friction coefficient, hence offering quantitative information between the surface topology and engineering-relevant performance parameters. This work may provide a benchmark for future numerical studies of turbomachinery flows with roughness.

Engineering↗
DOE OSTI2025

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗