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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic STEM-EELS for single-atom and defect measurement during electron beam transformations

This study introduces the integration of dynamic computer vision–enabled imaging with electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). This approach involves real-time discovery and analysis of atomic structures as they form, allowing us to observe the evolution of material properties at the atomic level, capturing transient states traditional techniques often miss. Rapid object detection and action system enhances the efficiency and accuracy of STEM-EELS by autonomously identifying and targeting only areas of interest. This machine learning (ML)–based approach differs from classical ML in that it must be executed on the fly, not using static data. We apply this technology to V-doped MoS 2 , uncovering insights into defect formation and evolution under electron beam exposure. This approach opens uncharted avenues for exploring and characterizing materials in dynamic states, offering a pathway to increase our understanding of dynamic phenomena in materials under thermal, chemical, and beam stimuli.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Scalable bottom-up synthesis of Co-Ni–doped graphene

Introducing heteroatoms into graphene is a powerful strategy to modulate its catalytic, electronic, and magnetic properties. At variance with the cases of nitrogen (N)– and boron (B)–doped graphene, a scalable method for incorporating transition metal atoms in the carbon (C) mesh is currently lacking, limiting the applicative interest of model system studies. This work presents a during-growth synthesis enabling the incorporation of cobalt (Co) alongside nickel (Ni) atoms in graphene on a Ni(111) substrate. Single atoms are covalently stabilized within graphene double vacancies, with a Co load ranging from 0.07 to 0.22% relative to C atoms, controllable by synthesis parameters. Structural characterization involves variable-temperature scanning tunneling microscopy and ab initio calculations. The Co- and Ni-codoped layer is transferred onto a transmission electron microscopy grid, confirming stability through scanning transmission electron microscopy and electron energy loss spectroscopy. This method holds promise for applications in spintronics, gas sensing, electrochemistry and catalysis, and potential extension to graphene incorporation of similar metals.

Science & Technology - Other Topics↗
DOE OSTI2019

Direct determination of mode-projected electron-phonon coupling in the time domain

Ultrafast spectroscopies have become an important tool for elucidating the microscopic description and dynamical properties of quantum materials. In particular, by tracking the dynamics of nonthermal electrons, a material’s dominant scattering processes can be revealed. In this paper, we present a method for extracting the electron-phonon coupling strength in the time domain, using time- and angle-resolved photoemission spectroscopy (TR-ARPES). This method is demonstrated in graphite, where we investigate the dynamics of photoinjected electrons at the $\overline{K}$ point, detecting quantized energy-loss processes that correspond to the emission of strongly coupled optical phonons. We show that the observed characteristic time scale for spectral weight transfer mediated by phonon-scattering processes allows for the direct quantitative extraction of electron-phonon matrix elements for specific modes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

$$\alpha $$-event characterization and rejection in point-contact HPGe detectors

Abstract P-type point contact (PPC) HPGe detectors are a leading technology for rare event searches due to their excellent energy resolution, low thresholds, and multi-site event rejection capabilities. We have characterized a PPC detector’s response to $$\alpha $$ α particles incident on the sensitive passivated and p $$^+$$ + surfaces, a previously poorly-understood source of background. The detector studied is identical to those in the Majorana Demonstrator experiment, a search for neutrinoless double-beta decay ( $$0\nu \beta \beta $$ 0 ν β β ) in $$^{76}$$ 76 Ge. $$\alpha $$ α decays on most of the passivated surface exhibit significant energy loss due to charge trapping, with waveforms exhibiting a delayed charge recovery (DCR) signature caused by the slow collection of a fraction of the trapped charge. The DCR is found to be complementary to existing methods of $$\alpha $$ α identification, reliably identifying $$\alpha $$ α background events on the passivated surface of the detector. We demonstrate effective rejection of all surface $$\alpha $$ α events (to within statistical uncertainty) with a loss of only 0.2% of bulk events by combining the DCR discriminator with previously-used methods. The DCR discriminator has been used to reduce the background rate in the $$0\nu \beta \beta $$ 0 ν β β region of interest window by an order of magnitude in the Majorana Demonstrator and will be used in the upcoming LEGEND-200 experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the nuclear modification factor of $b$-jets in 5.02 TeV Pb+Pb collisions with the ATLAS detector

This paper presents a measurement of b-jet production in Pb+Pb and pp collisions at $\sqrt{sNN}$ = 5.02 TeV with the ATLAS detector at the LHC. The measurement uses 260 pb –1 of pp collisions collected in 2017 and 1.4 nb –1 of Pb+Pb collisions collected in 2018. In both collision systems, jets are reconstructed via the anti-$k_t$ algorithm. The b-jets are identified from a sample of jets containing muons from the semileptonic decay of b-quarks using template fits of the muon momentum relative to the jet axis. In pp collisions, b-jets are reconstructed for radius parameters R = 0.2 and R = 0.4, and only R = 0.2 jets are used in Pb+Pb collisions. For comparison, inclusive R = 0.2 jets are also measured using 1.7 nb –1 of Pb+Pb collisions collected in 2018 and the same pp collision data as the b-jet measurement. The nuclear modification factor, $R_{AA}$, is calculated for both b-jets and inclusive jets with R = 0.2 over the transverse momentum range of 80–290 GeV. The nuclear modification factor for b-jets decreases from peripheral to central collisions. The ratio of the b-jet $R_{AA}$ to inclusive jet $R_{AA}$ is also presented and suggests that the $R_{AA}$ for b-jets is larger than that for inclusive jets in central Pb+Pb collisions. The measurements are compared with theoretical calculations and suggest a role for mass and colour-charge effects in partonic energy loss in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Jet-like correlations with respect to $\textrm{K}^{0}_\mathrm{{S}}$ and $\Lambda $ ($\overline{\Lambda }$) in pp and central Pb–Pb collisions at $\mathbf {\sqrt{s_\textrm{NN}}} = 5.02$ TeV

Two-particle correlations with $\textrm{K}^{0}_\mathrm{{S}}$, $\Lambda $ /$\overline{\Lambda }$, and charged hadrons as trigger particles in the transverse momentum range 8 < p T,trig < 16 GeV/c , and associated charged particles within 1 < p T,assoc < 8 GeV/c , are studied at midrapidity in pp and central Pb–Pb collisions at a centre-of-mass energy per nucleon–nucleon collision $\mathbf {\sqrt{s_\textrm{NN}}} = 5.02$ TeV with the ALICE detector at the LHC. After subtracting the contributions of the flow background, the per-trigger yields are extracted on both the near and away sides, and the ratio in Pb–Pb collisions with respect to pp collisions (I AA ) is computed. The per-trigger yield in Pb–Pb collisions on the away side is strongly suppressed to the level of I AA ≈0.6 for p T,assoc > 3 GeV/c as expected from strong in-medium energy loss, while an enhancement develops at low p T,assoc on both the near and away sides, reaching I AA ≈1.8 and 2.7 respectively. These findings are in good agreement with previous ALICE measurements from two-particle correlations triggered by neutral pions (π 0 –h) and charged hadrons (h–h) in Pb–Pb collisions at $\mathbf {\sqrt{s_\textrm{NN}}} = 2.76$ TeV. Moreover, the correlations with $\textrm{K}^{0}_\mathrm{{S}}$ mesons and $\Lambda $ /$\overline{\Lambda }$ baryons as trigger particles are compared to those of inclusive charged hadrons. The results are compared with the predictions of Monte Carlo models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Potassium-Containing α-MnO 2 Nanotubes: The Impact of Hollow Regions on Electrochemistry

α-MnO 2 type materials have been studied as electrode materials in rechargeable batteries and electrocatalysts due to their 2 × 2 tunneled crystal structures capable of accommodating cations and their tunable physiochemical properties. In this study, we deliberately synthesized K + containing α-MnO 2 (K 0.9 Mn 8 O 16 ) hollow nanotubes varying the dimensions of the hollow regions and level of surface defects. The K 0.9 Mn 8 O 16 nanotube material samples have similar crystallinity, thermal stability, and average Mn oxidation state. Oxygen surface defects in the hollow regions were revealed through detailed studies using electron energy loss spectroscopy. The impact of the hollow regions and associated surface defects on the electrochemistry of K x Mn 8 O 16 were investigated using cyclic voltammetry, galvanostatic intermittent titration technique, and galvanostatic cycling. The K 0.9 Mn 8 O 16 nanotubes with a large hollow region (~30 nm) and higher level of surface defects show higher apparent lithium ion diffusion coefficients and lower polarization compared to the nanotubes with a small hollow region (~10 nm). In-situ lithiation demonstrated that the dimensions of the nanotube walls expanded, but the hollow region did not change in size as result of lithiation. Furthermore, this research demonstrates that tuning particle architecture and surface defects can positively impact functional behavior of electrochemical storage materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

HydraGNN v5.0

HydraGNN v5.0 expands the code base into a more portable, scalable, and flexible framework for scientific graph learning, with particular strength in atomistic machine-learning interatomic potentials and large-scale distributed training. The release adds Fully Sharded Data Parallel (FSDP) support alongside existing DDP and DeepSpeed paths, including FSDP-aware checkpointing and optimizer integration, and introduces a configurable multi-precision training workflow supporting FP32, BF16, and FP64 across GPUs and Intel XPUs. For atomistic modeling, HydraGNN v5.0 strengthens its MLIP capabilities through dynamic graph construction at every forward pass, energy-conserving force prediction via automatic differentiation, and per-atom energy loss formulations, while extending EGNN models to properly handle periodic boundary conditions. The release also broadens model expressiveness through graph-level attribute conditioning, adds new multi-task and model-parallel extensions such as MACE support and encoder/decoder branch optimization, and expands application coverage with integrated examples for datasets including OC25, Nabla2-DFT, QCML, Open Polymers 2026, and OPF. In parallel, HydraGNN v5.0 improves production readiness through performance optimizations for large-scale runs, stratified sampling and linear-regression preprocessing utilities, and tested installation scripts for DOE supercomputers including Frontier, Aurora, Perlmutter, and Andes. Overall, the release advances HydraGNN as a robust software platform for scalable graph neural networks across materials science, chemistry, and scientific machine learning workflows

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2020

Chemical and bonding analysis of liquids using liquid cell electron microscopy

Liquid cell transmission electron microscopy (TEM) has become an essential tool for studying the structure and properties of both hard and soft condensed-matter samples, as well as liquids themselves. Liquid cell sample holders, often consisting of two thin window layers separating the liquid sample from the high vacuum of the microscope column, have been designed to control in situ conditions, including temperature, voltage/current, or flow through the window region. While high-resolution and time-resolved TEM imaging probes the structure, shape, and dynamics of liquid cell samples, information about the chemical composition and spatially resolved bonding is often difficult to obtain due to the liquid thickness, the window layers, the holder configuration, or beam-induced radiolysis. Here, we review different approaches to quantitative liquid cell electron microscopy, including recent developments to perform energy-dispersive x-ray and electron energy-loss spectroscopy experiments on samples in a liquid environment or the liquid itself. We also cover graphene liquid cells and other ultrathin window layer holders.

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

3D printable silicone compositions exhibiting high toughness and low durometer

3D printable silicones can be designed with varying crosslink density, network structures, and types of reinforcing additives. Within this design space, one may tailor the uncured material’s rheology and mechanical response to access a wide range of potential applications. However, printable, low modulus silicones, particularly those applicable to direct ink write, are underreported in published literature. To address the need for higher performance, low modulus silicones with demonstrated printability, a new set of ca. 20–50 Shore A hardness silicone elastomers exhibiting ca. 7 MPa ultimate tensile strength and ca. 400–1200% elongation at break is presented. Mechanical properties were analyzed, providing insight to the effects of formulation constituents on mechanical properties. Cyclic mechanical testing of the silicone formulations was also performed, and the energy loss and permanent set throughout cycling were determined. In conclusion, printed structures demonstrate the feasibility of these new silicones as durable frameworks for novel soft device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CEBAF 22 GeV FFA energy upgrade

Extending the energy reach of CEBAF by increasing the number of recirculations, while using the existing linacs is explored. This energy upgrade is based on the multi-pass acceleration of electrons in a single non-scaling Fixed Field Alternating Gradient (FFA) beam line, using Halbach-style permanent magnets. Encouraged by the recent successful demonstration of CBETA, a proposal was formulated to nearly double the energy of CEBAF from 12 to 22~GeV by replacing the highest energy arcs with FFA transport. The new FFA arcs would support simultaneous transport of an additional 6 passes spanning roughly a factor of two in energy. One of the challenges of the multi-pass (11) linac optics is to assure uniform focusing over a wide range of energies. Here, we propose a triplet lattice that provides a stable periodic solution covering an energy ratio of 1:33. The current CEBAF injection at 123 MeV, makes optical matching in the first linac impossible due to the extremely high energy ratio (1:175). Replacement of the current injector with a 650 MeV recirculating injector will alleviate this issue. Orbital and optical matching from the FFA arcs to the linacs is implemented as a compact non-adiabatic insert. The design presented here is anticipated to deliver a 22 GeV beam with normalized emittance of 76 mm·mrad and a relative energy spread of 1×10\textsuperscript{-3}. Further recirculation beyond 22 GeV is limited by the large (974 MeV per electron) energy loss due to synchrotron radiation.

Benesch, J.↗
DOE OSTI2020

FY19 FES Theory Performance Target (Final Report)

Understanding the relevant turbulent transport mechanisms at the edge of a high-performance tokamak is essential for predicting and optimizing the H-mode pedestal structure in future burning plasma devices. Global electromagnetic gyrokinetic simulations will be performed based on representative experimental pedestal scenarios in order to clarify which instabilities are most important for each of the particle and heat transport channels. Edge transport modeling will be performed in order to estimate and bound the particle and heat sources—e.g., the ionization density source and the atomic energy loss channels due to ionization, charge exchange, and radiation. Comparisons will be made with data from the DIII-D, JET, C-Mod and NSTX or MAST experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Varying Quantum Degeneracy in Plasmas Created at the National Ignition Facility [Slides]

Physically realized electron gas systems usually reside in either the quantum non-degenerate or fully degenerate limit, where the average de Broglie wavelength of the thermal electrons becomes comparable with the interparticle distance between electrons. A few systems, such as young brown dwarfs and the cold dense fuels created in imploded cryogenic capsules at the National Ignition Facility, lie between these two limits and are partially degenerate. The National Ignition Facility has the unique capability of varying the electron quantum degeneracy by adjusting the laser drive used to implode the capsules. This allows experimental studies of the effects of the degeneracy level on plasma transport properties. By measuring rare nuclear reactions in these cold dense fuels, we show that the electron stopping power, which is the rate of energy loss per unit distance travelled by a charged particle, changes with increasing electron density. We observe a quantum-induced shift in the peak of the stopping power using diagnostics that measure above and below this peak. The observed changes in the stopping power are shown to be unique to the transition region between non-degenerate and degenerate plasmas. Our results support the screening models applied to partially degenerate astrophysical systems such as young brown dwarfs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Advanced Non-Tread Materials for Fuel-Efficient Tires

PPG Industries, Inc. proposes to develop a new silica filler that can increase fuel efficiency by 2% while maximizing key performance properties in non-tread tire components compared to current carbon black/silica filler blends. In this project PPG focused on a sidewall compound. The developed compounds/components will reduce energy losses by approximately 25%, with no more than a 5% loss of resistance to degradative forces (targeting better performance). PPG plans to achieve this goal by characterizing the impact the silica filler can have on rubber properties and then tuning the silica morphology and surface chemistry for this end use. PPG will also provide guidance in optimizing the compound formulation to make the best use of this new filler. A key aspect is to understand and maintain, if not improve, the aging performance as evaluated by crack growth resistance under ozone environment. Two key strategies were used to meet the rolling resistance goal while maintaining other performance properties. The first factor was understanding the surface treatments and chemical makeup of the silica and its effects on compound performance. The second factor was using the best performing silicas and determining the optimum compound modifications to achieve the final sidewall compound performance. Using statistical analysis throughout the optimization process, it was determined that changing the silica morphology played a role in improving the reduction of tear strength while reducing rolling resistance and the improvements observed varied depending on the CB type.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Image quality indicator and dechromator setup for static LANSCE proton radiography experiment

This document describes a static geometry consisting of a sphere of gold and Ti-6Al-4V alloy, along with an energy-loss matching dechromator composed of polycarbonate, to field with the X3 electromagnetic magnifying lens at LANSCE during the next beam cycle. This static configuration will allow us to: (1) characterize the system’s resolution at the material interface between the gold and titanium alloy, and test the image quality for fine features associated with the screws used to fasten the titanium alloy hemispheres; (2) tune our models of proton scattering and imaging for these materials; and (3) test a procedure to align the polycarbonate dechromator and the sphere within the proton beamline. The data will also be suitable for validation of the software options available for proton radiography simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Exotic Meson Photoproduction at GlueX – Search for the hybrid candidate Y

Understanding the hadron spectrum is one of the primary goals of non-perturbative QCD. Many predictions have experimentally been confirmed, others still remain under experimental investigation. Of particular interest is how gluonic excitations give rise to states with constituent glue. One class of such states are hybrid mesons that are predicted by theoretical models and Lattice QCD calculations. Searching for and understanding the nature of these states is a primary physics goal of the GlueX experiment at the CEBAF accelerator at Jefferson Lab. A search for a JPC = 1-- hybrid meson candidate, the Y (2175), in phi(1020)pi+pi+ and phi(1020)f0(980) channels in photoproduction on a proton target has been conducted. A first measurement of non-resonant phi(1020)pi+pi+ and phi(1020)f0(980) total cross sections in photoproduction has been performed. An upper limit on the resonance production cross section for the Y (2175) -> phi(1020)pi+pi+ and Y (2175) -> phi(1020)f0(980) channels are estimated. Since the analysis essentially depends on the quality of the charged kaon identification, also an optimization of particle identification through an improvement of the energy loss estimation in the CDC by a truncated mean method has been investigated.

Hamdi, Abdennacer↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Roundtable on Foundational Science for Carbon-Neutral Hydrogen Technologies (Technology Status Document)

This document summarizes the status of carbon-neutral hydrogen production, storage and transport, and utilization. The state of the art in the implementation, limitations, and challenges of these technologies are summarized. Sources of hydrogen are broadly categorized as hydrcoarbons or water and the processes used to convert these sources to hydrogen as catalytic, thermochemical, or electrochemical. Catalytic steam methane reforming of methane is the dominant process today. Other processes have smaller production volumes and the technology is less mature, but are being deployed at increasing rates, most notably water electrolyzers for hydrogen fueling stations. Efficient transport and storage of hydrogen is one of the major challenges facing a hydrogen-based energy economy. This arises in part from its low volumetric energy density necessitating very high pressures or cryogenic temperatures to store sufficient amounts for practical applications. High-pressure compressed hydrogen cylinders are the incumbent hydrogen storage technology for applications such as light-duty fuel cell electric vehicles, for example. The storage of hydrogen in materials or in chemicals is being pursued to address the issues associated with compression, such as parasitic energy loss and weight, size, and cost of storage containers. The complex nature of the chemical and physical processes involved in the uptake, storage, and release of hydrogen has slowed the discovery of suitable hydrogen storage materials. Both small and large-scale storage face the challenge of embrittlement of the storage media by hydrogen. There is a myriad of uses of hydrogen offering the promises of improving the efficiency of various applications and reducing or eliminating CO 2 emissions. These range from direct electrochemical conversion to electricity to power vehicles and grid-level stationary applications to combustion to production of chemicals and commodities. One of the most impactful applications in terms of reduction of CO 2 emissions is fuel cell passenger vehicles and heavy-duty vehicles such as class 8 trucks. The challenges facing widespread deployment of fuel cells, beyond the major hurdle of the lack of a hydrogen distribution infrastructure, are cost and durability, primarily related to the precious metal cathode catalyst and its durability. The other uses of hydrogen from conversion to hydrocarbons, polymer upcycling, and upgrading of bio-oils are at varying stages of maturity and also face fundamental challenges associated with catalytic processes and materials.

08 HYDROGEN↗