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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reactor Performance Improvement Options to Sustain High Flux Isotope Reactor Leadership into the Future

The mission of the Neutron Sciences Directorate (NScD) at the U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) is the undertaking of high-impact research into the structure and properties of materials across the spectrum of biology, chemistry, physics, materials science, and engineering. NScD operates two world-leading neutron scattering facilities including the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source. HFIR achieved full power in 1966, and over a half century later, it continues to serve a variety of national missions. HFIR provides one of the highest steady-state neutron fluxes of any research reactor in the world to support scientific missions including cold and thermal neutron scattering, isotope production, and materials irradiation research. To sustain leadership in neutron sciences into the future, ORNL is exploring areas in which HFIR can be improved to enhance its performance. Many improvement areas are being explored such as upgrading the cold source and neutron scattering facilities; however, the improvement areas focused on in this paper include replacing the reactor pressure vessel, upgrading the neutron reflector, and converting from high-enriched uranium to low-enriched uranium fuel.

Chandler, David↗
DOE OSTI2020

Investigation of magnetic noise from conductive shields in the 10–300 kHz frequency range

Here we present experimental and theoretical investigations of magnetic noise originating from radio-frequency (RF) conductive shields of flat geometry in the inductance-dominated impedance regime below 300 kHz. The measurement is based on a Q-factor determination of a coil that provides a sufficient sensitivity, placed at the position where the shield magnetic noise is measured. The theory is based on calculations of magnetic field and inductance of one or a few flat rings that emulate a conductive shield. The theoretical model is found to be in close agreement with experimental data. It can be used to predict the magnetic noise of a conductive shield with different thicknesses, conductivities, and temperatures at different distances for a wide range of frequencies. Although the model can be generalized for a more arbitrary shield geometry, in its presented form, it can be applied to the magnetic noise predictions when the shield surface curvature is not large. One important conclusion is that the RF conductive shield can generate the magnetic noise much lower than femtotesla, and, thus, it can be used in many precision experiments targeting minute high-frequency magnetic signals, such as detection of magnetic resonance imaging and nuclear quadrupole resonance signals and search for axion dark matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Magnetic imaging and statistical analysis of the metamagnetic phase transition of FeRh with electron spins in diamond

Magnetic imaging based on nitrogen-vacancy (NV) centers in diamond has emerged as a powerful tool for probing magnetic phenomena in fields ranging from biology to physics. A key strength of NV sensing is its local-probe nature, enabling high-resolution spatial images of magnetic stray fields emanating from a sample. However, this local character can also form a drawback for analyzing the global properties of a system, such as a phase transition temperature. Here, we address this challenge by using statistical analyses of magnetic-field maps to characterize the first-order temperature-driven metamagnetic phase transition from the antiferromagnetic to the ferromagnetic state in FeRh. After imaging the phase transition and identifying the regimes of nucleation, growth, and coalescence of ferromagnetic domains, we statistically characterize the spatial magnetic-field maps to extract the transition temperature and thermal hysteresis width. By analyzing the spatial correlations of the maps in relation to the magnetocrystalline anisotropy and external magnetic field, we detect a reorientation of domain walls across the phase transition. The employed statistical approach can be extended to the study of other magnetic phenomena with NV magnetometry or other sensing techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗
DOE OSTI2021

Structure and assembly of the diiron cofactor in the heme-oxygenase–like domain of the N-nitrosourea–producing enzyme SznF

In biosynthesis of the pancreatic cancer drug streptozotocin, the tridomain nonheme-iron oxygenase SznF hydroxylates N δ and N ω ' of N ω -methyl- L -arginine before oxidatively rearranging the triply modified guanidine to the N-methyl-N-nitrosourea pharmacophore. A previously published structure visualized the monoiron cofactor in the enzyme’s C-terminal cupin domain, which promotes the final rearrangement, but exhibited disorder and minimal metal occupancy in the site of the proposed diiron cofactor in the N-hydroxylating heme-oxygenase–like (HO-like) central domain. We leveraged our recent observation that the N-oxygenating µ-peroxodiiron(III/III) intermediate can form in the HO-like domain after the apo protein self-assembles its diiron(II/II) cofactor to solve structures of SznF with both of its iron cofactors bound. These structures of a biochemically validated member of the emerging heme-oxygenase–like diiron oxidase and oxygenase (HDO) superfamily with intact diiron cofactor reveal both the large-scale conformational change required to assemble the O 2 -reactive Fe 2 (II/II) complex and the structural basis for cofactor instability—a trait shared by the other validated HDOs. During cofactor (dis)assembly, a ligand-harboring core helix dynamically (un)folds. The diiron cofactor also coordinates an unanticipated Glu ligand contributed by an auxiliary helix implicated in substrate binding by docking and molecular dynamics simulations. The additional carboxylate ligand is conserved in another N-oxygenating HDO but not in two HDOs that cleave carbon–hydrogen and carbon–carbon bonds to install olefins. Among ~9,600 sequences identified bioinformatically as members of the emerging HDO superfamily, ~25% conserve this additional carboxylate residue and are thus tentatively assigned as N-oxygenases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Polyubiquitin ligand-induced phase transitions are optimized by spacing between ubiquitin units

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or posttranslational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to either the UBQLN2-binding surface of Ub or the spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model based on polyphasic linkage principles that accurately described the effects of different hubs on UBQLN2 phase separation, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. The extent to which polyubiquitin hubs promote UBQLN2 phase separation is encoded in the spacings between Ub units. This spacing is modulated by chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. The spacing in naturally occurring linear polyubiquitin chains is already optimized to promote phase separation with UBQLN2. We expect our findings to extend to other condensates, emphasizing the importance of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Operator-level quantum acceleration of non-logconcave sampling

Sampling from probability distributions of the form 𝝈 ∝ e −𝜷V , where V is a continuous potential, is a fundamental task across physics, chemistry, biology, computer science, and statistics. However, when V is nonconvex, the resulting distribution becomes non-logconcave, and classical methods such as Langevin dynamics often exhibit poor performance. We introduce a quantum algorithm that provably accelerates a broad class of continuous-time sampling dynamics. For Langevin dynamics, our method encodes the target Gibbs measure into the amplitudes of aquantum state, identified as the kernel of a block matrix derived from a factorization of the Witten Laplacian operator. This connection enables Gibbs sampling via singular value thresholding and yields up to a quartic quantum speedup over best-knownclassical Langevin-based methods in the non-logconcave setting. Building on this framework, we further develop the first quantum algorithm that accelerates replica exchange Langevin diffusion, a widely used method for sampling from complex, rugged energy landscapes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Diamond magnetometer enhanced by ferrite flux concentrators

Magnetometers based on nitrogen-vacancy (NV) centers in diamond are promising room-temperature, solid-state sensors. However, their reported sensitivity to magnetic fields at low frequencies (≲1 kHz) is presently ≳10 pTs 1/2 , precluding potential applications in medical imaging, geoscience, and navigation. Here we show that high-permeability magnetic flux concentrators, which collect magnetic flux from a larger area and concentrate it into the diamond sensor, can be used to improve the sensitivity of diamond magnetometers. By inserting an NV-doped diamond membrane between two ferrite cones in a bowtie configuration, we realize a ~ 250-fold increase of the magnetic field amplitude within the diamond. We demonstrate a sensitivity of ~ 0.9pTs 1/2 to magnetic fields in the frequency range between 10 and 1000 Hz. This is accomplished using a dual-resonance modulation technique to suppress the effect of thermal shifts of the NV spin levels. The magnetometer uses 200 mW of laser power and 20 mW of microwave power. This work introduces a new degree of freedom for the design of diamond sensors by using structured magnetic materials to manipulate magnetic fields.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Five-analyzer Johann spectrometer for hard X-ray photon-in/photon-out spectroscopy at the Inner Shell Spectroscopy beamline at NSLS-II: design, alignment and data acquisition

Here, a recently commissioned five-analyzer Johann spectrometer at the Inner Shell Spectroscopy beamline (8-ID) at the National Synchrotron Light Source II (NSLS-II) is presented. Designed for hard X-ray photon-in/photon-out spectroscopy, the spectrometer achieves a resolution in the 0.5–2 eV range, depending on the element and/or emission line, providing detailed insights into the local electronic and geometric structure of materials. It serves a diverse user community, including fields such as physical, chemical, biological, environmental and materials sciences. This article details the mechanical design, alignment procedures and data-acquisition scheme of the spectrometer, with a particular focus on the continuous asynchronous data-acquisition approach that significantly enhances experimental efficiency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Privacy Preservation from High-Performance Computing to Autonomous Science [Industrial and Governmental Activities]

High-Performance Computing (HPC) and Leadership-Class Supercomputing are driving forces behind scientific advancements, enabling researchers to tackle complex challenges in physics, chemistry, biology, and engineering. These systems power vast simulations and data analyses, fueling discoveries in fields ranging from materials science to climate modeling. However, their use often involves processing sensitive data—such as proprietary industry simulations, biomedical records, and national security computations—posing significant privacy concerns. In conclusion, this issue is amplified in collaborative environments like Department of Energy (DOE) user facilities, where HPC resources are shared across institutions to foster innovation.

Kotevska, Olivera [Oak Ridge National Laboratory (↗
DOE OSTI2022

A re-examination of the mechanism of whiting events: A new role for diatoms in Fayetteville Green Lake (New York, USA)

Whiting events—the episodic precipitation of fine-grained suspended calcium carbonates in the water column—have been documented across a variety of marine and lacustrine environments. Whitings likely are a major source of carbonate muds, a constituent of limestones, and important archives for geochemical proxies of Earth history. While several biological and physical mechanisms have been proposed to explain the onset of these precipitation events, no consensus has been reached thus far. Fayetteville Green Lake (New York, USA) is a meromictic lake that experiences annual whitings. Materials suspended in the water column collected through the whiting season were characterized using scanning electron microscopy and scanning transmission X-ray microscopy. Whitings in Fayetteville Green Lake are initiated in the spring within the top few meters of the water column, by precipitation of fine amorphous calcium carbonate (ACC) phases nucleating on microbial cells, as well as on abundant extracellular polymeric substances (EPS) frequently associated with centric diatoms. Whiting particles found in the summer consist of 5–7 μm calcite grains forming aggregates with diatoms and EPS. Simple calculations demonstrate that calcite particles continuously grow over several days, then sink quickly through the water column. In the late summer, partial calcium carbonate dissolution is observed deeper in the water column. Settling whiting particles, however, reach the bottom of the lake, where they form a major constituent of the sediment, along with diatom frustules. The role of diatoms and associated EPS acting as nucleation surfaces for calcium carbonates is described for the first time here as a potential mechanism participating in whitings at Fayetteville Green Lake. This mechanism may have been largely overlooked in other whiting events in modern and ancient environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Performance of novel VUV-sensitive Silicon Photo-Multipliers for nEXO

Liquid xenon time projection chambers are promising detectors to search for neutrinoless double beta decay (0νββ), due to their response uniformity, monolithic sensitive volume, scalability to large target masses, and suitability for extremely low background operations. The nEXO collaboration has designed a tonne-scale time projection chamber that aims to search for 0νββ of 136 Xe with projected half-life sensitivity of 1.35 x 10 28 yr. To reach this sensitivity, the design goal for nEXO is ≤1% energy resolution at the decay Q-value (2458.07 ± 0.31 keV). Reaching this resolution requires the efficient collection of both the ionization and scintillation produced in the detector. The nEXO design employs Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm scintillation light of liquid xenon. This paper reports on the characterization of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3 SiPMs specifically designed for nEXO, as well as new measurements on new test samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters (MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct crosstalk, correlated avalanches and photon detection efficiency were measured as a function of the applied over voltage and wavelength at liquid xenon temperature (163 K). The results from this study are used to provide updated estimates of the achievable energy resolution at the decay Q-value for the nEXO design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The 20th Gray lecture 2019: Health and heavy ions

Particle radiobiology has contributed new understanding of radiation safety and underlying mechanisms of action to radiation oncology for the treatment of cancer, and to planning of radiation protection for space travel. This manuscript will highlight the significance of precise physical and biologically effective dosimetry to this translational research for the benefit of human health. This review provides a brief snapshot of the evolving scientific basis for, and the complex current global status, and remaining challenges of hadron therapy for the treatment of cancer. The need for particle radiobiology for risk planning in return missions to the Moon, and exploratory deep-space missions to Mars and beyond are also discussed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Unexpected symmetry breaking in ferroelectric wurtzite thin films on silicon observed by optical second harmonic generation

Optical second harmonic generation (SHG) exists as a popular tool for probing materials with broken inversion symmetry in the physical and biological sciences. SHG polarimetry can reveal material anisotropy with high sensitivity, including point group and phase transitions. Here, we probe ferroelectric wurtzite films with a nominal 6 mm symmetry under a normal reflection geometry using SHG microscopy and discover an unexpected symmetry breaking. Symmetry considerations would normally forbid the detection of the SHG signal when light propagates along the polar 6-fold rotation axis. Yet a uniquely anisotropic SHG response is observed in this geometry in Al 1-x B x N, Al 1-x Sc x N, Zn 1-x Mg x O, and AlN/Al 1-x Sc x N heterostructures grown on silicon that can be modeled by an average monoclinic symmetry of point group m. A significant enhancement of the SHG signal corresponding to up to a 5.3× increase in the SHG intensity (hence ∼2.3 × in effective SHG tensor coefficient) is observed at antiparallel polar domain walls, suggesting local cooperative alignment of symmetry-breaking structural distortions. Namely, it is found that the monoclinic mirror plane is oriented predominantly perpendicular to the walls. Such increases in domain wall SHG thus reveal that subtle symmetry breaking can be a pathway to large property enhancements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep learning enhanced super-resolution x-ray fluorescence microscopy by a dual-branch network

X-ray fluorescence (XRF) microscopy is a powerful technique for quantifying the distribution of elements in complex materials, which makes it a crucial imaging technique across a wide range of disciplines in physical and biological sciences, including chemistry, materials science, microbiology, and geosciences. However, as a scanning microscopy technique, the spatial resolution of XRF imaging is inherently constrained by the x-ray probe profile and scanning step size. Here we propose a dual-branch machine learning (ML) model, which can extract scale-variant features and bypass abundant low-frequency information separately, to enhance the spatial resolution of the XRF images by mitigating the effects of blurring from the probe profile. The model is trained by simulated natural images, and a two-stage training strategy is used to overcome the domain gap between the natural images and experimental data. The tomography reconstruction from enhanced XRF projections shows an improvement in resolution by a scale factor of four and reveals distinct internal features invisible in low-resolution XRF within a battery sample. This study offers a promising approach for obtaining high-resolution XRF imaging from its low-resolution version, paving the way for future investigations in a broader range of disciplines and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantitative Nonlinear Optical Polarimetry with High Spatial Resolution

Nonlinear optical microscopy such as in the optical second-harmonic generation (SHG) modality has become a popular tool today for probing materials in the physical and biological sciences. While imaging and spectroscopy are widely used in the microscopy mode, nonlinear polarimetry, which can shed light on materials’ symmetry and microstructure, is relatively underdeveloped. This is partly because quantitative analytical modeling of the optical SHG response for anisotropic crystals and films largely assumes low-numerical aperture (NA) focusing of light, where the plane-wave approximation is sufficient. Tight focusing provides unique benefits in revealing out-of-plane polarization responses, which cannot be detected by near-plane-wave illumination at normal incidence. Here, we outline a method for quantitatively analyzing SHG polarimetry measurements obtained under high-NA focusing within a microscope geometry. Experiments and simulations of a variety of standard samples, from single crystals to thin films, are in good agreement, including measured and simulated spatial SHG maps of ferroelectric domains. A solution to the inverse problem is demonstrated, where the spatial distribution of an SHG tensor with unknown tensor coefficient magnitudes is determined by experimentally measured polarimetry. The ability to extract the out-of-plane component of the nonlinear polarization in normal incidence is demonstrated, which can be valuable for high-resolution polarimetry of 2D materials, thin films, heterostructures, and uniaxial crystals with a strong out-of-plane response.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Better together: Elements of successful scientific software development in a distributed collaborative community

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities

97 MATHEMATICS AND COMPUTING↗