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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coherence and superradiance from a plasma-based quasiparticle accelerator

Coherent light sources, such as free electron lasers, provide bright beams for biology, chemistry, physics, and advanced technological applications. Increasing the brightness of these sources requires progressively larger devices, with the largest being several km long (e.g., LCLS). Can we reverse this trend, and bring these sources to the many thousands of labs spanning universities, hospitals, and industry? Here we address this long-standing question by rethinking the basic principles of radiation physics. At the core of our work is the introduction of quasiparticle-based light sources that rely on the collective and macroscopic motion of an ensemble of light-emitting charges to evolve and radiate in ways that would be unphysical when considering single charges. The underlying concept allows for temporal coherence and superradiance in new configurations, such as in plasma accelerators, providing radiation with intriguing properties and clear experimental signatures spanning nearly 10 octaves, from THz to the extreme ultra-violet. The concept extends well beyond this case, such as to nonlinear optical configurations. Furthermore, the simplicity of the quasiparticle approach makes it suitable for experimental demonstrations at existing laser and accelerator facilities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Directional self-locomotion of active droplets enabled by nematic environment

Active matter comprised of self-propelled interacting units holds a major promise for the extraction of useful work from its seemingly chaotic dynamics. Streamlining active matter is especially important at microscale, where the viscous forces prevail over inertia and transport requires a non-reciprocal motion. Here we report that microscopic active droplets representing aqueous dispersions of swimming bacteria Bacillus subtilis become unidirectionally motile when placed in an inactive nematic liquid crystal medium. Random motion of bacteria inside the droplet is rectified into a directional self-locomotion of the droplet by the polar director structure that the droplet creates in the surrounding nematic through anisotropic molecular interactions at its surface. Droplets without active swimmers show no net displacement. The trajectory of the active droplet can be predesigned by patterning the molecular orientation of the nematic. As a result, the effect demonstrates that broken spatial symmetry of the medium can be the reason for and the means to control directional microscale transport.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Emergent actin flows explain distinct modes of gliding motility

During host infection, Toxoplasma gondii and related unicellular parasites move using gliding, which differs fundamentally from other known mechanisms of eukaryotic cell motility. Gliding is thought to be powered by a thin layer of flowing filamentous (F)-actin sandwiched between the plasma membrane and a myosin-covered inner membrane complex. How this surface actin layer drives the various gliding modes observed in experiments—helical, circular, twirling and patch, pendulum or rolling—is unclear. Here we suggest that F-actin flows arise through self-organization and develop a continuum model of emergent F-actin flow within the confines provided by Toxoplasma geometry. In the presence of F-actin turnover, our model predicts the emergence of a steady-state mode in which actin transport is largely directed rearward. Removing F-actin turnover leads to actin patches that recirculate up and down the cell, which we observe experimentally for drug-stabilized actin bundles in live Toxoplasma gondii parasites. These distinct self-organized actin states can account for observed gliding modes, illustrating how different forms of gliding motility can emerge as an intrinsic consequence of the self-organizing properties of F-actin flow in a confined geometry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Fusion and fission events regulate endosome maturation and viral escape

Endosomes are intracellular vesicles that mediate the communication of the cell with its extracellular environment. They are an essential part of the cell’s machinery regulating intracellular trafficking via the endocytic pathway. Many viruses, which in order to replicate require a host cell, attach themselves to the cellular membrane; an event which usually initiates uptake of a viral particle through the endocytic pathway. In this way viruses hijack endosomes for their journey towards intracellular sites of replication and avoid degradation without host detection by escaping the endosomal compartment. Recent experimental techniques have defined the role of endosomal maturation in the ability of enveloped viruses to release their genetic material into the cytoplasm. Endosome maturation depends on a family of small hydrolase enzymes (or GTPases) called Rab proteins, arranged on the cytoplasmic surface of its membrane. Here, we model endosomes as intracellular compartments described by two variables (its levels of active Rab5 and Rab7 proteins) and which can undergo coagulation (or fusion) and fragmentation (or fission). The key element in our approach is the “per-cell endosomal distribution” and its dynamical (Boltzmann) equation. The Boltzmann equation allows us to derive the dynamics of the total number of endosomes in a cell, as well as the mean and the standard deviation of its active Rab5 and Rab7 levels. We compare our mathematical results with experiments of Dengue viral escape from endosomes. The relationship between endosomal active Rab levels and pH suggests a mechanism that can account for the observed variability in viral escape times, which in turn regulate the viability of a viral intracellular infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Golden ratio in venation patterns of dragonfly wings

Abstract The vein pattern in insect wings allows this lightweight structure to carry multiple biological functions. Here, an investigation of the angular distribution of the vein struts in dragonfly wings revealed that the golden angle or golden ratio dominates the venation patterns. We find that the golden angle dominates the intervein angles in regions where thin veins and membranes demand strength reinforcement. A golden ratio partition method has thus been developed that explains a set of preferred intervein angles in distorted polygon-shaped venation cells throughout the venation pattern in dragonfly wings. These observations provide new evidence that the wing structure is spatially optimized, by the golden rule in nature, for supporting biomechanical functions of dragonfly wings.

36 MATERIALS SCIENCE↗
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 OSTI2023

All scales must be considered to understand rifts

Feedbacks between chemical, physical, and biological processes at rift zones evolve through various time (seconds to 10 7 yrs) and spatial (microns to 10 6 m) scales. Here, we discuss how consideration of these scales is needed to tap rift energy, water, and mineral resources safely and equitably while preserving biodiversity in these changing settings.

58 GEOSCIENCES↗
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 (↗