Crystal structure of a conformational antibody that binds tau oligomers and inhibits pathological seeding by extracts from donors with Alzheimer's disease
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “physical sciences and engineering”
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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Exclusion and Verification of Remote Nuclear Reactors with a 1-kiloton Gd -Doped Water Detector
To date, antineutrino experiments built for the purpose of demonstrating a nonproliferation capability have typically employed organic scintillators situated as close to the core as possible (typically at a distance of a few meters to tens of meters) and have not exceeded a few tons in size. One problem with this approach is that proximity to the reactor core requires accommodation by the host facility. Water Cherenkov detectors located offsite, at distances of a few kilometers or greater, may facilitate nonintrusive monitoring and verification of reactor activities over a large area. As the standoff distance increases, the detector target mass must scale accordingly. This paper quantifies the degree to which a kiloton-scale gadolinium-doped water Cherenkov detector can exclude the existence of undeclared reactors within a specified distance, and remotely detect the presence of a hidden reactor in the presence of declared reactors, by verifying the operational power and standoff distance using a Feldman-Cousins-based likelihood analysis. A 1-kton scale (fiducial) water Cherenkov detector can exclude gigawatt-scale nuclear reactors up to tens of kilometers within a year. In conclusion, when attempting to identify the specific range and power of a reactor, the detector energy resolution is not sufficient to delineate between the two.
42 ENGINEERING↗
Effect of frequency and applied voltage of an atmospheric-pressure dielectric-barrier discharge on breakdown and hydroxyl-radical generation with a liquid electrode
This work examines the effect of the frequency and peak applied voltage on hydroxyl-radical generation in a dielectric-barrier plasma discharge between a metallic needle electrode and one electrode covered with dielectric. The authors examine a system that can expose up to 96 liquid samples in an automated fashion without human intervention beyond setting the initial software configuration. Then, hydroxylradical concentration, measured through coumarin fluorescence, was measured for 5 s plasma exposures generated under different highvoltage conditions with frequencies from 2 to 16 kHz and amplitudes from 4 to 9 kV. Their results show that an increase in frequency and/or applied voltage, within the range prescribed above and the limits of the high-voltage power supply, can yield up to a 150% increase in fluorescence with an equivalent hydroxyl-radical increase. Applications using typical previous methods, such as the Fenton Reaction, are limited in that they continuously generate hydroxyl radicals over millisecond and longer intervals. These results establish the electrical parameters that can now be applied to polymers, like proteins, which show three dimensional structures that are flexible and fluctuate on a microsecond and nanosecond time scale, with hydroxyl-radical generation on this time scale using this device. Additionally, plasma exposures may be optimized for a great variety of proteins, devices and techniques, where hydroxyl-radical generation is of utmost importance, reducing exposure time and potential subjection of samples to harmful side effects.
42 ENGINEERING↗
Science & Technology Review: Awards for Livermore Innovation
At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review (S&TR) is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world. In 2021, Lawrence Livermore technologies received three R&D 100 awards, which honor the year’s top 100 innovations from around the world. The feature article beginning on p. 4 describes the Laboratory’s winners: the Multiplicity Counter for Thermal and Fast Neutrons, Flux, and the Optical Transconductance Varistor. The 2021 awards raised the Laboratory’s total R&D 100 awards to 173 since 1978. The R&D 100 logo is reprinted in this issue with permission from R&D World magazine.
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Understanding Proton Movement in [Fe-Fe] Hydrogenases
Nature uses specialized metalloenzymes to carry out small molecule activation reactions, including CO 2 fixation, O 2 activation, and proton reduction, with unparalleled efficiency, rates, and selectivity. The latter reactions are performed by hydrogenases, protein metallo-complexes that interconverts H 2 to protons and electrons (H 2 oxidation) and the reverse reaction (H 2 production) with incredibly low energy input and amazingly fast kinetics. Reproducing both the activity and efficiency of metalloenzymes in sustainable anthropogenic systems remains one of the “holy grails” of inorganic chemistry. However, identifying the precise molecular components responsible for these desirable properties has been challenging in the natural metalloenzymes, hindering efforts to develop analogous processes in synthetic compounds. Considering the inherent complexity of a metalloenzyme and the many interactions, both strong and weak, that contribute to the function of an enzyme, we have elected to model natural metalloenzymes on a biochemical platform. Towards this end, we have a developed structural, functional, and mechanistic mimic of the [Ni-Fe] hydrogenases within a robust protein scaffold, rubredoxin, to understand the influence of the secondary coordination environment on the metal center. This involved preparing a series of three rubredoxin constructs containing a single point mutation at Val positions and making the NMR chemical shift assignments for the paramagnetic (nickel-substituted) and non-paramagnetic (zinc-substituted) form. These physical studies were complemented with in silico molecular dynamic studies on proteins with [Fe-S] clusters to engineer new proton channels to test in vitro . To assist our search for new natural metalloprotein scaffolds within the vast number of sequenced genomes, we created a neural network-based program to identify proteins with specific metal-binding sites. These computational and physical studies with metalloenzymes provide direct insight into the fundamental chemical principles driving the natural systems and offer design principles for developing catalysts that utilize analogous principles.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Development of Structure–Property Relationships for Ammonium Transport through Charged Organogels
Ammonia is a promising carbon-free fuel, but current methods to produce ammonia are energy intensive. New methods are thereby needed, with one promising method being electrochemical nitrogen reduction cells. Efficient cell operation requires robust catalysts but also efficient membrane separators that permit the selective transport of ions while minimizing the transport of the products across the cell. Commercial membranes have an unknown morphology which makes designing improved cells challenging. To address this problem, we synthesized a series of membranes with controlled crosslinking density and chemical composition to understand their impact on ammonium transport. Higher crosslinking density led to lower ammonium permeability. At the highest crosslinking density, similar ammonium permeability was observed independent of the water volume fraction and hydrophobicity of the monomers. These results suggest new directions to develop membranes with reduced ammonium crossover to improve the efficiency of these electrochemical cells.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Distributed chemical sensing for CO2 leakage monitoring
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Engineering - Electronic and electrical engineerin↗
Revealing the Origin and Nature of the Buried Metal‐Substrate Interface Layer in Ta/Sapphire Superconducting Films
Abstract Despite constituting a smaller fraction of the qubit's electromagnetic mode, surfaces and interfaces can exert significant influence as sources of high‐loss tangents, which brings forward the need to reveal properties of these extended defects and identify routes to their control. Here, we examine the structure and composition of the metal‐substrate interfacial layer that exists in Ta/sapphire‐based superconducting films. Synchrotron‐based X‐ray reflectivity measurements of Ta films, commonly used in these qubits, reveal an unexplored interface layer at the metal‐substrate interface. Scanning transmission electron microscopy and core‐level electron energy loss spectroscopy identified an intermixing layer (≈0.65 ± 0.05 nm) at the metal‐substrate interface containing Al, O, and Ta atoms. Density functional theory modeling reveals that the structure and properties of the Ta/sapphire heterojunctions are determined by the oxygen content on the sapphire surface prior to Ta deposition for two atomic terminations of sapphire. Using a multimodal approach, we gained deeper insights into the interface layer between the metal and substrate, which suggests that the orientation of deposited Ta films depend on the surface termination of sapphire. The observed elemental intermixing at the metal‐substrate interface influences the thermodynamic stability and electronic behavior of the film, which may also affect qubit performance.
36 MATERIALS SCIENCE↗
Barium ion sensing with IPG K + molecular probes
Fluorophores covalently bound to azacrown ether ionophores can be assembled into sensitive turn-on chemosensors. The size specificity and electron-rich nature of the ionophore's binding domain contribute to both selectivity and strong turn-on fluorescence sensing by various mechanisms when properly constructed. Aza-18-crown-6 ethers are quite selective for binding to K + and Ba 2+ , yet the more electron-withdrawing dicationic nature of barium imposes a larger electronic effect on turn-on fluorescent sensors. Barium chemosensors can be important for measuring soluble Ba 2+ in drinking water and have gained recent attention for their potential to enhance the detection of rare events in xenon decay. Here we quantify the capability of three chemosensors, marketed for biologically useful K + sensing, as effective probes for Ba 2+ ions. Here, we present measurements from bulk spectrofluorometry to characterize the system in aqueous solutions and demonstrate the usefulness of these species for low-background single-ion fluorescence microscopy, revealing new candidates for Ba 2+ sensing.
Miller, R. L. [Department of Chemistry and Biochem↗
Science & Technology Review June 2026: Predicting Tsunamis
At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
X-ray thermal diffuse scattering as a texture-robust temperature diagnostic for dynamically compressed solids
We present a model of x-ray thermal diffuse scattering (TDS) from a cubic polycrystal with an arbitrary crystallographic texture, based on the classic approach of Warren [B. E. Warren, Acta Crystallogr. 6, 803 (1953)]. We compare the predictions of our model with femtosecond x-ray diffraction patterns gathered from ambient and dynamically compressed rolled copper foils obtained at the High Energy Density instrument of the European X-Ray Free-Electron Laser facility and find that the texture-aware TDS model yields more accurate results than does the conventional powder model owed to Warren. Nevertheless, we further show: with sufficient angular detector coverage, the TDS signal is largely unchanged by sample orientation and in all cases strongly resembles the signal from a perfectly random powder; shot-to-shot fluctuations in the TDS signal resulting from grain-sampling statistics are at the percent level, in stark contrast to the fluctuations in the Bragg-peak intensities (which are over an order of magnitude greater); and TDS is largely unchanged even following texture evolution caused by compression-induced plastic deformation. We conclude that TDS is robust against texture variation, making it a flexible temperature diagnostic applicable just as well to off-the-shelf commercial foils as to ideal powders.
Crystal lattices↗
A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0
SAND2024-01040O PyRoCS software synthesizes mathematical equations from several domains—including information theory, ecology, and engineering sciences—to support resilience analysis for complex systems. Resilience is the ability of the complex system being analyzed to withstand, operate through, and recover from a disruption. The complex system can be a physical system such as an electric grid, an organization such as a company, or even a subfunction of an organization. Existing mathematical equations for resilience analysis are found within multiple domains including information theory, biological sciences, and complex systems. This package synthesizes and refactors equations from these various domains to make them more generalizable for application across different types of complex systems relevant for resilience analysis. Users will be able to apply these equations to characterize different components of complex systems based on available data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Verzi, Stephen↗
Enhanced magnetic anisotropy in (Fe0.7-xCo0.3Zrx)2 B nanocrystallites
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Joshi, Pramanand [Department of Physics, Universit↗
CFD Simulation of Liquid Rocket Engine Injectors
Detailed design issues associated with liquid rocket engine injectors and combustion chamber operation require CFD methodology which simulates highly three-dimensional, turbulent, vaporizing, and combusting flows. The primary utility of such simulations involves predicting multi-dimensional effects caused by specific injector configurations. SECA, Inc. and Engineering Sciences, Inc. have been developing appropriate computational methodology for NASA/MSFC for the past decade. CFD tools and computers have improved dramatically during this time period; however, the physical submodels used in these analyses must still remain relatively simple in order to produce useful results. Simulations of clustered coaxial and impinger injector elements for hydrogen and hydrocarbon fuels, which account for real fluid properties, is the immediate goal of this research. The spray combustion codes are based on the FDNS CFD code' and are structured to represent homogeneous and heterogeneous spray combustion. The homogeneous spray model treats the flow as a continuum of multi-phase, multicomponent fluids which move without thermal or velocity lags between the phases. Two heterogeneous models were developed: (1) a volume-of-fluid (VOF) model which represents the liquid core of coaxial or impinger jets and their atomization and vaporization, and (2) a Blob model which represents the injected streams as a cloud of droplets the size of the injector orifice which subsequently exhibit particle interaction, vaporization, and combustion. All of these spray models are computationally intensive, but this is unavoidable to accurately account for the complex physics and combustion which is to be predicted, Work is currently in progress to parallelize these codes to improve their computational efficiency. These spray combustion codes were used to simulate the three test cases which are the subject of the 2nd International Workshop on-Rocket Combustion Modeling. Such test cases are considered by these investigators to be very valuable for code validation because combustion kinetics, turbulence models and atomization models based on low pressure experiments of hydrogen air combustion do not adequately verify analytical or CFD submodels which are necessary to simulate rocket engine combustion. We wish to emphasize that the simulations which we prepared for this meeting are meant to test the accuracy of the approximations used in our general purpose spray combustion models, rather than represent a definitive analysis of each of the experiments which were conducted. Our goal is to accurately predict local temperatures and mixture ratios in rocket engines; hence predicting individual experiments is used only for code validation. To replace the conventional JANNAF standard axisymmetric finite-rate (TDK) computer code 2 for performance prediction with CFD cases, such codes must posses two features. Firstly, they must be as easy to use and of comparable run times for conventional performance predictions. Secondly, they must provide more detailed predictions of the flowfields near the injector face. Specifically, they must accurately predict the convective mixing of injected liquid propellants in terms of the injector element configurations.
Farmer, Richard↗
Giant proximity exchange and flat Chern band in 2D magnet-semiconductor heterostructures
van der Waals (vdW) heterostructures formed by two-dimensional (2D) magnets and semiconductors have provided a fertile ground for fundamental science and spintronics. We present first-principles calculations finding a proximity exchange splitting of 14 meV (equivalent to an effective Zeeman field of 120 T) in the vdW magnet semiconductor heterostructure MoS 2 /CrBr 3 , leading to a 2D spin-polarized half-metal with carrier densities ranging up to 10 13 cm -2 . We consequently explore the effect of large exchange coupling on the electronic band structure when the magnetic layer hosts chiral spin textures such as skyrmions. A flat Chern band is found at a “magic” value of magnetization $\overline{m}$ ~ 0.2 for Schrödinger electrons, and it generally occurs for Dirac electrons. The magnetic proximity–induced anomalous Hall effect enables transport-based detection of chiral spin textures, and flat Chern bands provide an avenue for engineering various strongly correlated states.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates
Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.
36 MATERIALS SCIENCE↗
Synergistic learning with multi-task DeepONet for efficient PDE problem solving
Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.
42 ENGINEERING↗
Multiple Discipline science assessment
Various science disciplines were examined to determine where and when it is appropriate to include their objectives in the planning of planetary missions. The disciplines considered are solar astronomy, stellar and galactic astronomy, solar physics, cosmology and gravitational physics, the geosciences and the applied sciences. For each discipline, science objectives are identified which could provide a multiple discipline opportunity utilizing either a single spacecraft or two spacecraft delivered by a single launch vehicle. Opportunities using a common engineering system are also considered. The most promising opportunities identified include observations of solar images and relativistic effects using the Mercury orbiter; collection of samples exposed to solar radiation using the Mars surface sample return; studies of interstellar neutral H and He, magnetic fields, cosmic rays, and solar physics during Pluto or Neptune flybys; using the Mars orbiter to obtain solar images from 0.2 AU synchronous or from 90 deg orbit; and the study of the structure and composition of the atmosphere using atmospheric probes and remotely piloted vehicles.
Wells, W. C.↗