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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 109 records · Page 6

$2+1$ dimensional Floquet systems and lattice fermions: Exact bulk spectral equivalence

A connection has recently been proposed between periodically driven systems known as Floquet insulators in continuous time and static fermion theories in discrete time. This connection has been established in a (1+1) ( 1 + 1 ) -dimensional free theory, where an explicit mapping between the spectra of a Floquet insulator and a discrete-time Dirac fermion theory has been formulated. Here we investigate the potential of static discrete-time theories to capture Floquet physics in higher dimensions, where so-called anomalous Floquet topological insulators can emerge that feature chiral edge states despite having bulk bands with zero Chern number. Starting from a particular model of an anomalous Floquet system, we provide an example of a static discrete-time theory whose bulk spectrum is an exact analytic match for the Floquet spectrum. The spectra with open boundary conditions in a particular strip geometry also match up to finite-size corrections. However, the models differ in several important respects. The discrete-time theory is spatially anisotropic, so that the spectra do not agree for all lattice terminations, e.g. other strip geometries or on half spaces. This difference can be attributed to the fact that the static discrete-time model is quasi-one-dimensional in nature and therefore has a different bulk-boundary correspondence than the Floquet model.

Iadecola, Thomas (ORCID:0000000251456441)↗

The Urban Deployment Model: A Toolset for the Simulation and Performance Characterization of Radiation Detector Deployments in Urban Environments

Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

House Advantage or House of Cards? Stacking the Deck for Data Videos Leads to Null Results: Preprint

Videos are becoming a ubiquitous means of sharing information on social media platforms. In response, data videos - short clips combining visualization with dynamic storytelling, audio descriptions, and spatial referencing - have gained popularity for communicating data. These affordances suggest that data videos might communicate data patterns, trends, and concepts more effectively than static visualizations, enhancing comprehension. However, existing research has not systematically tested this claim. To address this gap, we conducted three controlled studies to measure comprehension differences between data videos and static visualizations. Despite leveraging visual cues and audio explanations, no data video led to significantly better comprehension than an analogous static visualization. Our results suggest data videos are not categorically better and that future research should examine the tradeoffs between their engagement benefits and costs.

97 MATHEMATICS AND COMPUTING↗

Solid face sheets enable lattice metamaterials to withstand high-amplitude impulsive loading without yielding

Owing to their ability to provide tunable mechanical responses, lattice materials are frequently studied to elucidate their response to static and dynamic loads. However, these roles are typically in opposition: static loads must be supported sufficiently far away from the onset of buckling or yielding, whereas dynamic loads are typically ameliorated by crushing of the lattice, which provides excellent energy-absorption due to the large plastic deformation accompanying densification. In contrast, this work considers the octet truss as an exemplar topology, in a structural role where it must simultaneously support static loads while enduring high-amplitude impulsive loads. This study focuses on the ability to withstand impulsive loads without yielding, an essential prerequisite to enduring dual loading. Computational studies using the ALE3D hydrocode were performed to examine the response of the octet truss under a short temporal width impulse shape associated with laser-driven shocks. A key finding was that covering the lattice with a solid face sheet and treating this face sheet thickness as a design variable allows the Taylor-like pulse to be attenuated prior to entering the weaker lattice, at the cost of added mass up front. Experimental validation was accomplished by laser-driven shock testing, using octet trusses printed out of Ti-5Al-5V-5Mo-3Cr. The results show that for a given quantity of mass, the attenuation is maximized when as much mass as possible is moved into the face sheet, leaving a more slender lattice structure. The effect of placing mass in the face sheet rather than lattice beams dominates the effect of relative density, to the point where a low-mass structure with most of the mass concentrated in the face sheet can outperform a high-mass structure with most of the mass in the lattice. Finally, by further understanding the propagation of short pulse width waves within under-dense structures, this study expand the domain of applicability of such structures, including lattice materials, to challenging dual-loading regimes spanning decades of strain rates.

36 MATERIALS SCIENCE↗

Experimental investigation into coal wettability changes caused by reactions with scCO 2 -H 2 O

Geological CO 2 sequestration (GCS) can help mitigate global warming and enhance methane recovery from coal beds. However, few studies have linked the effects of CO 2 to surface chemistry changes controlling wetting behavior in deep coal beds. Contact angles (CAs) of CO 2 /N 2 -high volatile bituminous coal-water systems were measured under different temperatures and pressures. The surface chemistry and physical structure of coals were characterized to investigate changes in physicochemical properties and their relations with wettability after reactions. For N 2 treatment, the time-dependence of static and dynamic CAs were insignificant, ranging within 4°. For gaseous CO 2 treatment, the static CAs and the average advancing angles increased slightly. With supercritical (sc) CO 2 , both the static and dynamic CAs increased significantly, and θ adv changed to intermediate-wet (92°). Reactions with minerals exposed to scCO 2 resulted in greater surface roughness and heterogeneity, greater contact angle hysteresis and more surface sites occupied by scCO 2 rather than H 2 O. Increases in hydrophobic functional groups and decreases in hydrophilicity were shown by FTIR spectra, reflecting the shedding of polar oxygen-containing functional groups, reduction of hydrogen bonds, and increasing percentage of hydrocarbons. XRD patterns obtained following scCO 2 -treatment showed that crystallite growth and molecular polymerization were higher toward graphite-like. The calculated structural parameters of functional groups and crystallites both showed elevated coal rank. Changes in crystallite structure, notably higher carbon content and decreased negative surface charge, are unfavorable for water-wetting. Finally, this study contributes to understanding surface chemistry changes responsible for decreased wettability during CO 2 -enhanced coal bed methane recovery and GCS in coal reservoirs.

01 COAL, LIGNITE, AND PEAT↗

Efficient 15 N hyperpolarization of [ 15 N 3 ]metronidazole antibiotic via spin-relayed pulsed SABRE-SHEATH

Signal Amplification by Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei (SABRE-SHEATH) is an NMR hyperpolarization technique that relies of the simultaneous exchange of parahydrogen and a to-be-hyperpolarized molecule on the metal center of a polarization-transfer catalyst in a microtesla magnetic field. Until recently, this method has been understood to perform hyperpolarization by establishing level anti-crossings between the nuclear spins of the parahydrogen derived hydrides (acting as a source of hyperpolarization) and those of the substrate. Recently, the application of highly non-intuitive pulse sequences (comprising pulses of microtesla DC fields) was predicted to hyperpolarize nuclear spins more efficiently than the canonical (static-field) SABRE-SHEATH approach. Here we show that by employing a basic “on-off” pulse sequence of rectangular microtesla pulses, it is possible to improve the hyperpolarization efficiency for SABRE-SHEATH of [ 15 N 3 ]metronidazole, an FDA-approved antibiotic (in non-enriched and non-hyperpolarized form) and potential hypoxia sensing molecule. Specifically, we demonstrate that 15N polarization of 18.5 % can be obtained in 80 s of parahydrogen bubbling parahydrogen through a solution containing 20 mM [ 15 N 3 ]metronidazole. In practice, (1.32 ± 0.14)-fold improvements in P 15N was obtained with the pulsed method described here compared to static field technique variant. These results show that pulsed SABRE-SHEATH was successfully applied to 15 N-labeled biologically relevant molecule. Moreover, we also demonstrate that although the pulsed SABRE-SHEATH sequence was designed for polarization transfer from parahydrogen derived hydrides to the metronidazole’s 15 N catalyst-binding site, all three 15 N sites of [ 15 N 3 ]metronidazole attained the hyperpolarized state. This spin-relayed polarization transfer becomes possible due to the 15 N relay network established by their spin-spin J-couplings. The feasibility of the spin-relayed polarization transfer is demonstrated here for the first time for pulsed SABRE-SHEATH (as opposed to the static-field SABRE-SHEATH reported previously) and it paves the way to broad applicability of the technique.

Hyperpolarization↗

Shear rate dependency on flowing granular biomass material

The commercialization of bioenergy has been significantly limited by various material handling issues due to the poor flowability of granular biomass materials. A good understanding of flow physics and robust constitutive models to predict flow behavior across multiple regimes are essential to address these issues. In this study, we investigated the multi-regime flow behavior of loblolly pine chips, a widely used bioenergy feedstock, through comprehensive inclined plane flow experiments and simulations. A quasi-static hypoplastic model and a cross-regime Drucker-Prager-µ(I) model were calibrated and validated against the physical experiments to investigate the quasi-static and dense flow behavior. The results show that for granular biomass, 1) plane flow (iso-thickness along the plane) exists within a smaller range of inclination while heap flow (varying thickness along the plane) exists within a broader range of inclination, as compared with conventional granular materials (e.g., glass beads); 2) the scaling law of granular biomass flowing on an inclined plane (Froude Number versus dimensionless thickness) forms a bi-linear trend with the turning point governed by the quasi-static and dense flow regimes; 3) the multi-regime DP-µ(I) model can capture the flow behavior in both regimes well at the cost of extra calibration. In conclusion, these findings advance the scientific understanding of the multi-regime flow behavior of granular biomass materials and shed light on formulating novel constitutive models to assist granular biomass handling in the bioenergy industry.

09 BIOMASS FUELS↗

Accelerated Steam Methane Reforming by Dynamically Applied Charges

Catalyst design has traditionally focused on tuning active site properties to optimally bind reaction intermediates and balance the kinetic requirements of multiple competing chemical processes, as necessitated by the Sabatier principle. It has recently been proposed that for reactions following certain potential energy landscapes, the activity limit imposed by the Sabatier principle may be overcome by using programmed oscillations of surface electron density at the timescales of surface reactions (i.e., “catalytic resonance”). Here, we use a combination of density functional theory (DFT) simulations and transient kinetic models (TKMs) to simulate the kinetics of steam methane reforming (SMR) on Ru(211) surfaces under statically and dynamically applied charges. DFT-calculated binding energies of SMR intermediates and transition states exhibit strong sensitivity to positively applied charges and follow unique scaling relationships that deviate from linear periodic trends across transition metals. Our simulations demonstrate that applying a small positive charge to Ru dramatically enhances the steady-state turnover frequency (TOF) of SMR by up to 5 orders of magnitude above the TOF observed over neutral Ru. Thus, statically charging Ru catalysts may be an effective strategy to lower the temperature requirements for SMR. Dynamic square-wave oscillations in charge resulted in SMR catalytic resonance with an onset frequency f ∼ 106 Hz and the corresponding average TOFs exceeding the statically charged Ru surface by an additional 15%. Here, based on sensitivity analyses performed for the two end points of oscillation, we propose that dynamic TOF improvement beyond the Sabatier maximum can be expected when the system oscillates between two kinetic regimes that are uniquely controlled by distinct elementary steps.

Catalysts↗

Enhanced Stability and Sensitivity for CA-125 Detection Under Microfluidic Shear Flow Using Polyethylene Glycol-Coated Biosensor

The microfluidic-based point-of-care (POC) diagnostic tool has garnered significant interest in recent years, offering rapid and cost-effective disease detection. There is a growing trend toward integrating microfluidic platforms with biosensors, aligning lab-on-a-chip technologies with POC diagnostic devices. Despite numerous efforts to incorporate biosensors into microfluidic systems, researchers have performed very limited investigations on the stability of biomarker detection when biosensors operate under microfluidic shear flow conditions. Gold nanoparticles (AuNPs) are a widely employed material in capacitive biosensors for antibody immobilization and sensitivity enhancement. However, AuNPs have limitations in providing stable detection of biomarkers within microfluidic shear flow due to their agglomeration nature. This study addresses these limitations by employing 2 kDa polyethylene glycol (PEG) as an intermediate biofunctional layer to immobilize CA-125 antibodies on gold-interdigitated electrodes for the stable and accurate detection of CA-125 antigens. The stabilities and sensitivities of AuNPs and PEG-coated biosensors are evaluated under both static drop and microfluidic shear flow conditions for CA-125 antigen detection. The experimental results demonstrate a capacitive signal response (5660 pF at 10 kHz) 2.2 times higher using the PEG-coated biosensor than the signal (2551 pF at 10 kHz) measured by the AuNP-coated biosensor in the detection of CA-125 antigen–antibody conjugation under static drop conditions, indicating the higher sensitivity of the PEG-coated biosensor. Additionally, the PEG-coated biosensor exhibits better consistency for the CA-125 antigen detection between static drop and microfluidic shear flow conditions (Cp decrease in percentage (ΔCp%↓) = 2.9% at 10 kHz) compared to the electrical signals measured using the AuNP-coated biosensor (ΔCp%↓ = 32.4% at 10 kHz), which suggests that the PEG-coated biosensor demonstrates higher stability for CA-125 antigen detection under microfluidic shear flow conditions. With these significant improvements brought by the PEG-coated biosensor, especially under microfluidic conditions, a substantial hurdle in developing electrical biosensors for POC diagnostic applications has been overcome, expediting further advancements in the field.

36 MATERIALS SCIENCE↗

Superionic fluoride gate dielectrics with low diffusion barrier for two-dimensional electronics

Exploration of new dielectrics with a large capacitive coupling is an essential topic in modern electronics when conventional dielectrics suffer from the leakage issue near the breakdown limit. Here, to address this looming challenge, we demonstrate that rare-earth metal fluorides with extremely low ion migration barriers can generally exhibit an excellent capacitive coupling over 20 μF cm -2 (with an equivalent oxide thickness of ~0.15 nm and a large effective dielectric constant near 30) and great compatibility with scalable device manufacturing processes. Such a static dielectric capability of superionic fluorides is exemplified by MoS 2 transistors exhibiting high on/off current ratios over 10 8 , ultralow subthreshold swing of 65 mV dec -1 and ultralow leakage current density of ~10 -6 A cm -2 . Therefore, the fluoride-gated logic inverters can achieve notably higher static voltage gain values (surpassing ~167) compared with a conventional dielectric. Furthermore, the application of fluoride gating enables the demonstration of NAND, NOR, AND and OR logic circuits with low static energy consumption. In particular, the superconductor–insulator transition at the clean-limit Bi 2 Sr 2 CaCu 2 O 8+δ can also be realized through fluoride gating. In conclusion, our findings highlight fluoride dielectrics as a pioneering platform for advanced electronic applications and for tailoring emergent electronic states in condensed matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Wigner polarons probe the dynamics of a Wigner crystal in a monolayer semiconductor

Wigner crystals—lattices made purely of electrons—provide a platform for studying correlation-driven quantum phase transitions. Despite extensive research, accessing the internal dynamics of Wigner crystals has remained challenging, with most experiments probing only static order or collective motion. Here we demonstrate optical probing and the manipulation of zero-field Wigner crystals and elucidate their static and dynamic properties in the frequency domain. We observe optical resonances that we identify as Wigner polarons—quasiparticles formed when the electron lattice is locally distorted by exciton–Wigner crystal coupling. We further achieve all-optical control of spins in the Wigner crystal, thereby directly probing valley-dependent Wigner polaron scattering well above the magnetic ordering temperature and in the absence of any external magnetic field. Lastly, we show optical melting of the Wigner crystal and observe different responses of the umklapp (static) and Wigner polaron (dynamic) resonances to optical excitation. Our results provide an avenue for understanding electron dynamics and achieving ultrafast optical control of interaction-driven quantum phase transitions in strongly correlated electron systems.

2D materials↗

Compression rate effects on the Bi-III stability field in dynamic diamond anvil cell XFEL studies of bismuth

This study aims to resolve conflicting observations of bismuth’s high-pressure phase transitions across static, intermediate, and shock compression regimes. We probed its high-pressure structural sequence using the dynamic diamond anvil cell with and time-resolved X-ray diffraction with microsecond resolution at an X-ray free-electron laser. At room temperature and pressures up to 20 gigapascals, bismuth evolves through the same structural sequence previously identified under static compression. However, the transformation behavior differs in important ways under dynamic loading. In particular, the transition from the incommensurate intermediate-pressure phase to the high symmetry high pressure phase begins at pressures about 2 to 4 gigapascals lower than in static experiments, and the onset of this transformation depends on the compression rate. As a result, the stability field of the intermediate-pressure phase is reduced under rapid compression. Our results suggest that at sufficiently fast loading rates the intermediate phase may be bypassed entirely, consistent with previous shock-compression observations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Double-null power-sharing dynamics in MAST-U

Maintaining an effective double-null (DN) configuration is expected to be challenging in reactor-scale tokamak devices. As divertor power-sharing is closely linked to the magnetic topology, even minor variations can lead to fast power-sharing fluctuations which exacerbate the already daunting exhaust challenge. While the static aspects of DN power-sharing have been extensively studied across various devices, this paper presents the first detailed investigation of its dynamic behaviour. We employ dedicated H-mode experiments in MAST-U, in Super-X divertor configuration, featuring perturbation frequencies up to 200 Hz. Our results clearly show no significant dynamic damping of the power-sharing within this frequency range: the divertor responds equally to both fast and slow perturbations. Moreover, the dynamic response also aligns with quasi-static results from slow ramps, implying that static power-sharing models remain valid even for fast fluctuations. Occasionally, some deviations from the otherwise mainly linear behaviour are observed, alongside notable scatter and asymmetries between upwards and downwards trajectories. These observations are likely linked to changes in core conditions, though the underlying mechanisms remain unclear and require further study.

divertor↗

Adiabatic expansion cooling of antihydrogen

Magnetically trapped antihydrogen atoms can be cooled by expanding the volume of the trap in which they are confined. We report a proof-of-principle experiment in which antiatoms are deliberately released from expanded and static traps. Antiatoms escape at an average trap depth of 0.08 ± 0.01 K (statistical errors only) from the expanded trap while they escape at average depths of 0.22 ± 0.01 and 0.17 ± 0.01 K from two different static traps. (We employ temperature-equivalent energy units.) Detailed simulations qualitatively agree with the escape times measured in the experiment and show a decrease of 38 % (statistical error < 0.2 % ) in the mean energy of the population after the trap expansion without significantly increasing antiatom loss compared to typical static confinement protocols. This change is bracketed by the predictions of one-dimensional and three-dimensional semianalytic adiabatic expansion models. These experimental, simulational, and model results are consistent with obtaining an adiabatically cooled population of antihydrogen atoms that partially exchanged energy between axial and transverse degrees of freedom during the trap expansion. This result is important for future antihydrogen gravitational experiments which rely on adiabatic cooling, and it will enable antihydrogen cooling beyond the fundamental limits of laser cooling. Published by the American Physical Society 2024

Ahmadi, M.↗

Wilson loops with neural networks

Wilson loops are essential objects in QCD and have been pivotal in scale setting and demonstrating confinement. Various generalizations are crucial for computations needed in effective field theories. In lattice gauge theory, Wilson loop calculations face challenges, including excited-state contamination at short times and the signal-to-noise ratio issue at longer times. To address these problems, we develop a new method by using neural networks to parametrize interpolators for the static quark-antiquark pair. We construct gauge-equivariant layers for the network and train it to find the ground state of the system. The trained network itself is then treated as our new observable for the inference. Our results demonstrate a significant improvement in the signal compared to traditional Wilson loops, performing as well as Coulomb-gauge Wilson-line correlators while maintaining gauge invariance. Additionally, we present an example where the optimized ground state is used to measure the static force directly, as well as another example combining this method with the multilevel algorithm. Finally, we extend the formalism to find excited-state interpolators for static quark-antiquark systems. To our knowledge, this work is the first study of neural networks with a physically motivated loss function for Wilson loops.

Bellscheidt, Verena [Massachusetts Inst. of Techno↗

Deciphering Discrepancies: A Comparative Analysis of Docker Image Security

As the use of microservices continues to grow and become a foundational approach to architecting software solutions, ensuring the security of microservices is paramount. Docker images have emerged as the predominant solution to containerize microservices–and thus, Docker images are becoming a large attack surface. Thus, reducing vulnerabilities in Docker images will reduce microservice cyberattacks. A common way to find vulnerabilities in Docker images employs static analysis tools like Trivy and Grype. However, these tools frequently generate disparate vulnerability reports when analyzing the same Docker image, thus causing uncertainty in tool selection. We collected 927 Docker images, analyzed them with Trivy and Grype, and compared the vulnerabilities reported in each image. Among the 865 images found to have vulnerabilities, Trivy and Grype disagreed on both the number of vulnerabilities and the vulnerability IDs found therein. Since both tools interface with external vulnerability databases, some discrepancies can be attributed to how the tools interface with these external resources. The external vulnerability databases partially overlap and frequently contradict one another, thereby creating challenges for static analysis tool developers and end users alike. This New Ideas and Emerging Results (NIER) study contains new and critical information that practitioners need for selecting and using static analysis tools–given that increases in the use of Docker technologies means increases in the size of the attack surfaces.

Boles, Brittany [Montana State University]↗

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference

In this work, we present two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport (COT) problems. Both approaches enable conditional sampling and conditional density estimation, which are core tasks in Bayesian inference—particularly in the simulation-based (“likelihood-free”) setting. Our methods represent the target conditional distribution as a transformation of a tractable reference distribution. Obtaining such a transformation, chosen here to be an approximation of the COT map, is computationally challenging even in moderate dimensions. To improve scalability, our numerical algorithms use neural networks to parameterize candidate maps and further exploit the structure of the COT problem. Our static approach approximates the map as the gradient of a partially input convex neural network. It uses a novel numerical implementation to increase computational efficiency compared to state-of-the-art alternatives. Our dynamic approach approximates the conditional optimal transport via the flow map of a regularized neural ODE; compared to the static approach, it is slower to train but offers more modeling choices and can lead to faster sampling. We demonstrate both algorithms numerically, comparing them with competing state-of-the-art approaches, using benchmark datasets and simulation-based Bayesian inverse problems.

97 MATHEMATICS AND COMPUTING↗