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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 163 records · Page 9

Detailed Characterization of CZT Detector Response for Improved Coded-Aperture Imaging Performance

Gamma-ray imaging is a powerful method for locating and quantifying sources of radiation. The coded-aperture technique demonstrates superior angular resolution in comparison to other methods (e.g., Compton reconstruction). In this method, a mask constructed of highly attenuating material encodes the scene as a shadow pattern on a position-sensitive detector; this pattern can then be used to recreate the origin(s) of incident radiation. This is typically done through convolution of the mask and shadow patterns. Iterative methods which attempt to reconstruct the observed shadow pattern using a weighted combination of simulated patterns may also be employed. In either case, errors in event position reconstruction due to detector imperfections alter the shadow pattern and will therefore degrade system performance and may introduce imaging artifacts. These effects can be mitigated with a detailed understanding of such errors – allowing for the generation of representative simulations that include the errors and/or correction of raw imager data to remove the errors. We present a calibration process for a commercially available cadmium zinc telluride (CZT) gamma imager which provides a comprehensive characterization of the spatial and energy dependence of event reconstruction. By illuminating a mask featuring a regular grid of pinholes with a calibration source, the localized response of the detector can be measured with fine granularity. These local responses are combined to generate a full detector response map which can be used to distort simulations in a manner that is representative of the observed detector data. Details of the calibration procedure and an assessment of the impact of its end products on the performance of iterative imaging methods will be presented.

Ziock, Klaus-Peter↗

Understanding the Dissolution and Passivation of an Aluminum Electrode during Electrocoagulation of Groundwater Using Neutron and X-ray Reflectometry

An aluminum (Al)-based electrocoagulation (EC) system can effectively remove dissolved silica and hardness in groundwater. The effectiveness of Al-EC in terms of pollutant removal, Faradaic efficiency, and energy consumption depends on the interfacial electrolysis or passivation of the electrode in water. Thus, understanding the electrolysis reaction at the liquid/electrode interface during operation is important for sustainable EC deployment. Here, a continuous flow-through Al-EC system was tested with various groundwater simulants, i.e., chloride (Cl – )-based, sulfate (SO 4 2– )-based, and mixed solutions. High pollutant removal with low energy consumption was observed in Cl – -based groundwater treatment, while low pollutant removal with high energy consumption was observed in SO 4 2– -based groundwater. For example, the required energy per unit mass of Al dosing in SO 4 2– -based groundwater is three times higher than that in Cl – -based groundwater at 10 mA/cm 2 . However, increasing the Cl – concentration significantly reduces this energy demand. In SO 4 2– -based groundwater, the silicate removal efficiency drops from 85.1% to 24.0% compared to that for Cl – -based groundwater, while Mg 2+ and Ca 2+ removal efficiencies decrease to 0.6% from 15.8% and 5.7% from 44.8%, respectively. To better understand this EC performance, we used in situ neutron reflectometry (NR) to examine the interfacial dynamics of Al dissolution and passivation at a 100 nm scale occurring on the surface of the sacrificial Al electrodes during EC. Ex situ X-ray reflectometry (XRR) was also used to support the in situ NR results. Both NR and XRR results revealed that Al dissolution is influenced by the presence of Cl – in the simulants, while a passivating layer forms on the electrode in a SO 4 2– -based solution. In the Cl – -based solution, anodic Al dissolution occurred locally and inhomogeneously across the surface of the Al anode film, resulting in a localized thickness reduction over time. In the SO 4 2– -based solution, no apparent dissolution of the Al anode was identified. Instead, Al underwent oxidation, forming an amorphous Al 2 O 3 surface layer within the Al electrode film that increased in thickness over time. In the mixed solution, both anodic Al dissolution and surface Al 2 O 3 layer formation occurred, indicating that Al dissolution and surface Al 2 O 3 layer formation are attributable to the Cl – and SO 4 2– ions, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intermediate-temperature topological Uhlmann phase on IBM quantum computers

A spin-1 system can exhibit an intermediate-temperature topological regime with a quantized Uhlmann phase sandwiched by topologically trivial low- and high-temperature regimes. We present a quantum circuit consisting of system and ancilla qubits plus a probe qubit which prepares an initial state corresponding to the purified state of a spin-1 system at finite temperature, evolves the system according to the Uhlmann process, and measures the Uhlmann phase via expectation values of the probe qubit. Although classical simulations suggest the quantized Uhlmann phase is observable on International Business Machines (IBM’s) noisy intermediate-scale quantum (NISQ) computers, an implementation of the circuit without any optimization exceeds the gate count for the error budget and results in unresolved signals. Through a series of optimization with Qiskit and BQSKit, the gate count can be substantially reduced, making the jumps of the Uhlmann phase more visible. A recent hardware upgrade of IBM quantum computers further improves the signals and leads to a clearer demonstration of interesting finite-temperature topological phenomena on NISQ hardware.

Mastandrea, Christopher [Univ. of California, Merc↗

Impact of solvent forces and broken symmetry on the assembly of designed proteins at a liquid-solid interface

The era of protein design has enabled the creation of hybrid protein-inorganic interfaces, leading to both surface-directed self-assembly of de novo protein architectures and protein-directed formation of inorganic materials. However, the resulting patterns of protein assembly are often unexpected, implying that essential interactions are not accounted for in current design platforms. Here, we use high-speed atomic force microscopy (AFM) analyzed through machine learning to follow the assembly of protein nanorods in aqueous electrolytes on two types of mica exhibiting disparate symmetry elements, which are imprinted on the overlying hydration structure. Using Monte Carlo simulations, we reproduce the observed phases and show that an observed smectic phase, previously thought to be unstable for non-interacting rods in two dimensions, emerges when crystal symmetry introduces a directional bias. The findings demonstrate the importance of incorporating solvent forces as modulated by the hydration structure inherent to interfacial systems when designing protein assemblies at liquid-crystal interfaces. Coupling physics-based simulations that can account for these factors to de novo protein design algorithms can lead to improved design platforms for bio-inspired, hybrid materials.

bioinspired materials↗

Towards robust laser beam propagation in atmospheric turbulence

High-fidelity optical propagation through the atmosphere is essential for free-space optical technologies, including laser-based remote sensing and optical communication. However, atmospheric turbulence severely distorts beams and compromises system performance. In this work, we employ hypergeometric-Gaussian (HyGG) vortex beams as probes to characterize and mitigate atmospheric turbulence. Using over 250,000 experimental and simulated frames, we show that refining the power spectrum density (PSD) can reduce numerical prediction errors by up to 79.8%. Concurrently, experimental observations supported by numerical simulations demonstrate that HyGG beams exhibit superior turbulence resilience across multiple metrics compared to conventional Gaussian beams, particularly in their ability to withstand over 5 times stronger turbulence while maintaining similar intensity fluctuations. These dual investigations, on both turbulence mitigation and robust beam solutions, converge to form a unified strategy for enhancing free-space optical system performance. Collectively, our findings provide new insights into light–turbulence interactions and highlight the practical utility of vortex beams under atmospheric conditions.

Zhang, Boyu↗

Gamma-Ray Bursts and Kilonovae from the Accretion-induced Collapse of White Dwarfs

Abstract We present the first seconds-long 2D general relativistic neutrino magnetohydrodynamic simulations of accretion-induced collapse (AIC) in rapidly rotating, strongly magnetized white dwarfs (WDs), which might originate as remnants of double-WD mergers. This study examines extreme combinations of magnetic fields and rotation rates, motivated both by the need to address the limitations of 2D axisymmetric simulations and to explore the physics of AIC under rare conditions that, while yet to be observationally confirmed, may be consistent with current theoretical models and account for unusual events. Under these assumptions, our results demonstrate that, if realizable, such systems can generate relativistic jets and neutron-rich outflows with properties consistent with long gamma-ray bursts (LGRBs) accompanied by kilonovae, such as GRB 211211A and GRB 230307A. These findings highlight the potential role of AIC in heavy r -process element production and offer a framework for understanding rare LGRBs associated with kilonova emission. Longer-duration 3D simulations are needed to fully capture magnetic field amplification, resolve instabilities, and determine the fate of the energy retained by the magnetar at the end of the simulations.

Cheong 張, Patrick Chi-Kit 志杰 (ORCID:00000003144933↗

Modelling Beam Loss Within the LANSCE Proton Storage Ring

Several upgrades are being considered for the proton storage ring (PSR) at the Los Alamos Neutron Science Center (LANSCE) to reduce beam loss and thereby reduce the cooldown period of the PSR following a beam run. First, we have considered an increased beam pipe diameter would reduce beam loss due to beam scraping caused by misalignments and tuning errors. However, this would require increased pole-to-pole gap height within the dipoles and quadrupoles, which would change their effective length and alter their fringe fields. The effect of different magnet gaps on the beam optical parameters and on beam loss was studied using the simulation codes MAD-X and PyORBIT. Second, we are developing a detailed particle tracking model within the framework of the simulation package General Particle Tracer (GPT) for the PSR H - stripping system. This model will be used to study the effect of the stripper foil parameters (position, composition, areal density, depth, etc.) on first-turn losses, where most of the observed beam loss and emittance growth occurs due to foil scattering, foil stripping, and Lorentz stripping. The model implements C++ custom elements created to model foil scattering, foil stripping, and Lorentz stripping, as these are not built-in features of GPT. The preliminary results of the MAD-X and PyORBIT simulations, as well as the GPT simulation model, is described in this tech note.

43 PARTICLE ACCELERATORS↗

Rotation‐Controlled Diurnal Evolution of Uranus' Asymmetric Bow Shock at Equinox

Uranus possesses the most extreme magnetic and rotational geometry in the solar system, resulting in a uniquely dynamic and asymmetric interaction between its magnetosphere and the solar wind. Here we investigate the diurnal evolution of the Uranian bow shock (BS) at equinox using global multifluid magnetohydrodynamic simulations constrained by Voyager 2 observations. The BS structure and variability are quantified using the stand‐off distance, terminator distance, flaring parameter, and BS parameter, enabling a systematic assessment of its global asymmetry over one planetary rotation. Our results show that the BS exhibits pronounced diurnal asymmetry that is primarily controlled by planetary rotation. Even under steady upstream solar wind conditions, the BS undergoes periodic expansion and contraction, reflecting rotation‐driven reconfiguration of the planetary magnetospheric topology. This diurnal modulation represents a remarkably large asymmetry in planetary BS geometry within the solar system. These results establish planetary rotation as the intrinsic primary driver of Uranus' BS dynamics at equinox and provide essential constraints for the design and formulation of future space missions to the ice giants. These findings also offer a unique framework for understanding shock physics in the abundant population of ice‐giant exoplanets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations

Abstract Large‐scale discrete fracture network (DFN) simulators are standard fare for studies involving the sub‐surface transport of particles since direct observation of real world underground fracture networks is generally infeasible. While these simulators have successfully been used in several engineering applications, estimates of output quantities of interest (QoI) — such as breakthrough time of particles reaching the edge of the system — suffer from two distinct types of uncertainty. A run of a DFN simulator requires several parameters to be set that dictate the placement and size of fractures, the density of fractures, and the overall permeability of the system; uncertainty on the proper parameters will lead to uncertainty in the QoI, called epistemic uncertainty. Furthermore, since these input settings to DFN simulators control the stochastic processes which place fractures and govern flow, understanding how this randomness affects the QoI requires several runs of the simulator at distinct random seeds. The uncertainty in the QoI attributed to different realizations (i.e., different seeds) of the same random process (i.e., identical input parameters) leads to a second type of uncertainty, called aleatoric uncertainty. In this paper, we perform a Sensitivity Analysis, which directly attributes the uncertainty observed in the QoI to the epistemic uncertainty from each input parameter and to the aleatoric uncertainty. Beyond the specific takeaways on which input variables influence uncertainty in the QoI the most, a major contribution of this paper is the introduction of a statistically rigorous workflow for characterizing the uncertainty in DFN flow simulations that exhibit heteroskedasticity.

58 GEOSCIENCES↗

Bayesian model-data comparison incorporating theoretical uncertainties

Accurate comparisons between theoretical models and experimental data are critical for scientific progress. However, inferred physical model parameters can vary significantly with the chosen physics model, highlighting the importance of properly accounting for theoretical uncertainties. In this Letter, we present a Bayesian framework that explicitly quantifies these uncertainties by statistically modeling theory errors, guided by qualitative knowledge of a theory’s varying reliability across the input domain. We demonstrate the effectiveness of this approach using two systems: a simple ball drop experiment and multi-stage heavy-ion simulations. In both cases incorporating model discrepancy leads to improved parameter estimates, with systematic improvements observed as additional experimental observables are integrated.

Bayesian methods↗

Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER

Global Storm-Resolving Models (GSRMs) are becoming increasingly vital for advancing climate modeling and improving the prediction of extreme weather events. Houston, a coastal region frequently affected by deep convective storms, offers an ideal setting to evaluate the ability of GSRMs to simulate deep convection. This study assesses the performance of the Doubly Periodic Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere Model (DP-SCREAM) using observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. DP-SCREAM effectively reproduces the diurnal cycles of clouds and precipitation, demonstrating much greater skill than the E3SM single column model. The DP-SCREAM is demonstrated to be applicable to coastal regions, partially due to the forcing data sets already capturing the influence of breezes. DP-SCREAM also replicates biases persistent in the global version of SCREAM: the underrepresentation of boundary layer shallow clouds, a lack of mid-level congestus clouds, and the popcorn convection, characterized by small and disorganized convective cells generating the strongest precipitation. To investigate these issues, two sensitivity experiments were conducted: increasing the mixing length and scaling up the buoyancy flux within the Simplified Higher Order Closure scheme. Increasing the mixing length improved mid-level congestus representation and reduced unrealistic early morning fog occurrence. Enhancing buoyancy flux only marginally improved the bias of underproduced big convective cells. In conclusion, an additional resolution sensitivity test at 0.5 km grid spacing demonstrated that a refined horizontal resolution alone is insufficient to resolve these biases.

54 ENVIRONMENTAL SCIENCES↗

Neuromorphic heat transport effects in a molecular junction

Understanding energy transport at the nanoscale is an open and fundamental challenge in the molecular sciences with direct implications for the design of new electronics, computing devices, and materials. While nanoscale energy transport under steady-state conditions has been studied extensively, there is much less known about energy transport under time-dependent driving forces, particularly in the far-from-equilibrium regime. In this work, we use nonequilibrium molecular dynamics simulations and stochastic thermodynamics to investigate energy transport in a well-studied nanoscale system—a molecular junction—subjected to a time-periodic temperature gradient. The primary observation is that molecular junctions can exhibit heat transport hysteresis, a phenomenon in which the heat flux through a system depends not only on the instantaneous value of a time-dependent temperature bias but also on the temporal history of that bias. The presented findings illustrate that molecular junctions can exhibit the specific memory effect—heat transport hysteresis—that is essential for the design of thermal neuromorphic computers. This work elucidates a potential pathway toward the realization of such devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Misalignment Tolerant Magnetic Coupler Design and Implementation for Wireless Charging of Unmanned Aerial Vehicles (UAVs)

Wireless power transfer technology is getting more attention these days as a part of expanded battery charging infrastructure and network at a wide range of power levels. Charging Unmanned aerial vehicles (UAVs) is one wireless charging application, and charging their batteries can be challenging because they have short flight times and are frequently charged. For wireless charging of UAVs, the misalignment performance of the magnetic coupler pads is critical because landing on a charging pad at a perfectly aligned position is difficult and can be time-consuming. Different coil shapes and system structures have been proposed in the literature to overcome this challenge. A new design with a high misalignment tolerance is needed; therefore, to fill this gap, a wireless power transfer system has been designed for a 250 W UAV battery charging system with a new magnetic coupler design. A 3D model of the proposed design was created, and finite element simulations were performed. To prove the proposed design, the magnetic coupler prototypes were developed, and experimental results are presented herein. The misalignment tolerance of the proposed system was observed for various rotational positions of the secondary coil, from 0° to 360°. The results demonstrate that DC–DC efficiency varies between 80% and 85% within full 360° rotation of the receiver coil. This result enables the proposed system to address the misalignment problem for wireless charging of UAVs.

UAVs↗

Exploring Causes of Beam Loss at CEBAF

At Jefferson Lab, the Continuous Electron Beam Accelerator (CEBAF) features a unique design with two linear accelerators and two arc sections allowing for multiple turns of the electron beam, as well as four experimental end stations. This topology leads to increased beam losses, especially in the spreader and recombiner regions connecting the arcs to the linacs and in the extraction regions connecting the experimental end stations to the accelerator. These losses result in equipment activation and operational interruptions. Recent upgrades to the facility’s diagnostic systems, including the addition of xenon ion chambers, have provided higher-resolution data regarding these loss events. Building on this improved observational capability, we are developing a simulation framework using optics codes and the Geant4-based BDSIM to model beam extinction and halo formation in these regions. This work aims to correlate simulation results with experimental data to isolate the causes of beam loss and inform future machine tuning strategies. We present a summary of conclusions drawn from recent operational studies and outline a plan to model the beam loss and validate the simulations.

Matthews, C. [Old Dominion Univ., Norfolk, VA (Uni↗

The Impacts of Rotational Mixing on the Precipitation Simulated by a Convection Permitting Model

With increased availability of computational resources, regional and global scale convection-permitting model (CPM, Δx ~ 1–10 km) simulations are becoming more common. CPMs have improved accuracy in their representation of deep convection and mesoscale convective systems (MCSs) compared to coarser resolution models. However, CPMs still exhibit convective cloud and precipitation biases relative to observations, notably a lesser frequency of light precipitation rates and greater frequency of heavy precipitation rates. In this work we hypothesize that these CPM biases are related to under-resolved mixing between convective updrafts and their surrounding environment. To test this hypothesis, we introduce a parameterization to the Weather Research and Forecasting model (WRF) that adds a small angular rotation of the grid-scale flow about the axis perpendicular to the plane of convective drafts. This rotated flow is then allowed to alter advection of moisture and hydrometeors. The effects of such mixing on precipitation characteristics are evaluated in month-long 4-km grid spacing simulations over the Amazon. The enhanced mixing transports moisture and condensate from convective cores to other areas including downdrafts. This increases the frequency of low-precipitable water and light precipitation. It also decreases the frequency of intense precipitation from isolated deep convection and MCSs, increases cloud top temperatures, reduces radar echo-top heights, and increases overall precipitation by altering the relationship of precipitation with precipitable water, in better agreement with observations. The results suggest when optimized using multiple observations, such an approach may provide a path toward more accurate representation of convection and precipitation statistics in convection-permitting simulations.

54 ENVIRONMENTAL SCIENCES↗

How Well Does the DOE Global Storm Resolving Model Simulate Clouds and Precipitation Over the Amazon?

This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.

54 ENVIRONMENTAL SCIENCES↗

Pattern formation in odd viscoelastic fluids

Nonreciprocal interactions fueled by local energy consumption can be found in biological and synthetic active matter at scales where viscoelastic forces are important. Such systems can be described by “odd” viscoelasticity, which assumes fewer material symmetries than traditional theories. Here we study odd viscoelasticity analytically and using lattice Boltzmann simulations. We identify a pattern-forming instability which produces an oscillating array of fluid vortices, and we elucidate which features govern the growth rate, wavelength, and saturation of the vortices. Our observation of pattern formation through odd mechanical response can inform models of biological patterning and guide engineering of odd dynamics in soft active matter systems. Published by the American Physical Society 2024

Floyd, Carlos (ORCID:0000000262707250)↗

Comparing XRISM Cluster Velocity Dispersions with Predictions from Cosmological Simulations: Are Feedback Models Too Ejective?

The dynamics of the intracluster medium (ICM), the hot plasma that fills galaxy clusters, are shaped by gravity-driven cluster mergers and feedback from supermassive black holes (SMBHs) in the cluster cores. XRISM measurements of ICM velocities in several clusters offer insights into these processes. We compare XRISM measurements for nine galaxy clusters (Virgo, Perseus, Centaurus, Hydra-A, PKS 0745–19, A2029, Coma, A2319, and Ophiuchus) with predictions from three state-of-the-art cosmological simulation suites, TNG-Cluster, the Three Hundred Project GADGET-X, and GIZMO-SIMBA, that employ different models of feedback. In cool cores, XRISM reveals systematically lower velocity dispersions than the simulations predict, with all 10 measurements below the median simulated values by a factor of 1.5–1.7 on average and all falling within the bottom 10% of the predicted distributions. The observed kinetic-to-total pressure ratio is also lower, with a median value of 2.2%, compared to the predicted 5.0%–6.5% for the three simulations. Outside the cool cores and in non-cool-core (NCC) clusters, simulations show better agreement with XRISM measurements, except for the outskirts of the relaxed, cool-core cluster A2029, which exhibits an exceptionally low kinetic pressure support (<1%), with none of the simulated systems in either of the three suites reaching such low levels. The NCC Coma and A2319 exhibit dispersions at the lower end but within the simulated spread. Our comparison suggests that the three numerical models may overestimate the kinetic effects of SMBH feedback in cluster cores. Additional XRISM observations of NCC clusters will clarify if there is a systematic tension in the gravity-dominated regime as well.

galaxy clusters↗