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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 199 records · Page 11

Potentials of mean force fail to describe chemical bond-breaking in solution

Many liquid phase studies assume that the potential energy surfaces of reacting molecules are the same as in the gas phase, neglecting complex solvent dynamics that can completely alter the nature of chemical reactivity. Even studies that include solvent effects typically only consider them in an average, equilibrium way as part of a potential of mean force (PMF). In this work, we use mixed quantum/classical simulations to compare how equilibrium and non-equilibrium solvent motions affect the photodissociation of a simple diatomic molecule, NaK + , in liquid tetrahydrofuran. A PMF analysis shows that as the excited-state molecule dissociates with the solvent at equilibrium, the bonding electron remains associated with K + at short bond distances but eventually localizes on Na + at the end of dissociation. When we examine non-equilibrium dynamical photodissociation trajectories, however, we find that they fall into three distinct categories: about a quarter of them have the bonding electron mainly associated with Na + , another quarter stay mainly associated with K + , and about half have the bonding electron shared roughly equally between the two ions. The results show that equilibrium PMFs cannot accurately describe the dynamics of bond-breaking chemical reactions in solution because there is insufficient time for the solvent to reach equilibrium on the time scale over which bond dissociation occurs. Furthermore, our analysis shows that the solvent coupling between the electronic energy surfaces is similar at and away from equilibrium, suggesting that other factors, such as solute velocity-driven solvent memory effects, play a more important role in explaining the failure of the equilibrium PMF to predict the non-equilibrium dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnus force induced magnetic diode effect in skyrmion systems

We show that skyrmions can exhibit a “magnetic diode effect,” where there is a nonreciprocal response in the transport when the magnetic field is reversed. This effect can be achieved for skyrmions moving in channels with a sawtooth potential on one side and a reversed sawtooth potential on the other side. We consider the cases of both spin-transfer torque (STT) and spin–orbit torque (SOT). When the magnetic field is held fixed, the velocity response of the skyrmion is the same for current applied in either direction for both torques, so there is no current diode effect. When the magnetic field is reversed, under STT driving the velocity of the skyrmion reverses and its absolute value changes. Under SOT driving, the velocity remains in the same direction but drops to a much lower value, resulting in negative differential conductivity. For a fixed current, we find a nonreciprocal skyrmion velocity as a function of the applied field’s sign, in analogy to the velocity–current curves observed in the usual diode effect. The nonreciprocity is generated by the Magnus force, which causes skyrmions to interact preferentially with one side of the channel. Since the channel sides have opposite asymmetry, a positive magnetic field can cause the skyrmion to interact with the “hard” asymmetry side of the channel, while a negative magnetic field causes the skyrmion to interact with the “easy” asymmetry side. This geometry could be used to create new kinds of magnetic-field-induced diode effects that can be harnessed in new types of skyrmion-based devices.

36 MATERIALS SCIENCE↗

Magnetic force microscopy revealing long-range room temperature stable molecule bridge-induced magnetic ordering on magnetic tunnel junction (MTJ) pillars

Magnetic tunnel junctions (MTJs) can integrate novel single molecular device elements to overcome long-standing fabrication challenges, thus unlocking their novel potential. This study employs magnetic force microscopy (MFM) to demonstrate that organometallic molecules, when placed between two ferromagnetic electrodes along cross-junction shaped MTJ edges, dramatically altered the magnetic properties of the electrodes, affecting areas several hundred microns in size around the molecular junction vicinity at room temperature. These findings are supported by magnetic resonance and magnetometer studies on ∼7000 MTJ pillars. MFM on the pillar sample showed an almost complete disappearance of the magnetic contrast. The spatial magnetic image suggests that molecular channels significantly impacted the spin density of states in the ferromagnetic electrodes. This advancement in MTJ-based molecular devices paves the way for a new generation of commercially viable logic and memory devices controlled by molecular quantum states at near-room temperatures.

Tyagi, Pawan (ORCID:0000000275411344)↗

Code Validation of SAM Using Forced and Natural Circulation Data from NACIE-UP Benchmark

Heavy liquid metals (HLMs) are promising candidates as coolants of Generation IV fast reactors due to their thermophysical properties. In the last decade, experimental work has been proposed as part of research and development efforts to develop such systems. In this context, researchers from the Brasimone Research Center have conducted many experiments using the Natural Circulation Experiment Upgrade (NACIE-UP) facility to study the thermofluid dynamic behavior of HLMs in rod bundle configurations with or without wire wrappers. This facility consists of a rectangular loop operated with lead-bismuth eutectic. Sensors across the loop monitor relevant parameters, i.e. temperatures, heat transfer, and flow conditions. Here, in the present work, we carefully select published data from NACIE-UP to validate the System Analysis Module (SAM), a modern system analysis code developed at Argonne National Laboratory. We developed one SAM model using specifications of the facility geometry and materials existing in relevant papers and reports. On top of that, these references provided the boundary conditions for simulating natural circulation and forced convection experiments in either steady or transient conditions. The SAM model simulates five test cases with diverse operating conditions. Ultimately, the code is proven to predict temperatures and mass flow rates that closely match the experiments. The discrepancies between numerical predictions and diverse transients are limited to a few degrees Celsius, showcasing that SAM is well suited for analyzing nuclear systems relying on HLM coolants.

advanced reactors↗

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt-cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. Here, to address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor's size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. In conclusion, the Reger direct numerical simulation-driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Mixed Convection↗

Multiphysics Analyses of the Protected and Unprotected Loss of Forced Cooling Accidents in the HTR-PM

Here, we present the multiphysics simulation results for the protected pressurized and depressurized loss of forced cooling (PLOFC and DLOFC) events in the High-Temperature gas-cooled Reactor--Pebble-bed Module (HTR-PM) equilibrium core using the Griffin-Pronghorn coupled code system. Additionally, this paper discusses the strategy for estimating the spontaneous fission neutron source needed for unprotected events and re-criticality calculations. The solutions of the protected PLOFC and DLOFC events were verified against similar solutions obtained for temperature evolutions from the open literature. Both the average and maximum pebble surface temperatures behaved as expected during the DLOFC and remained below 1800 K. The PLOFC results are highly dependent on the ability to resolve the natural circulation in the core, which is impacted by the mesh resolution in Pronghorn. Furthermore, we present the results of the unprotected DLOFC transient to predict the timing of the re-criticality event, which occurred 47 hours after the onset of the transient, and the new steady-state power of 1.3 MW.

42 - ENGINEERING↗

Unsupervised atomic data mining via multi-kernel graph autoencoders for machine learning force fields

Constructing a chemically diverse dataset while avoiding sampling bias is critical to training efficient and generalizable force fields. However, in computational chemistry and materials science, many common dataset generation techniques are prone to oversampling regions of the potential energy surface. Furthermore, these regions can be difficult to identify and isolate from each other or may not align well with human intuition, making it challenging to systematically remove bias in the dataset. While traditional clustering and pruning (down-sampling) approaches can be useful for this, they can often lead to information loss or a failure to properly identify distinct regions of the potential energy surface due to difficulties associated with the high dimensionality of atomic descriptors. In this work, we introduce the Multi-kernel Edge Attention-based Graph Autoencoder (MEAGraph) model, an unsupervised approach for analyzing atomic datasets. MEAGraph combines multiple linear kernel transformations with attention-based message passing to capture geometric sensitivity and enable effective dataset pruning without relying on labels or extensive training. Demonstrated applications on niobium, tantalum, and iron datasets show that MEAGraph efficiently groups similar atomic environments, allowing for the use of basic pruning techniques for removing sampling bias. This approach provides an effective method for representation learning and clustering that can be used for data analysis, outlier detection, and dataset optimization.

Materials science↗

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES↗

Quantifying the impact of the Si/O interface in CCSN explosions using the Force Explosion Condition

ABSTRACT The explosion mechanism of a core-collapse supernova (SN) is a complex interplay between neutrino heating and cooling (including the effects of neutrino-driven convection), the gravitational potential, and the ram pressure of the infalling material. To analyse the post-bounce phase of an SN, one can use the generalized force explosion condition (FEC+), which succinctly formalizes the interplay among these four phenomena in an analytical condition, consistent with realistic simulations. In this paper, we use the FEC+ to study the post-bounce phase of 341 spherically symmetric simulations, where convection is included through a time-dependent mixing-length approach. We find that the accretion of the Si/O interface through the expanding shock can significantly change the outcome of the SN by driving the FEC+ above the explosion threshold. We systematically explore this by (i) artificially smoothing the pre-SN density profile, and (ii) artificially varying the mixing length. In both cases, we find that large-enough density contrasts at the Si/O interface lead to successful shock revival only if the FEC+ is already close to the explosion threshold. Furthermore, we find that the accretion of the Si/O interface has a substantial effect on the critical condition for SN explosions, contributing between 5 and 15 per cent, depending on how pronounced the density contrast at the interface is. Earlier studies showed that convection affects the critical condition by 25–30 per cent, which demonstrates that the accretion of the Si/O interface through the shock can play a nearly comparable role in influencing shock dynamics.

Boccioli, Luca (ORCID:000000024819310X)↗

Prediction of a measurable sign change in the Casimir force using a magnetic fluid

Here, we demonstrate quantum levitation controlled by Casimir forces acting between a polystyrene surface and a Teflon-coated metallic substrate immersed in a mixture of toluene and magnetite particles. This system experiences repulsion-attraction transitions in the Casimir interaction for distances where the effect is measurable. This Casimir trapping can be controlled by clever choices of metallic and ferrofluid materials, which are directly linked to the emergence of the trapping effect. Thermal and quantum contributions are investigated in detail, showing how the optical and magnetic properties of the ferrofluid and other materials affect the magnitude of the trapping and its distance range of observability.

Ma, Long [University of South Florida, Tampa, FL (↗

Mechanical sensors for ultraheavy dark matter searches via long-range forces

Dark matter candidates with masses around the Planck scale are theoretically well-motivated, and it has been suggested that it might be possible to search for dark matter solely via gravitational interactions in this mass range. In this work, we explore the pathway towards searching for dark matter candidates with masses around the Planck scale using mechanical sensors while considering realistic experimental constraints, and develop analysis techniques needed to conduct such searches. These dark matter particles are expected to leave tracks as their signature in mechanical sensor arrays, and we show that we can effectively search for such tracks using statistical approaches to track-finding. We analyze a range of possible experimental setups and compute sensitivity projections for searches for ultraheavy dark matter coupling to the Standard Model via long-range forces. We find that while a search for Planck-scale dark matter purely via gravitational couplings would be exceedingly difficult, requiring ∼80 dB of quantum noise reduction with a 100 3 array of devices, there is a wide range of currently unexplored dark matter candidates which can be searched for with already existing or near-term experimental platforms.

Qin, Juehang [Rice Univ., Houston, TX (United Stat↗

Machine learning force field model for kinetic Monte Carlo simulations of itinerant Ising magnets

Here, we present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update requires solving an electronic structure problem. Such repeated electronic structure calculations could be overwhelmingly prohibitive for large systems. Assuming the locality principle, a convolutional neural network (CNN) model is developed to directly predict the effective local field and the corresponding energy change associated with a given spin update based on Ising configuration in a finite neighborhood. As the kernel size of the CNN is fixed at a constant, the model can be directly scalable to kMC simulations of large lattices. Our approach is reminiscent of the ML force field models widely used in first-principles molecular dynamics simulations. Applying our ML framework to a square-lattice double-exchange Ising model, we uncover unusual coarsening of ferromagnetic domains at low temperatures. Our work highlights the potential of ML methods for large-scale modeling of similar itinerant systems with discrete dynamical variables.

machine learning↗

Probing New Hadronic Forces with Heavy Exotic Atoms

We explore the potential of precision spectroscopy of heavy exotic atoms where electrons are substituted by negative hadrons to detect new force carriers with hadronic couplings. The selected transitions are unaffected by nuclear contact terms, thus enabling highly accurate calculations using bound-state QED, provided that the nuclear polarization is under control. Alternatively, we demonstrate that the dipole polarizability, a fundamental property of nuclei, can be extracted from the spectroscopy of exotic atoms in a novel way by combining two transitions while maintaining high sensitivity to new physics. Based on existing data, we extracted world-leading bounds on mediator masses ranging from 0.1 to 10 MeV for two benchmark models and show that forthcoming experiments could enhance the sensitivity to new physics by 2 orders of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New μ forces from ν μ sources

Accelerator-based experiments reliant on charged pion and kaon decays to produce muon-neutrino beams also deliver an associated powerful flux of muons. Therefore, these experiments can additionally be sensitive to light new particles that preferentially couple to muons and decay to visible final states on macroscopic length scales. Such particles are produced through rare 3-body meson decays in the decay pipe or via muon scattering in the beam dump, and decay in a downstream detector. To demonstrate the potential of this search strategy, we recast existing MiniBooNE and MicroBooNE studies of neutral pion production in neutrino-induced neutral-current scattering ( ν μ N → ν μ N π 0 , π 0 → γ γ ) to place limits on light ( < 2 m μ ) muon-philic scalar particles that decay to diphotons through loops of virtual muons. While much of this parameter space has already been excluded by E137, we also project that SBND can be sensitive to unexplored parameter space for these models, and provide a road map for future neutrino experiments to perform dedicated searches for muon-philic forces. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Forced 3D Reconnection in an Exponentially Separating Magnetic Field

We present a solvable scenario for 3D reconnection in a sheared magnetic field. We consider a localized external force that is applied slowly to a flux tube and then maintained, generating an Alfvénic perturbation that spreads along the field lines. Separation of the sheared field lines reduces the scale of the perturbation across the field, enhancing magnetic diffusion. For a fusion-motivated equilibrium with exponential field-line separation, we find a reconnection timescale proportional to 𝒮/ ln⁡ 𝒮 under magnetohydrodynamics (MHD) and to 𝒮 1/3 for semicollisional electron-only reconnection, where 𝒮 is the Lundquist number of the perturbed flux tube. We generalize these results to arbitrary magnetic geometries, showing that the semicollisional case is geometry independent. Interestingly, we find that slower field-line separation yields an increased reconnection rate in MHD.

Magnetic confinement fusion↗

Test of the Gravitational Force Law on Cosmological Scales Using the Kinematic Sunyaev-Zeldovich Effect

The mean pairwise velocity of massive halos reflects the gravitational force law on cosmic scales. For this work, we combine cosmic microwave background intensity maps from the Atacama Cosmology Telescope and a galaxy catalog from the Sloan Digital Sky Survey to estimate the mean pairwise velocity using the kinematic Sunyaev-Zeldovich (kSZ) effect. On scales from 30 to 230 megaparsecs, we constrain the gravitational acceleration between pairs of halos at separation 𝑟 to be 𝑔 ∝ 1/𝑟 𝑛 with 𝑛 = 2.1 ± 0.3, which is consistent with Newtonian gravity in an expanding spacetime (i.e., the standard Λ⁢ CDM model). This constraint shows agreement with an inverse quadratic radial dependence over the large distances separating galaxy halos, as expected in standard cosmology. Upcoming surveys have the potential to rule out 𝑛 = 1 at 10⁢𝜎 significance. Our results establish the kSZ effect as a powerful tool for testing gravity on cosmological scales.

alternative gravity theories↗

Climate Forcing of Bioenergy Feedstocks: Insights From Carbon and Energy Flux Measurements

Bioenergy from biofuels has the potential to slow growing atmospheric carbon dioxide concentrations by reducing fossil fuel use. However, growing bioenergy feedstocks is a land-intensive process. In the United States, the recent expansion of maize bioethanol has presented some environmental costs, prompting the development of several alternative bioenergy feedstocks. These feedstocks, selected in part for traits associated with ecosystem services, may provide opportunities for environmental benefits beyond fossil fuel displacement. We hypothesized that these bioenergy ecosystems will provide direct climatic cooling through their influence on carbon and radiative energy fluxes (i.e., through albedo). To test this hypothesis, we investigated the potential cooling effect of five current or potential bioenergy feedstocks using multi-year records from eddy covariance towers. Perennial feedstocks were carbon sinks, with an annual mean net ecosystem carbon balance (NECB) of –2.7 ± 2.1 Mg C ha –1 for miscanthus, –0.8 ± 1.1 Mg C ha –1 for switchgrass, and –1.4 ± 0.7 Mg C ha –1 for prairie. In contrast, annual rotations were generally carbon sources, with an annual mean NECB of 2.6 ± 2.4 Mg C ha –1 for maize-soy and 3.2 ± 2.1 Mg C ha –1 for sorghum-soy. Using maize-soy as a baseline, conversion to alternative feedstocks increased albedo, inducing further cooling. This effect was strongest for miscanthus, with –3.5 ± 2.0 W m –2 of radiative forcing, and weakest for sorghum, with –1.4 ± 1.4 W m –2 . When feedstock effects on carbon and albedo were compared using carbon equivalents, carbon fluxes were the stronger ecosystem effect, underscoring the role of perennial species as effective carbon sinks. This work highlights the impact of feedstock choice on ecosystem processes as an element of bioenergy land conversion strategies.

09 BIOMASS FUELS↗

Mechanical forces orchestrate the metabolism of the developing oilseed rape embryo

The initial free expansion of the embryo within a seed is at some point inhibited by its contact with the testa, resulting in its formation of folds and borders. Although less obvious, mechanical forces appear to trigger and accelerate seed maturation. However, the mechanistic basis for this effect remains unclear. Manipulation of the mechanical constraints affecting either the in vivo or in vitro growth of oilseed rape embryos was combined with analytical approaches, including magnetic resonance imaging and computer graphic reconstruction, immunolabelling, flow cytometry, transcriptomic, proteomic, lipidomic and metabolomic profiling. Our data implied that, in vivo, the imposition of mechanical restraints impeded the expansion of testa and endosperm, resulting in the embryo's deformation. An acceleration in embryonic development was implied by the cessation of cell proliferation and the stimulation of lipid and protein storage, characteristic of embryo maturation. The underlying molecular signature included elements of cell cycle control, reactive oxygen species metabolism and transcriptional reprogramming, along with allosteric control of glycolytic flux. Constricting the space allowed for the expansion of in vitro grown embryos induced a similar response. The conclusion is that the imposition of mechanical constraints over the growth of the developing oilseed rape embryo provides an important trigger for its maturation.

59 BASIC BIOLOGICAL SCIENCES↗