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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 271 records · Page 15

“Quantum Geometric Nesting” and Solvable Model Flat-Band Systems

We introduce the concept of “quantum geometric nesting” (QGN) to characterize the idealized ordering tendencies of certain flat-band systems implicit in the geometric structure of the flat-band subspace. Perfect QGN implies the existence of an infinite class of local interactions that can be explicitly constructed and give rise to solvable ground states with various forms of possible fermion bilinear order, including flavor ferromagnetism, density waves, and superconductivity. For the ideal Hamiltonians constructed in this way, we show that certain aspects of the low-energy spectrum can also be exactly computed including, in the superconducting case, the phase stiffness. Examples of perfect QGN include flat bands with certain symmetries (e.g., chiral or time reversal) and non-symmetry-related cases exemplified with an engineered model for pair-density wave. Extending this approach, we obtain exact superconducting ground states with nontrivial pairing symmetry. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A model for the fragmentation kinetics of crumpled thin sheets

As a confined thin sheet crumples, it spontaneously segments into flat facets delimited by a network of ridges. Despite the apparent disorder of this process, statistical properties of crumpled sheets exhibit striking reproducibility. Experiments have shown that the total crease length accrues logarithmically when repeatedly compacting and unfolding a sheet of paper. Here, we offer insight to this unexpected result by exploring the correspondence between crumpling and fragmentation processes. We identify a physical model for the evolution of facet area and ridge length distributions of crumpled sheets, and propose a mechanism for re-fragmentation driven by geometric frustration. This mechanism establishes a feedback loop in which the facet size distribution informs the subsequent rate of fragmentation under repeated confinement, thereby producing a new size distribution. We then demonstrate the capacity of this model to reproduce the characteristic logarithmic scaling of total crease length, thereby supplying a missing physical basis for the observed phenomenon.

42 ENGINEERING↗

Revealing extreme twin-boundary shear deformability in metallic nanocrystals

Metals containing abundant coherent twin boundaries (TBs) are able to sustain substantial plastic deformation without fracture due to shear-induced TB migration and sliding. Retaining ductility in these metals, however, has proven difficult because detwinning rapidly exhausts TB migration mechanisms at large deformation, whereas TB sliding was only evidenced for loading on very specific crystallographic orientations. Here, we reveal the intrinsic shear deformability of twins in nanocrystals using in situ nanomechanical testing and multiscale simulations and report extreme shear deformability through TB sliding up to 364%. Sliding-induced plasticity is manifested for orientations that are generally predicted to favor detwinning and shown to depend critically on geometric inhomogeneities. Normal and shear coupling are further examined to delineate a TB orientation-dependent transition from TB sliding to TB cracking. These dynamic observations reveal unprecedented mechanical properties in nanocrystals, which hold implications for improving metal processing by severe plastic deformation.

36 MATERIALS SCIENCE↗

Modeling Adsorption in Silica Pores via Minkowski Functionals and Molecular Electrostatic Moments

Capillary condensation phenomena are important in various technological and environmental processes. Using molecular simulations, we study the confined phase behavior of fluids relevant to carbon sequestration and shale gas production. As a first step toward translating information from the molecular to the pore scale, we express the thermodynamic potential and excess adsorption of methane, nitrogen, carbon dioxide, and water in terms of the pore’s geometric properties via Minkowski functionals. This mathematical reconstruction agrees very well with molecular simulations data. Our results show that the fluid molecular electrostatic moments are positively correlated with the number of adsorption layers in the pore. Moreover, stronger electrostatic moments lead to adsorption at lower pressures. These findings can be applied to improve pore-scale thermodynamic and transport models.

42 ENGINEERING↗

Spray coating for washout tooling by binder jet additive manufacturing

We report washout tooling is a process in which a removable mold or fixture is disintegrated using a solvent. Binder Jet (BJ) additive manufacturing holds promise for creating customized washout molds from common materials. BJ-based washout tooling provides an advanced strategy in manufacturing fiber-reinforced composites (FRCs), especially for customized hollow FRCs. However, washout tools formed by BJ require an impermeable barrier between the porous tooling surface and the parts laid up on the surface to prevent the resin from infiltrating the tooling surface and bonding the tool to the FRC. The conventional method for preventing resin migration into the washout mold from the FRC is winding Teflon® tape over the entire surface, which is labor-intensive and very difficult to deploy for specific geometries. Here, we report the development of a polymer spray coating method to seal the tooling surface and prevent resin infiltration without affecting the washout properties needed for sacrificial tooling. Two water-soluble polymers, poly(sodium 4-styrenesulfonate) (PSS–Na) and poly(vinylsulfonic acid, sodium salt) (PVS–Na), were investigated for spray coating. PVS-Na maintained tighter geometric tolerances and provided excellent thermal stability with the onset of decomposition at 320 °C and glass transition temperature of 280 °C. Spray coating with PVS-Na streamlines the process of forming a protective layer for the washout molds by BJ, reduces migration of the resins from the FRC, and significantly improves the production efficiency of complex washout tools.

42 ENGINEERING↗

Modeling glass degradation and release of radionuclides from vitrified waste for performance assessment simulations

The release of radionuclides initially encapsulated in a slowly degrading solid waste form and contained in an eventually corroding canister defines the source term for numerical simulations for the assessment of a geologic repository for high-level radioactive waste. While the details of waste degradation, canister corrosion, and dissolution and mobilization of the radionuclides in pore water include complex chemical reaction and transport processes that are coupled to the thermal, hydrological, microbiological, and mechanical conditions in the repository, the source-term model suitable for use in a numerical performance assessment model should be a defensible abstraction of these mechanisms. We developed a radiological source-term model and implemented it into a non-isothermal flow and transport simulator. While the proposed source-term model is applicable to various waste forms, canister systems, and disposal concepts, we specifically considered radionuclide releases from vitrified high-level waste placed in a cylindrical canister disposed in a deep vertical borehole repository. In this model, waste degradation is a function of temperature, and it can be adjusted to evaluate the influence of and propagate uncertainties in pH, passivation reactions, and chemical conditions as well as geometrical factors. The time-dependent, congruent release of safety-relevant radionuclides present in the decaying inventory is then calculated. Finally, the radionuclides are mobilized by diffusive and advective transport according to the thermo-hydraulic conditions prevailing in the near field of the repository, from where they migrate through the geosphere to the accessible environment. We examine the influence of the source-term model’s parameters on performance assessment calculations through sensitivity and uncertainty propagation analyses, identifying influential factors and confirming the upper bound of their impact. These considerations align with the overarching goal of repository design, which is to demonstrate that engineered and natural barriers can collectively delay radionuclide migration for timescales far exceeding human planning, thereby providing multiple, redundant barriers against environmental contamination.

iTOUGH2↗

MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS

This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗

Concurrent characterization of GaN MOSHEMT gate leakage via electrical and thermoreflectance measurements

In this work, we report the first concurrent use of electrical and thermal characterization, via thermoreflectance, to analyze Time Dependent Dielectric Breakdown in GaN MOSHEMTs. Electrically stressing the devices until a failure occurs, then evaluating them via thermoreflectance, revealed a geometric dependence of the failure mode. Further, all soft breakdowns occurred at the mesa edge where the electric field strength was at its strongest, and tunneling current density was at its highest. This breakdown phenomenon at the mesa edge has been seen previously in GaN HEMTs employing a mesa architecture. Possible approaches to mitigate these failures in MOSHEMTs are proposed.

42 ENGINEERING↗

Automated Design-for-Reliability of a Power Electronics Module

The design of a power electronics module is a multiphysics problem and involves electrical, thermal, and reliability targets and constraints. Although the electrical and thermal design consider multiple aspects such as materials, geometry, and energy losses, reliability design is often limited to the selection of the attachment materials and electrical interconnect types. In this paper, we incorporate reliability metrics in the design phase by investigating the impact of package geometry on the thermomechanical behavior of the die-attachment material. To this end, we conducted thermal and power cycling simulations of a commercial six-pack power module with silicon carbide devices to compute junction temperature and strain energy density per cycle, respectively. We performed multiple simulations with different geometric dimensions and established a correlation between input features and output variables using subspace-based dimension reduction. The machine learning-based dimension reduction method serves as a surrogate model, which can be employed to identify the optimal module design from a thermal and reliability standpoint.

design-for-reliability↗

A Novel Deployable Telescope Baffle Using the Kresling Origami Fold

This report introduces a novel deployable origami baffle designed for telescopes and optical systems, which reduces stray light while maintaining high compactness ratios and low weight. This design leverages the planar nature of the end caps on a cylindrical Kresling origami fold to incorporate mounting points, deployable options, and baffle vanes. The adaptable nature of origami (number of faces, origami geometrical ratios, scaling, etc.) allows the design to easily conform to system requirements, including field of view, deployed length, stowed/deployed stability points, and available volume. Geometric ratios that exhibit bistability in both the stowed and deployed states are discussed in detail, as this results in a rigid structure that maintains its desired configuration. Several designs were conceptualized, and multiple small-scale prototypes were constructed. Potential applications include camera lens hoods, lightweight astronomy telescopes, and deployable baffles for space telescopes and optical systems.

42 ENGINEERING↗

Reactor physics characterization of triply periodic minimal surface-based nuclear fuel lattices

Triply periodic minimal surface (TPMS) lattices are receiving substantial attention in numerous engineering fields due to their impressive topology-driven physical characteristics. TPMS lattices are periodic structures of two distinct intertwined volume domains separated by an area-minimizing surface or wall. TPMS lattices have been observed in nature, such as biological membranes, skeletons, block copolymers, sea urchins, butterfly wings, and equipotential surfaces in crystals. Intriguingly, the topology of TPMS lattices can be easily parametrized via level-set equations and thus are heavily numerically and experimentally studied. Here, a significant research effort is currently applying TPMS lattices for heat exchangers and sinks. This paper extends TPMS lattice applications to nuclear reactor fuel designs, with a focus on identifying relevant TPMS geometric parameters controlling neutronics characteristics, such as reactivity, neutron spectrum, and heat removal properties. We found that fuel surface-area-to-volume ratios for TPMS lattices can be two orders of magnitude larger than current cylindrical fuel rods. Further, the selected TPMS lattice and its implicit equation, the unit cell pitch, wall thickness, and structure porosity are design parameters enabling neutronics optimization for both thermal and fast spectrum configurations, paving the way for exceptionally compact and dense nuclear core concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Oxygen-Vacancy Abundant Nanoporous Ni/NiMnO 3 /MnO 2 @NiMn Electrodes with Ultrahigh Capacitance and Energy Density for Supercapacitors

High-performance energy storage devices (HPEDs) play a critical role in the realization of clean energy and thus enable the overarching pursuit of nonpolluting, green technologies. Supercapacitors are one class of such lucrative HPEDs; however, a serious limiting factor of supercapacitor technology is its sub-par energy density. Here, this report presents hitherto unchartered pathway of physical deformation, chemical dealloying, and microstructure engineering to produce ultrahigh-capacitance, energy-dense NiMn alloy electrodes. The activated electrode delivered an ultrahigh specific-capacitance of 2700 F/cm 3 at 0.5 A/cm 3 . The symmetric device showcased an excellent energy density of 96.94 Wh/L and a remarkable cycle life of 95% retention after 10,000 cycles. Transmission electron microscopy and atom probe tomography studies revealed the evolution of a unique hierarchical microstructure comprising fine Ni/NiMnO 3 nanoligaments within MnO 2 -rich nanoflakes. Theoretical analysis using density functional theory showed semimetallic nature of the nanoscaled oxygen-vacancy-rich NiMnO 3 structure, highlighting enhanced carrier concentration and electronic conductivity of the active region. Furthermore, the geometrical model of NiMnO 3 crystals revealed relatively large voids, likely providing channels for the ion intercalation/de-intercalation. The current processing approach is highly adaptable and can be applied to a wide range of material systems for designing highly efficient electrodes for energy-storage devices.

25 ENERGY STORAGE↗

Conditional Generative Adversarial Networks for Solving Heat Transfer Problems

Generative Adversarial Networks (GANs) have been used as a deep learning approach to solving physics and engineering problems. Using deep learning for these problems is attractive in that reasonably accurate models can be inferred from only raw data, eliminating the need to define the exact physical equations governing a problem. We expand on previous work using GANs to generate steady-state solutions to the two-dimensional heat equation. Using a basic conditional GAN (cGAN), we generate accurate solutions for rectangular domains conditioned on four edge boundary conditions (MAE < 0.5%). For finding steady-state solutions over arbitrary two-dimensional domains (not constrained to rectangles), we use a cGAN designed for image-to-image translation. We train this GAN on various types of geometric domains (circles, squares, triangles, shapes with one circular or rectangular hole), achieving accurate results on test data made up of geometries similar to those in training (MAE < 1%). For both of these GANs, we experiment with different loss function terms, showing that a term using the gradients of solution images significantly improves the basic cGAN but not the image-to-image GAN. Lastly, we show that the image-to-image GAN performs poorly when applied to two-dimensional geometries that vary in structure from training data (MAE < 8% for shapes with multiple holes or different shaped holes). This demonstrates the cGAN's lack of generalizability. While the cGAN is an accurate and computationally efficient method when trained and tested on similarly structured data, it is a much less reliable method when applied to data that is slightly different in structure from the training data.

97 MATHEMATICS AND COMPUTING↗

Multidimensional simulations of Mckenna-driven flow tube configuration: Investigating non-ideality in NO x formation flow tube experiments

Multidimensional simulations have been conducted to simulate atmospheric pressure, flat-flame/McKenna-burner-driven-flow tube experiments targeted to obtain NO x speciation data for predicting/analyzing syngas combustion emissions. In a prior work, we demonstrated the impacts of multidimensional transport on post flame region prediction departures from those assuming unidimensional flow/transport conditions. In this work, we develop and utilize a multidimensional laminar reacting flow solver to simulate the fully coupled flame and post flame regions to further elucidate the impacts of the earlier unidimensional modeling assumptions on interpreting post flame NO x experimental data. The model is used to simulate a lean, premixed syngas/air flame and its associated post flame regions within a cylindrical flow-tube-like arrangement. The combustion process takes place under atmospheric condition with trace amount of NO x seeding fed into the inlet gas stream. The spatial evolution of NO x species (NO and NO 2 ) in the flame and in the post-combustion zone suggests two distinct regions: 1) a region encompassing the flame structure itself; and 2) a post flame region in which the temperature decays due to both axial and radial transport processes. The predictions show that for the conditions studied, a pulsatile flow field exists due to the formation of an expanding and contracting recirculation zone in the outer periphery of the flow tube. By resolving the nature of the flow, the resulting time-averaged temperature and species concentrations show improved agreement with existing experimental measurements. The flow-field interaction results in radial inhomogeneities in the NO 2 profiles with the maximum concentration offset from the flow centerline. The location of the peak in NO 2 is coupled with radial temperature gradients from wall cooling effects and their significant influence on NO/NO 2 interconversion kinetics, producing notable NO 2 accumulation in regions near the wall. Geometrical configurations capable of suppressing/minimizing the pulsatile nature are also investigated and the results are compared. Other experimental configurations could be considered in parametric simulations to determine the optimal configuration that would minimize non-idealities in the observations. The work shows the value in performing such computations in advance of settling on a particular design for flow tube/flow reactor experiments.

42 ENGINEERING↗

Realizing mechanical frustration at the nanoscale using DNA origami

Structural designs inspired by physical and biological systems have been previously utilized to develop mechanical metamaterials with enhanced properties based on clever geometric arrangement of constituent building blocks. Here, we use the DNA origami method to realize a nanoscale metastructure exhibiting mechanical frustration, a counterpart of the well-known phenomenon of magnetic frustration. By selectively actuating reconfigurable struts, it adopts either frustrated or non-frustrated states, each characterized by distinct free energy profiles. While the non-frustrated state distributes the strain homogeneously, the frustrated mode concentrates it at a specific location. Molecular dynamics simulations reconcile the contrasting behaviors and provide insights into underlying mechanics. We explore the design space further by tailoring responses through structural modifications. Our work combines programmable DNA self-assembly with mechanical design principles to overcome engineering limitations encountered at the macroscale to design dynamic, deformable nanostructures with potential applications in elastic energy storage, nanomechanical computation, and allosteric mechanisms in DNA-based nanomachinery.

DNA nanostructures↗

Hybrid MEMS-CMOS ion traps for NISQ computing

Surging interest in engineering quantum computers has stimulated significant and focused research on technologies needed to make them manufacturable and scalable. In the ion trap realm this has led to a transition from bulk three-dimensional macro-scale traps to chip-based ion traps and included important demonstrations of passive and active electronics, waveguides, detectors, and other integrated components. At the same time as these technologies are being developed the system sizes are demanding more ions to run noisy intermediate scale quantum (NISQ) algorithms, growing from around ten ions today to potentially a hundred or more in the near future. To realize the size and features needed for this growth, the geometric and material design space of microfabricated ion traps must expand. In this paper we describe present limitations and the approaches needed to overcome them, including how geometric complexity drives the number of metal levels, why routing congestion affects the size and location of shunting capacitors, and how RF power dissipation can limit the size of the trap array. Finally, we also give recommendations for future research needed to accommodate the demands of NISQ scale ion traps that are integrated with additional technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Phonon Screening of Excitons in Atomically Thin Semiconductors

Atomically thin semiconductors, encompassing both 2D materials and quantum wells, exhibit a pronounced enhancement of excitonic effects due to geometric confinement. Consequently, these materials have become foundational platforms for the exploration and utilization of excitons. Recent ab initio studies have demonstrated that phonons can substantially screen electron-hole interactions in bulk semiconductors and strongly modify the properties of excitons. While excitonic properties of atomically thin semiconductors have been the subject of extensive theoretical investigations, the role of phonon screening on excitons in atomically thin structures remains unexplored. In this Letter, we demonstrate via ab initio GW-Bethe-Salpeter equation calculations that phonon screening can have a significant impact on optical excitations in atomically thin semiconductors. We further show that the degree of phonon screening can be tuned by structural engineering. We focus on atomically thin GaN quantum wells embedded in AlN and identify specific phonons in the surrounding material, AlN, that dramatically alter the lowest-lying exciton in monolayer GaN via screening. Our studies provide new intuition beyond standard models into the interplay among structural properties, phonon characteristics, and exciton properties in atomically thin semiconductors, and have implications for future experiments.

2-dimensional systems↗