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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 361 records · Page 20

Measurement of Temperature Fluctuations and Microscopic Growth Rates in a Silicon Floating Zone and Microgravity

A silicon crystal growth experiment has been accomplished using the floating-zone technique under microgravity on a sounding rocket (TEXUS 36). Measurements of temperature fluctuations in the silicon melt zone due to time dependent thermocapillary convection (Marangoni convection) and an observation of the microscopic growth rate were simultaneously performed during the experiment. Temperature fluctuations of about 0.5 - 0.7 C with a frequency range < 0.5Hz were detectable. The microscopic growth rate fluctuates considerably around the average growth rate of 1 mm/min: Growth rates up to 3 to 4mm/min, close to zero mm/min, as well as negative values (backmelting) were observed. Dopant striations are clearly visible in the Sb-doped crystal. They were characterized by Spreading Resistance measurements and Differential Interference Contrast microscopy. The frequencies of temperature fluctuations, microscopic growth rates, and the dopant inhomogeneities correspond quite well, with main frequencies between 0.1 and 0.3 Hz. 3D numerical simulations were performed to predict the optimum position of the temperature sensor, and the characteristic temperature amplitudes and frequencies. At a position 3.4mm above the interface and 1.4mm inside the melt, equivalent to the sensor tip position in the experiment, temperature fluctuations up to 1.8 C and frequencies ? 0.25Hz were found in the simulations.

Schweizer, Markus↗

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗

GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure

We propose GrainGNN, a surrogate model for the evolution of polycrystalline grain structure under rapid solidification conditions in metal additive manufacturing. High fidelity simulations of solidification microstructures are typically performed using multicomponent partial differential equations (PDEs) with moving interfaces. The inherent randomness of the PDE initial conditions (grain seeds) necessitates ensemble simulations to predict microstructure statistics, e.g., grain size, aspect ratio, and crystallographic orientation. Here, currently such ensemble simulations are prohibitively expensive and surrogates are necessary.In GrainGNN, we use a dynamic graph to represent interface motion and topological changes due to grain coarsening. We use a reduced representation of the microstructure using hand-crafted features; we combine pattern finding and altering graph algorithms with two neural networks, a classifier (for topological changes) and a regressor (for interface motion). Both networks have an encoder-decoder architecture; the encoder has a multi-layer transformer long-short-term-memory architecture; the decoder is a single layer perceptron.We evaluate GrainGNN by comparing it to high-fidelity phase field simulations for in-distribution and out-of-distribution grain configurations for solidification under laser power bed fusion conditions. GrainGNN results in 80%–90% pointwise accuracy; and nearly identical distributions of scalar quantities of interest (QoI) between phase field and GrainGNN simulations compared using Kolmogorov-Smirnov test. GrainGNN's inference speedup (PyTorch on single x86 CPU) over a high-fidelity phase field simulation (CUDA on a single NVIDIA A100 GPU) is 150×–2000× for 100-initial grain problem. Further, using GrainGNN, we model the formation of 11,600 grains in 220 seconds on a single CPU core.

36 MATERIALS SCIENCE↗

The Influence of Processing Parameters on the Transition Zone for Blended Material 3D Printing

The use of Multiple Materials (MM) in Additive Manufacturing (AM) is increasingly important for expanding the range of applications in the manufacturing industry, particularly for large-format processes. Typically, polymer-based AM incorporates MM transitions through discrete interfaces between layers. This arrangement significantly increases the occurrence of layer delamination failures due to decreased bonding between dissimilar polymers. Elimination of discrete material interfaces by continuously transitioning from Material A to B provides a possible solution. Such continuous gradients could be used to create functionally graded structures that take full advantage of AM’s capability to deliberately impart site-specific properties. Cincinnati’s Big Area Additive Manufacturing (BAAM) system at Oak Ridge National Lab has been equipped with a dual-hopper system that enables in-situ material switching specifically intended for functionally graded and MM printing. The resulting material transition exhibits varied behavior based on printing conditions, which can have an impact on part design and resulting mechanical properties. In this work, the transition zone is characterized as a function of the printing screw speed (related to volumetric flow) and the screw geometry.

Brackett, James↗

Integrated three-dimensional characterization of reactive phase formation and coarsening during isothermal annealing of metastable Zn–3Mg–4Al eutectic

Microstructural instabilities associated with a metastable lamellar eutectic when exposed to an elevated temperature were analyzed in a Zn-3Mg-4Al alloy as a model system. X-ray diffraction and scanning electron microscopy showed that annealing at a temperature 43 K below the equilibrium eutectic temperature converted the metastable ternary MgZn 2 /η-Zn/β-ZnAl eutectic to a stable mixture of Mg 2 Zn 11 /η-Zn/α-Al. 3D EBSD suggested that supersaturation of η-Zn with Mg and Al eased difficulties in nucleation of Mg 2 Zn 11 and α-Al at the MgZn 2 /η-Zn phase interfaces. Quasi-in-situ X-ray nanotomography revealed that a reactive diffusion process prevailed in an early stage of annealing leading to rapid consumption of MgZn 2 for growth of Mg 2 Zn 11 and concomitant thinning and pinch-off of η-Zn lamellae. The reactive diffusion process also brought about significant and quantifiable changes in the topological characteristics of the η-Zn phase at remarkably shorter time scales compared to Rayleigh instability and Ostwald ripening mechanisms. Overall, the present results provide fresh insights on the short-term annealing effects on metastable eutectics, with relevance to structural evolution in additive manufacturing.

36 MATERIALS SCIENCE↗

A Discrete Dendrite Dynamics Model for Epitaxial Columnar Grain Growth in Metal Additive Manufacturing with Application to Inconel

Epitaxial columnar grain growth is a prevalent microstructural feature in the additive manufacturing (AM) of metal components such as Inconel, with cubic unit cell crystal lattice structure (face centered cubic (FCC) or body centered cubic (BCC)). These columnar grains evolve from the partly molten grains in the substrate or the solidified metal. This work proposes an efficient model to simulate the competitive growth of epitaxial columnar dendritic grains. The proposed model tracks the dynamic changes in the dendrites emanating from discrete points along the solid/liquid interface of a quasi-steady melt pool (MP). These dynamic changes include convergence and divergence of growing dendrites. The model is extended to predict the microstructure of large 3D parts and experimentally validated by comparing the simulation results for laser powder bed fusion (L-PBF) and wire-arc additive manufacturing (WAAM) processes. The microstructure and pole figures are predicted for Inconel 718 samples produced by L-PBF and Inconel 740H samples produced by WAAM processes. Finally, the model predictions compare well with the observed microstructure and pole figures results for both the L-PBF and WAAM processes.

20 FOSSIL-FUELED POWER PLANTS↗

VERAView User's Manual

VERAView has been developed as an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software is easy to install, intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. This document provides a brief overview of the software and some description of the major features of the application, including examples of each of the encapsulated “widgets” that have been implemented thus far. VERAView is still under major development and large changes in the software and this document are still anticipated.

97 MATHEMATICS AND COMPUTING↗

Polar Firn Properties in Greenland and Antarctica and Related Effects on Microwave Brightness Temperatures

In studying the mass balance of polar ice sheets, fluctuations of firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations in the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, Snow Radar echoes, microwave brightness temperatures, and modelling results from the Community firn model (CFM) are used. It is shown that firn density profiles can be represented using 3 processes: “long” and “short” length scale density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5-2 GHz brightness temperatures and Snow Radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three scale description of the firn. Short and long scale firn processes are modelled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D random layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modelling to match measured 0.5-2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the SMOS satellite at DOME C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5-2 GHz brightness temperature measurements are shown to be sensitive to long scale firn density fluctuations with density standard deviations in the range 0.01-0.06 g/cm^3 and vertical correlation lengths of 6-20 cm.

Haokui Xu↗

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

Integrated Multiscale Model for Design of Robust 3D Solid-state Lithium Batteries

In FY23, we successfully established the multiscale modeling framework for probing the effects of materials microstructure on cell performance of 3D solid-state batteries. The framework covers physicochemical processes co-evolving at the atomistic and microstructure scales. Our simulations revealed the mechanism of initial interfacial degradation, formation of secondary phases, and the structure-property relationship for ion transport and mechanical stability at the interface. In addition, we also established the microstructure-performance relationships by performing sensitivity tests of various microstructure features and extracting their impact on cell performance during charge-discharge cycles. We have successfully applied our multiscale, multiphysics modeling capability to common electrode and electrolyte materials that are of interests to VTO and the experimental teams within the US-Germany collaboration. The insights we obtained from these simulations provide valuable design principles to optimize materials properties for advanced 3D solid-state batteries.

25 ENERGY STORAGE↗

Atomic Gradient Structures: Atomic Gradient Structure Alters Electronic Structure in 3D across the Bulk and Enhances Photoactivity

Understanding structure–function relationships enables the design of materials with tailored functionalities. The long-standing challenge is to design materials with high active volume to improve the efficiency. Tailored grain boundaries and lattice defects are traditionally used to tune the electronic structure near interfaces or defects to promote electron and hole separation. However, the active volume of point defect sites or interfaces in these traditional photocatalysts is extremely low. In this work, we report a structure with continuous atomic positional deformation across the bulk, altering the electronic structure in three-dimension and creating a significantly high active volume. Such a structure in anatase is obtained and tuned by phase transformation during heating process. Transmission electron microscopy and density functional theory results reveal that atomic deformations result in continuous band bending across the particles, facilitating electron–hole separation, inhibiting their recombination, and inducing dramatically enhanced photoactivity. These findings enable a different materials design paradigm that can potentially be harnessed for a broad range of applications.

TiO2↗

3D Scanning System to Assess Gravity-Dependent Body Shape Changes

The human body shows unique morphological changes when exposed to different gravity conditions, including muscle atrophy, fluid shift, and spinal elongation. Such changes need to be incorporated for human-system integration in the vehicle habitat, garment, and spacesuit designs, as inaccurate body measurements can result in suboptimal crew protection that can potentially decrease injury tolerance. However, measurement tools have not been available for accurate assessments of body shape changes. This work aimed to develop a prototype 3-D body scanning system with the configuration and performance optimized for in-flight crewmember body scanning. A scan hardware system was developed using Intel RealSense commercial off-the-shelf 3D sensors. The sensor parameters were iteratively optimized and tested to obtain the performance level needed for body scanning. A scan booth structure was fabricated, with the overall size 4 x 4 x 8 feet. The specific number of sensors and mounting positions were determined by iterative simulations, which indicated that 16 cameras can capture 94% and 96% of body surface area from the 1st percentile female and 99th percentile male crew population subject. The mounted sensors were linked through a mix of USB-C and USB-3 cables and operated for data acquisition from a Linux laptop computer. A software prototype was developed using Python and Tkinter graphical user interface toolkit. A calibration procedure was also built using a panel of QR codes. A computer vision tool detected and decoded the unique ID and pattern locations of the QR codes. The calibration information determined the position and orientation of the 3D sensors with respect to each other. The scanner performance was assessed using a set of 3D printed custom manikins. The manikin size and shape were derived from the previous ISS study, which measured the crewmembers’ anthropometry changes across the different flight phases. The average anthropometric measurements at the pre-flight and flight day 15 were sampled and projected onto the 1st percentile female and 99th percentile male body shapes. Another pair of manikins were also 3D printed to simulate the neutral body posture, estimated from ISS microgravity environments. A preliminary analysis assessed the performance of the newly developed scanner against the reference scanner, which has been used at the NASA JSC for crew and test subject anthropometry. Although the new scanner data showed several artifacts and missing geometries in the occluded body areas such as armpits and crotch, overall shape matched with the reference scan. When the manikin surface coordinates were compared, a root mean square error of 1.3 cm was observed from the manikin torso segment. Linear measurements including the stature, knee height and circumference measurements at the chest and calf showed differences from the reference scan measurements, ranging between 0.3 and 0.9 cm. Overall, this work demonstrated a development framework for an in-flight scanner with design and operation optimized for crewmember body scanning. Further improvement can potentially provide previously unavailable anthropometric data from different gravitational environments, including 0-g, 1/6-g, and 1-g. Such data can improve suit fit, habitat design, exercise efficacy quantification and sizing of orthostatic intolerance garments.

K H Kim↗

Phase-stabilized 2D/3D hetero-bilayers via lattice matching for efficient and stable inverted solar cells

2D-on-3D (2D/3D) perovskite heterostructures with engineered energy landscapes offer the potential to realize efficient and stable inverted solar cells. However, managing the energy landscape using 2D perovskites with thicker inorganic layers n > 1 necessitates the usage of the chemically unstable methylammonium MA + . Here, we synthesized formamidinium (FA)-rich and pure-FA n = 3 Ruddlesden-Popper (RPP) and Dion-Jacobson perovskite (DJP) single crystals by identifying ligands with suitably lattice-matched organic and inorganic components of the 2D lattice. These crystals were translated onto 3D perovskites as capping layers, forming 2D/3D hetero-bilayers (HBs). Degradation studies revealed that HBs with butylammonium-based RPPs as capping layers rapidly phase segregate into non-perovskites under combined extrinsic stressors, compromising the underlying 3D layer, whereas FA-rich DJPs based on 3-aminomethylpiperidine retain their phase stability. The DJP HBs also possess a favorable energy landscape and electron transport at the 2D/3D interface, enabling inverted solar cells with a champion PCE of 25.33% and remarkable stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Jupiter Environment Tool

The Jupiter Environment Tool (JET) is a custom UI plug-in for STK that provides an interface to Jupiter environment models for visualization and analysis. Users can visualize the different magnetic field models of Jupiter through various rendering methods, which are fully integrated within STK s 3D Window. This allows users to take snapshots and make animations of their scenarios with magnetic field visualizations. Analytical data can be accessed in the form of custom vectors. Given these custom vectors, users have access to magnetic field data in custom reports, graphs, access constraints, coverage analysis, and anywhere else vectors are used within STK.

Sturm, Erick J.↗

Comparison of Staggered Grid Finite Difference Schemes for Ultrasound Simulation in Curving Composites

The optimization of ultrasonic nondestructive evaluation (NDE) simulation tools for composites has the potential to reduce both individual part inspection time and overall certification time for composite parts and structures. Inspection guidance based on simulation provides increased confidence in the veracity of inspection results in addition to time reductions. This paper outlines ongoing work targeted to advance this objective through the use of finite difference (FD) simulation techniques formulated for composite structures with realistic geometries. Two staggered grid explicit FD schemes which show promise for this purpose are assessed: the Lebedev FD scheme and the rotated staggered grid (RSG) FD scheme. Algorithmic points which provide challenges for complex geometries are addressed, in particular handling of traction free surfaces and bi-material interfaces present at lamina boundaries. Code execution time estimates are performed as well to guide feasible domain sizes relative to algorithm choice and available hardware. Three test cases are simulated: a delaminated plate, a cylinder, and a triclinic lamina. These tests demonstrate that the Lebedev FD scheme needs additional work to handle inter-laminar interfaces and traction free boundaries in the presence of stair-stepping approximations. In contrast, the simple structure of the RSG unit cell makes it more straightforward to construct a 3D simulation technique for curved composite laminates.

Frankforter, Erik↗

Surface Instability of Liquid Propellant under Vertical Oscillatory Forcing

Fluid motion in a fuel tank produced during thrust oscillations can circulate sub-cooled hydrogen near the liquid-vapor interface resulting in increased condensation and ullage pressure collapse. The first objective of this study is to validate the capabilities of a Computational Fluid Dynamics (CFD) tool, CFD-ACE+, in modeling the fundamental interface transition physics occurring at the propellant surface. The second objective is to use the tool to assess the effects of thrust oscillations on surface dynamics. Our technical approach is to first verify the CFD code against known theoretical solutions, and then validate against existing experiments for small scale tanks and a range of transition regimes. A 2D axisymmetric, multi-phase model of gases, liquids, and solids is used to verify that CFD-ACE+ is capable of modeling fluid-structure interaction and system resonance in a typical thrust oscillation environment. Then, the 3D mode is studied with an assumed oscillatory body force to simulate the thrust oscillating effect. The study showed that CFD modeling can capture all of the transition physics from solid body motion to standing surface wave and to droplet ejection from liquid-gas interface. Unlike the analytical solutions established during the 1960 s, CFD modeling is not limited to the small amplitude regime. It can extend solutions to the nonlinear regime to determine the amplitude of surface waves after the onset of instability. The present simulation also demonstrated consistent trends from numerical experiments through variation of physical properties from low viscous fluid to high viscous fluids, and through variation of geometry and input forcing functions. A comparison of surface wave patterns under various forcing frequencies and amplitudes showed good agreement with experimental observations. It is concluded that thrust oscillations can cause droplet formation at the interface, which results in increased surface area and enhanced heat transfer between the liquid and gas phases as the ejected droplets travel well into the warmer gas region.

Yang, H. Q.↗

Scaling theory of three-dimensional magnetic reconnection spreading

We develop a first-principles scaling theory of the spreading of three-dimensional (3D) magnetic reconnection of finite extent in the out of plane direction. This theory addresses systems with or without an out of plane (guide) magnetic field, and with or without Hall physics. The theory reproduces known spreading speeds and directions with and without guide fields, unifying previous knowledge in a single theory. New results include: (1) Reconnection spreads in a particular direction if an x-line is induced at the interface between reconnecting and non-reconnecting regions, which is controlled by the out of plane gradient of the electric field in the outflow direction. (2) The spreading mechanism for anti-parallel collisionless reconnection is convection, as is known, but for guide field reconnection it is magnetic field bending. We confirm the theory using 3D two-fluid and resistive-magnetohydrodynamics simulations. (3) The theory explains why anti-parallel reconnection in resistive-magnetohydrodynamics does not spread. (4) The simulation domain aspect ratio, associated with the free magnetic energy, influences whether reconnection spreads or convects with a fixed x-line length. (5) We perform a simulation initiating anti-parallel collisionless reconnection with a pressure pulse instead of a magnetic perturbation, finding spreading is unchanged rather than spreading at the magnetosonic speed as previously suggested. The results provide a theoretical framework for understanding spreading beyond systems studied here, and are important for applications including two-ribbon solar flares and reconnection in Earth’s magnetosphere.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integrated Multiscale Modeling for Design of Robust 3D Solid-State Lithium Batteries - FY21 Annual Report

This project is developing a multiscale, multi-physics modeling framework for probing the effects of materials microstructure and device architecture on ion transport within 3D ceramic solid-state battery materials, with the goal of enhancing performance and reliability. The project has three primary objectives: (1) integrate multi physics and multiscale model components; (2) understand interface- and microstructure-derived limitations on ion transport; and (3) derive key structure-performance relations for enabling future optimization.

25 ENERGY STORAGE↗