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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Discovery of spontaneous mesoscopic strain waves in nematic domains using dark-field x-ray microscopy

Electronic nematic order arises when correlated electrons spontaneously break the rotational symmetry of a crystal lattice. When electronic nematic order couples bilinearly to symmetry-breaking lattice strain, both appear together at a single ferroelastic phase transition, producing structural twin domains with distinct orientations of the nematic director. While the effects of applied strain on these domains are well established, the intrinsic behavior of spontaneous subdomain strain fields has remained unexplored. Here, we report the discovery of spontaneous mesoscopic strain waves within individual nematic domains of an iron-based superconductor, observed using dark-field x-ray microscopy (DFXM). Using this advanced full-field imaging technique, we visualize subdomain strain modulations emerging concurrently with nematic order. Elastic compatibility relations governing inhomogeneous strains provide a natural mechanism for the strain waves. Our findings reveal a broadly relevant form of strain self-organization and position DFXM as a powerful probe of the local interplay between lattice strain and electronic order.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Emergent orbital magnetization in Kitaev quantum magnets

Unambiguous identification of the Kitaev quantum spin liquid (QSL) in materials remains a huge challenge despite many encouraging signs from various measurements. To facilitate the experimental detection of the Kiteav QSL, here we propose to use remnant charge response in Mott insulators hosting QSL to identify the key signatures of QSL. We predict an emergent orbital magnetization in a Kitaev system in an external magnetic field. The direction of the orbital magnetization can be flipped by rotating the external magnetic field in the honeycomb plane. The orbital magnetization is demonstrated explicitly through a detailed microscopic analysis of the multiorbital Hubbard-Kanamori Hamiltonian and also supported by a phenomenological picture. We first derive the localized electrical loop current operator in terms of the spin degrees of freedom. Thereafter, utilizing the Majorana representation, we estimate the loop currents in the ground state of the chiral Kitaev QSL state, and obtain the consequent current textures, which are responsible for the emergent orbital magnetization. Finally, we discuss the possible experimental techniques to visualize the orbital magnetization which can be considered as the signatures of the underlying excitations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗
DOE OSTI2021

Structure Perception in 3D Point Clouds

Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗
DOE OSTI2021

Structure Perception in 3D Point Clouds: Preprint

Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

ChatGrid: Power Grid Visualization Empowered by Large Language Model

This paper presents a novel open framework, ChatGrid, for easy, intuitive, and interactive geospatial visualization of large-scale transmission networks. ChatGrid uses state-of-the-art techniques for geospatial visualization of large networks including 2.5D views, animated flows, hierarchical and level-based filtering, and aggregation to provide visual information in an easy, cognitive manner. The highlight of ChatGrid is a natural language query based interface powered by large language model (ChatGPT) that offers an enhanced interactive experience whereby the user asks a question and ChatGrid provides the information both in text and visual. We discuss the architecture, implementation, design decisions, and usage of large language model for ChatGrid.

Jin, Sichen↗
DOE OSTI2020

Liquid helium fluid dynamics studies. Final Technical Report

Future high energy physics accelerators depend on a number of advanced technologies to open the many doors of scientific discovery. Among these advanced technologies, superconducting magnets and superconducting radio frequency (SRF) cavities are the backbone of the accelerator and detector systems. But all these low temperature systems depend critically on successful and reliable operation of their supporting technologies, among which the liquid helium cooling system is of the utmost importance. To improve the quality of these systems both in terms of efficiency and reliability, a robust helium cryogenics research and development (R&D) effort is required. The proposed research to be conducted by the FSU cryogenics group aims to produce fundamental knowledge that meets this R&D need. The projects that we have completed over the past grant period at Florida State University consist of experimental research on liquid helium fluid dynamics and heat transfer problems relevant to the development of future superconducting particle physics accelerators. Liquid helium is the coolant used in all such facilities and in many of these facilities He II (the low temperature phase of liquid helium also known as superfluid helium) is preferred due to its outstanding heat transfer characteristics. The work consists of two main experimental studies that probe both fundamental as well as practical aspects of liquid helium cooling. The first is a broad and fundamental study of the heat and mass transfer processes that can occur during a sudden catastrophic loss of vacuum (SCLV) incident in a superconducting accelerator. SCLV refers to the remote but extremely critical accident scenario where atmospheric pressure air is allowed to flood into the insulating vacuum system and impinge on the liquid helium cooled surfaces in the accelerator. Safe performance and recovery from such accidents is essential to the reliable operation of superconducting accelerators. The dynamics of this process is quite complex and so our approach is to conduct a series of well-orchestrated experiments that probe the various physical phenomena that can occur during an SCLV event. The experiments are coupled with analytic and numerical analysis in an effort to develop a general understanding of the process and to assist with future accelerator design and development. The second activity is directed toward fundamental understanding of heat and mass transfer in He II, which is essential to the design of superconducting magnets and radio frequency cavities in accelerators. The work consists of flow visualization of the dynamics of He II using laser assisted techniques. Two complementary techniques are used to study the fundamentals of the turbulent state. The first technique uses neutrally buoyant solid hydrogen particles to probe the flow fields of the superfluid and normal fluid components. The other technique uses laser excited He2* molecules as tracers of the normal fluid motion within the He II. The activities also included an effort to use visualization techniques to locate transient hot spots in radio frequency superconducting cavities. Such work provides valuable information about the heat transfer process in He II and its impact on the performance of superconducting devices. The research effort at Florida State University is not directly in support of a specific high energy physics experiment or facility. Rather, the work is general and coordinated with HEP accelerator laboratories to provide valuable insight that can assist with future accelerator development.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

State of the Art of Molecular Visualization in Immersive Virtual Environments

Abstract Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of low temperature fuel cell holders for Operando x-ray micro and nano computed tomography to visualize water distribution

Abstract Synchrotron x-ray imaging techniques, like x-ray computed tomography (CT) and radiography have proven instrumental in expanding the communities knowledge of complex transport and reaction kinetics in electrochemical devices such as fuel cells and electrolyzers. This work presents the development of novel x-ray CT imaging techniques for operando visualization of water within low temperature fuel cells at spatial resolutions spanning the micro and nano scales. The design of operando sample holders, for both micro x-ray CT and nano CT experiments is described in depth, and prototypes of these sample holders were evaluated across a set of requirements, the most important of which are x-ray transmissibility, electrical conductivity and mechanical stability. Water segmentation from micro x-ray CT data was enabled by an image subtraction method, where the image without water is subtracted from the one with water. Through iterative experimentations, the operando nano CT cell was developed to optimize mechanical compression, electric conductivity and gas flow. While three-dimensional fuel cell reconstructions were shown possible, there remain challenges to overcome at typical lower energies (8 keV) due to beam damage, whereas it is not as significant for higher energies (>17.5 keV).

Kulkarni, Devashish↗
DOE OSTI2020

Quantitative probing of the fast particle motion during the solidification of battery electrodes

Synchrotron x-ray tomography represents one of the most powerful imaging techniques that can visualize the three-dimensional microstructural complexity with a high spatial resolution. To date, however, the temporal resolution of this technique has been handicapped by the intrinsic limitations in the data acquisition speed and the lack of a suitable data processing method. The present study aims to fundamentally resolve this challenge by implementing a data analysis method that is based on differentiating discrete tomography reconstruction from a continuous scan reconstruction. With this methodological development, we capture and quantify the particle motion during the solidification of battery electrodes and reveal the statistics of the dynamically evolving motion in the drying process, which has been challenging to resolve. We discover that the particle motion exhibits a strong dependence on its geometric location within a drying electrode. Our results also imply that the final electrode quality can be controlled by balancing the solvent evaporation rate and the particle mobility in the region close to the drying surface.

25 ENERGY STORAGE↗
DOE OSTI2022

Rapid macrovoid characterization in membranes prepared via nonsolvent-induced phase separation: A comparison between 2D and 3D techniques

Optimizing the performance of asymmetric membranes prepared via nonsolvent-induced phase separation (NIPS) requires a quantitative understanding of how processing variables influence membrane morphology. Presently, the most useful structural quantification techniques require 3D visualization of the membrane structure and are best suited for studies seeking detailed information on small datasets. This study proposes and validates a rapid and accurate technique for quantifying macroporosity (i.e., D m ), a simple descriptor of sublayer macrovoid content in asymmetric membranes D m . values measured from segmented cross-sectional imaging performed via X-ray computed tomography (XCT) and scanning electron microscopy (SEM) are presented and compared for three asymmetric membranes prepared from commercial polymers. Importantly, analyses of 3D XCT membrane reconstructions reveal that D m is described by a single, centralized mean, which demonstrates that macrovoid content is spatially homogenous. Thus, D m can be approximated from limited sampling of the 2D cross-sectional membrane structure via SEM. A proposed 2D SEM sampling method provides D m estimates within ±6% of corresponding 3D XCT values with 30 independent measurements for the three membranes. Further sensitivity is achieved using complementary descriptors such as macrovoid count density (i.e., C m ). This technique is thus a useful tool for characterizing macroporosity from a broad selection of membrane samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Observation of Persistent Zero Modes and Superconducting Vortex Doublets in UTe 2

Superconducting vortices can reveal electron pairing details and nucleate topologically protected states. Yet, vortices of bulk spin-triplet superconductors have never been visualized at the atomic scale. Recently, UTe 2 has emerged as a prime spin-triplet superconductor, but its superconducting order parameter is elusive, and whether time-reversal symmetry (TRS) is broken remains unsettled. Here, in this work, we visualize vortices on the (011) surface of ultraclean UTe 2 single crystals (T c = 2.1 K) using scanning tunneling microscopy (STM). We introduce $\frac{d^{2}𝐼}{d𝑉^{2}}$ imaging as an effective technique for vortex visualization in superconductors with substantial residual zero-energy density of states (DOS), as in UTe 2 . Anisotropic single-flux-quantum vortices, with coherence lengths of ∼12 nm (4 nm) parallel (perpendicular) to the a -axis, form a triangular vortex lattice (VL) under a small out-of-plane magnetic field. The invariance of vortex structures and VL under changes of field polarity and cooling history strongly supports time-reversal invariant superconductivity under zero field. At vortex cores (VCs), nonsplit, spectrally sharp zero-bias conductance peaks (ZBPs) persist up 8 T that are consistent with symmetry-protected Majorana zero modes (MZMs) in a topological vortex line. Close examination of vortex structures reveals a mirror-asymmetric doublet─one with ZBPs and another with an enhanced apparent gap, possibly originating from a field-induced multicomponent order parameter.

UTe2↗
DOE OSTI2024

Data-Driven Computation of Probabilistic Marching Cubes for Efficient Visualization of Level-Set Uncertainty

Uncertainty visualization is an important emerging research area. Being able to visualize data uncertainty can help scientists improve trust in analysis and decision-making. However, visualizing uncertainty can add computational overhead, which can hinder the efficiency of analysis. In this paper, we propose novel data-driven techniques to reduce the computational requirements of the probabilistic marching cubes (PMC) algorithm. PMC is an uncertainty visualization technique that studies how uncertainty in data affects level-set positions. However, the algorithm relies on expensive Monte Carlo (MC) sampling for the multivariate Gaussian uncertainty model because no closed-form solution exists for the integration of multivariate Gaussian. In this work, we propose the eigenvalue decomposition and adaptive probability model techniques that reduce the amount of MC sampling in the original PMC algorithm and hence speed up the computations. Our proposed methods produce results that show negligible differences compared with the original PMC algorithm demonstrated through metrics, including root mean squared error, maximum error, and difference images. We demonstrate the performance and accuracy evaluations of our data-driven methods through experiments on synthetic and real datasets.

Athawale, Tushar↗
DOE OSTI2023

Examining phase separation and crystallization in glasses with X-ray nano-computed tomography

X-ray nano-computed tomography (nano-CT) is a powerful technique to characterize and visualize 3 dimensional (3D) phenomena in complex glasses at the nanoscale. This technique can offer a unique opportunity to explore the intricate morphology of multicomponent glass and glass-ceramic samples, due to its low X-ray energy and high spatial resolution (down to 50 nm). In the current demonstration paper, nano-CT provided insight into crystallization and phase separation, as well as a variety of other phenomena, including corrosion, fracture, and porosity. At scales ranging from 100 to 20 μm, the microstructures of phase separation in borosilicate, complex silicate, and chalcogenide glass compositions were examined. In addition, crystallites present in simulant nuclear waste glasses, volcanic glasses, and other related samples were explored. Nano-CT analysis can add to the understanding of (1) the formation processes, (2) distributions, interactions, and compositions of phases, and (3) the mechanisms, structures, and growth of crystallization and phase separation. Nano-CT offers wide potential in the field of glass science, especially when (1) common characterization methods are insufficient, (2) simple sample preparation is required, (3) 3D rendering is needed, or (4) compelling images of small, complex features are desired.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reaction inhomogeneity coupling with metal rearrangement triggers electrochemical degradation in lithium-rich layered cathode

High-energy density lithium-rich layered oxides are among the most promising candidates for next-generation energy storage. Unfortunately, these materials suffer from severe electrochemical degradation that includes capacity loss and voltage decay during long-term cycling. Present research efforts are primarily focused on understanding voltage decay phenomena while origins for capacity degradation have been largely ignored. Here, we thoroughly investigate causes for electrochemical performance decline with an emphasis on capacity loss in the lithium-rich layered oxides, as well as reaction pathways and kinetics. Advanced synchrotron-based X-ray two-dimensional and three-dimensional imaging techniques are combined with spectroscopic and scattering techniques to spatially visualize the reactivity at multiple length-scales on lithium- and manganese-rich layered oxides. These methods provide direct evidence for inhomogeneous manganese reactivity and ionic nickel rearrangement. Coupling deactivated manganese with nickel migration provides sluggish reaction kinetics and induces serious structural instability in the material. Our findings provide new insights and further understanding of electrochemical degradation, which serve to facilitate cathode material design improvements.

25 ENERGY STORAGE↗
DOE OSTI2023

Spin-mediated shear oscillators in a van der Waals antiferromagnet

Understanding how microscopic spin configuration gives rise to exotic properties at the macroscopic length scale has long been pursued in magnetic materials. One seminal example is the Einstein-de Haas effect in ferromagnets, in which angular momentum of spins can be converted into mechanical rotation of an entire object. However, for antiferromagnets without net magnetic moment, how spin ordering couples to macroscopic movement remains elusive. Here we observed a seesaw-like rotation of reciprocal lattice peaks of an antiferromagnetic nanolayer film, whose gigahertz structural resonance exhibits more than an order-of-magnitude amplification after cooling below the Neel temperature. Using a suite of ultrafast diffraction and microscopy techniques, we directly visualize this spin-driven rotation in reciprocal space at the nanoscale. This motion corresponds to interlayer shear in real space, in which individual micro-patches of the film behave as coherent oscillators that are phase-locked and shear along the same in-plane axis. Using time-resolved optical polarimetry, we further show that the enhanced mechanical response strongly correlates with ultrafast demagnetization, which releases elastic energy stored in local strain gradients to drive the oscillators. Finally, our work not only offers the first microscopic view of spin-mediated mechanical motion of an antiferromagnet but it also identifies a new route towards realizing high-frequency resonators up to the millimetre band, so the capability of controlling magnetic states on the ultrafast timescale can be readily transferred to engineering the mechanical properties of nanodevices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Operando video microscopy of Li plating and re-intercalation on graphite anodes during fast charging

Despite the demand for fast-charging lithium (Li)-ion batteries, high-energy-density batteries with thick graphite anodes are limited by Li plating when charging at >4C rates. In this work, plan-view operando video microscopy is applied on >3 mA h cm –2 calendared graphite electrodes to study the dynamic evolution of local state-of-charge (SoC) and Li plating during fast charging. This technique allows for visualization of the spatial heterogeneity in SoC across the electrode, nucleation and growth of Li filaments, Li re-intercalation into graphite, “dead Li” formation, and SoC equilibration. The operando microscopy analysis is complemented by ex situ imaging of through-plane gradients in SoC to gain a three-dimensional visualization of spatial heterogeneity. We demonstrate that (1) Li plating preferentially nucleates on the graphite particles that lithiate fastest during fast charging; (2) the onset of Li plating correlates with the local minimum of the graphite electrode potential; (3) galvanic corrosion currents are responsible for Li re-intercalation, dead Li formation, and SoC re-equilibration after fast charging; and (4) electrochemical signatures during OCV rest or discharge are associated with Li re-intercalation into graphite. Furthermore, this work provides insight into the Li–graphite interactions at the composite electrode level and can be used to inform strategies to diagnose and mitigate Li plating during fast charging.

25 ENERGY STORAGE↗