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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Topological data analysis of task-based fMRI data from experiments on schizophrenia

We use methods from computational algebraic topology to study functional brain networks, in which nodes represent brain regions and weighted edges represent similarity of fMRI time series from each region. With these tools, which allow one to characterize topological invariants such as loops in high-dimensional data, we are able to gain understanding into low-dimensional structures in networks in a way that complements traditional approaches based on pairwise interactions. In the present paper, we analyze networks constructed from task-based fMRI data from schizophrenia patients, healthy controls, and healthy siblings of schizophrenia patients using persistent homology, which allows us to explore the persistence of topological structures such as loops at different scales in the networks. We use persistence landscapes, persistence images, and Betti curves to create output summaries from our persistent-homology calculations, and we study the persistence landscapes and images using k-means clustering and community detection. Based on our analysis of persistence landscapes, we find that the members of the sibling cohort have topological features (specifically, their 1-dimensional loops) that are distinct from the other two cohorts. From the persistence images, we are able to distinguish all three subject groups and to determine the brain regions in the loops (with four or more edges) that allow us to make these distinctions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data

We present a novel multi-modal data fusion technique using topological features. The method, TopFusion, leverages the flexibility of topological data analysis tools (namely persistent homology and persistence images) to map multi-modal datasets into a common feature space by forming a new multi-channel persistence image. Each channel in the image is representative of a view of the data from a modality-dependent filtration. We demonstrate that the topological perspective we take allows for more effective data reconstruction, i.e. imputation. In particular, by performing imputation in topological feature space we are able to outperform the same imputation techniques applied to raw data or alternatively derived features. We show that TopFusion representations can be used as input to downstream deep learning-based computer vision models and doing so achieves comparable performance to other fusion methods for classification on two multi-modal datasets.

Myers, Audun D.↗
DOE OSTI2021

Quantitative and interpretable order parameters for phase transitions from persistent homology

Here, we apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and fully frustrated XY models. In particular, we use persistent homology, which computes the births and deaths of individual topological features as a coarse-graining scale or sublevel threshold is increased, to summarize multiscale and high-point correlations in a spin configuration. We employ vector representations of this information called persistence images to formulate and perform the statistical task of distinguishing phases. For the models we consider, a simple logistic regression on these images is sufficient to identify the phase transition. Interpretable order parameters are then read from the weights of the regression. This method suffices to identify magnetization, frustration, and vortex-antivortex structure as relevant features for phase transitions in our models. We also define “persistence” critical exponents and study how they are related to those critical exponents usually considered.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Pore-Filling Induced Solid Electrolyte Failure of Ti-Doped Na 3 Zr 2 Si 2 PO 12 Characterized by Operando Synchrotron X-Ray Tomography

Solid-state batteries (SSBs), particularly those utilizing sodium metal, are emerging as a promising technology due to their potential for enhanced safety, higher energy density, and longer cycle life. NASICON (Na superionic conductor) materials, known for their robust crystalline structure and high ionic conductivity, are pivotal in the development of efficient sodium all-solid-state batteries. These materials exhibit high room-temperature ionic conductivity and electrochemical stability, making them ideal for various applications. Research has focused on improving NASICON's ionic conductivity and stability through doping, interface regulation, and composite anode design. Recent advancements include Ti-doped Na 3 Zr 2 Si 2 PO 12 (Ti-NZSP), which demonstrates improved surface stability, higher ionic conductivity, and increased critical current density. However, challenges such as Na dendrite formation and mechanical integrity under operational conditions persist. Advanced imaging techniques like operando synchrotron X-ray tomography have provided insights into failure mechanisms, revealing that pore-filling and dendrite growth are significant issues. Understanding these processes is essential for enhancing the performance and safety of Na-based SSBs. Here, this study underscores the need for continued research to address these challenges and develop reliable, high-performance solid-state electrolytes for future energy storage solutions.

25 ENERGY STORAGE↗
DOE OSTI2025

Characterization of fluorite-structured ferroelectrics using transmission electron microscopy: Techniques, challenges, and recent advances

Fluorite-structured ferroelectrics, such as hafnium oxide and its alloyed variants, are key candidates for next-generation memory devices. Yet, fundamental questions about switching mechanisms, domain dynamics, and phase evolution remain open. Transmission electron microscopy (TEM) provides unique capabilities to address these challenges by simultaneously resolving the positions of anions and cations, chemical variations, and structural transformations. Recent advances—including in situ heating, electron beam-induced switching, electron energy loss spectroscopy, and differential phase contrast imaging—have revealed critical insights into phase transitions, potential switching pathways, and oxygen vacancy behavior. However, experimental barriers such as TEM sample-preparation-induced artifacts, high coercive fields, and imaging constraints persist, especially for polycrystalline films. By offering a focused overview of current TEM developments in fluorite ferroelectrics, this work outlines how TEM contributes to understanding key phenomena and proposes a roadmap for future studies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DMTN-197: Streak Masking in DM Image Processing

Streaks caused by satellites are a persistent problem in optical images, and their occurrence will likely increase in the coming years. Many Hyper Suprime-Cam images are already affected by streaks, and the same is expected for Rubin Observatory data. In the LSST Data Release Production (DRP), most streaks and other artifacts are already detected and masked by the algorithm CompareWarpAssembleCoadd. However, some streaks are not caught at this stage and can contaminate the final coadds and detection catalogs. To find and mask these, we adopt a morphologically-based method for detecting streaks, which uses the Kernel-Based Hough Transform to detect straight lines. Once the lines are detected, the streak profile is fit and the affected portion of the image is masked out. This algorithm, maskStreaks, is included in the meas_algorithms package and is used in CompareWarpAssembleCoadd to remove streaks from coadds. Similar implementation in the Alert Production Pipeline is possible but has not been implemented.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Persistent hot carrier diffusion in boron arsenide single crystals imaged by ultrafast electron microscopy

Cubic boron arsenide (BAs) is promising for microelectronics thermal management because of its high thermal conductivity. Recently, its potential as an optoelectronic material is also being explored. However, it remains challenging to measure its photocarrier transport properties because of small sizes of available high-quality crystals. Here, we use scanning ultrafast electron microscopy (SUEM) to directly visualize the diffusion of photocarriers in BAs single crystals. Surprisingly, we observed ambipolar diffusion at low optical fluence with persistent hot carrier dynamics for above 200 ps, which can likely be attributed to the large frequency gap between acoustic and optical phonons, the same feature that is responsible for the high thermal conductivity. At higher optical fluence, we observed spontaneous electron-hole separation. Our results show BAs is an attractive optoelectronic material combining high thermal conductivity and excellent photocarrier transport properties. Finally, our study also demonstrates the capability of SUEM to probe photocarrier transport in emerging materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Persistence of Late Substantial Patient-Reported Symptoms (LAPERS) After Radiochemotherapy Including Image Guided Adaptive Brachytherapy for Locally Advanced Cervical Cancer: A Report From the EMBRACE Study

This report describes the persistence of late substantial treatment-related patient-reported symptoms (LAPERS) in the multi-institutional EMBRACE study on magnetic resonance image guided adaptive brachytherapy in locally advanced cervical cancer (LACC).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Stabilization and control of persistent current magnets using variable inductance

Ultra-stable, tunable magnetic fields are desirable for a wide range of applications in medical imaging, electron microscopy, quantum science, and atomic physics. Superconducting magnets operated in persistent current mode, with device current flowing in a closed superconducting loop disconnected from a power source, are a common approach for applications with the most stringent requirements on temporal field stability. In this work, we present a method for active control of this persistent current by means of dynamic inductance change within the superconducting circuit. For a first realization of this general technique, we consider a variable superconducting inductor placed in series with the main magnet. The inductor acts as a dynamic flux storage device capable of transferring flux to or from the main magnet through inductance change. This allows for fine and fast adjustments of the persistent current without the use of thermal switches that limit the speed and accuracy of many present-day methods. With first experiments employing this technique, we demonstrate stabilization of a 1.95 T Nb–Ti round lens for electron microscopy against decay resulting from residual losses in the superconducting circuit, and more generally show flexibility for precise control over the magnitude and waveform of the persistent current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Low-dose high-resolution $\mathrm{TOF}$-$\mathrm{PET}$ using ionization-activated multi-state low-$\mathrm{Z}$ detector media

We propose PET scanners using low atomic number media that undergo a persistent local change of state along the paths of the Compton recoil electrons. Measurement of the individual scattering locations and angles, deposited energies, and recoil electron directions allows using the kinematical constraints of the 2-body Compton scattering process to perform a statistical time-ordering of the scatterings, with a high probability of precisely identifying where the gamma first interacted in the detector. In these cases the Line-of-Response is measured with high resolution, determined by the underlying physics processes and not the detector segmentation. There are multiple such media that act through different mechanisms. As an example in which the change of state is quantum-mechanical through a change in molecular configuration, rather than thermodynamic, as in a bubble chamber, we present simulations of a two-state photoswitchable organic dye, a ‘Switchillator’, that is activated to a fluorescent-capable state by the ionization of the recoil electrons. The activated state is persistent, and can be optically excited multiple times to image individual activated molecules. Energy resolution is provided by counting the activated molecules. Location along the LOR is implemented by large-area time-of-flight MCP-PMT photodetectors with single photon time resolution in the tens of ps and sub-mm spatial resolution. Simulations indicate a large reduction of dose.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Case Report: Differential diagnosis of hematuria in the emergency department: emphasizing double J stent-inferior vena cava fistula

Introduction Hematuria, a common clinical indicator of genitourinary tract pathology, arises from diverse etiologies including calculi, infections, malignancies, trauma, and iatrogenic causes. Initial evaluation requires hemodynamic assessment, identification of underlying causes, and urinary drainage optimization. This report highlights a rare case of iatrogenic hematuria secondary to double-J stent migration into the inferior vena cava. Case presentation A Chinese male presented with acute left flank pain and gross hematuria persisting for 4 h. Diagnostic imaging revealed a left ureteral stone, prompting double-J stent placement at a local hospital. Despite intervention, hematuria worsened, necessitating abdominal CT. Imaging identified proximal migration of the left double-J stent into the inferior vena cava, with no evidence of vascular injury. Due to concerns regarding inadequate drainage and infection risk, conservative management without catheter clamping was initiated prior to referral. Definitive treatment involved ureteroscopic stent removal under direct visualization at our institution, resulting in rapid symptom resolution. Conclusion This case emphasizes three critical clinical insights: (1) Persistent postoperative hematuria warrants consideration of iatrogenic causes, particularly following urologic device placement. (2) Imaging modalities, especially CT, are indispensable for detecting atypical stent migration. (3) Comprehensive history-taking must include prior urologic interventions to guide differential diagnosis. While double-J stent migration into major vessels remains exceptionally rare, its recognition prevents delayed management of potentially life-threatening complications. Clinicians should maintain heightened vigilance for device-related hematuria in patients with refractory symptoms post-procedurally, ensuring prompt imaging evaluation and multidisciplinary intervention when indicated.

Qi, Wenqi↗
DOE OSTI2021

Reconstructing magnetic deflections from sets of proton images using differential evolution

Proton imaging is a powerful technique for imaging electromagnetic fields within an experimental volume, in which spatial variations in proton fluence are a result of deflections to proton trajectories due to interaction with the fields. When deflections are large, proton trajectories can overlap, and this nonlinearity creates regions of greatly increased proton fluence on the image, known as caustics. The formation of caustics has been a persistent barrier to reconstructing the underlying fields from proton images. We have developed a new method for reconstructing the path-integrated magnetic fields, which begins to address the problem posed by caustics. Our method uses multiple proton images of the same object, each image at a different energy, to fill in the information gaps and provide some uniqueness when reconstructing caustic features. We use a differential evolution algorithm to iteratively estimate the underlying deflection function, which accurately reproduces the observed proton fluence at multiple proton energies simultaneously. We test this reconstruction method using synthetic proton images generated for three different, cylindrically symmetric field geometries at various field amplitudes and levels of proton statistics and present reconstruction results from a set of experimental images. Here, the method we propose requires no assumption of deflection linearity and can reliably solve for fields underlying linear, nonlinear, and caustic proton image features for the selected geometries and is shown to be fairly robust to noise in the input proton intensity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The persistent shadow of the supermassive black hole of M 87. I. Observations, calibration, imaging, and analysis

In April 2019, the Event Horizon Telescope (EHT) Collaboration reported the first-ever event-horizon-scale images of a black hole, resolving the central compact radio source in the giant elliptical galaxy M 87. These images reveal a ring with a southerly brightness distribution and a diameter of ∼42 μas, consistent with the predicted size and shape of a shadow produced by the gravitationally lensed emission around a supermassive black hole. These results were obtained as part of the April 2017 EHT observation campaign, using a global very long baseline interferometric radio array operating at a wavelength of 1.3 mm. Here, we present results based on the second EHT observing campaign, taking place in April 2018 with an improved array, wider frequency coverage, and increased bandwidth. In particular, the additional baselines provided by the Greenland telescope improved the coverage of the array. Multiyear EHT observations provide independent snapshots of the horizon-scale emission, allowing us to confirm the persistence, size, and shape of the black hole shadow, and constrain the intrinsic structural variability of the accretion flow. We have confirmed the presence of an asymmetric ring structure, brighter in the southwest, with a median diameter of 43.3−3.1+1.5 μas. The diameter of the 2018 ring is remarkably consistent with the diameter obtained from the previous 2017 observations. On the other hand, the position angle of the brightness asymmetry in 2018 is shifted by about 30° relative to 2017. The perennial persistence of the ring and its diameter robustly support the interpretation that the ring is formed by lensed emission surrounding a Kerr black hole with a mass ∼6.5 × 109 M⊙. The significant change in the ring brightness asymmetry implies a spin axis that is more consistent with the position angle of the large-scale jet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Comparison of automated chemical-guided segmentation and human annotation of soil organic matter in X-ray microcomputed tomography imaging in contrasted soil types

Soil organic matter (OM) formation and persistence is strongly influenced by the spatial distribution of organic substrates and microscale soil heterogeneity by dictating OM accessibility to microorganisms. However, traditional size and/or density fractionation techniques disrupt aggregate architecture, eliminating spatial information needed to fully understand intra-aggregate OM distribution. To quantify three-dimensional OM spatial distribution and automate segmentation in X-ray microcomputed tomography (µCT) imaging without human annotation bias, we developed an iodine gas vapor (I2) based staining workflow that eliminates labor-intensive manual annotation while maintaining segmentation accuracy, using aggregates from four taxonomically diverse soils (Xerofluvent, Haploxeroll Sphagnofibrist, Palehumult) with an 8-fold range of soil organic carbon. Human annotation of 10 µCT slices by the experienced and inexperienced annotators resulted in variations up to 3% in the Dice similarity coefficient (DSC), reflecting a degree of inherent subjectivity of manual labeling. Such inconsistencies are expected to compound as the number of manually annotated slices increases. Dual-energy µCT imaging at 33.1 keV (below the iodine (I) K-edge) and 33.2 keV (above the I K-edge) was used to resolve aggregate microstructure following I2 staining. The automated image subtraction pipeline identified OM regions by the I Kedge induced brightness increases, achieving DSC values of 0.58–0.83 relative to an experienced annotator. Sensitivity analyses revealed that the reconstruction alpha value—optimized via the open-source tool TomocuPy—and the 3D registration slice count were the primary determinants of accuracy, providing a novel benchmark for dual-energy soil imaging. The pipeline without GPU acceleration achieved 9.6 to 43.2 times faster than manual annotation. Using GPU-accelerated image post-processing and affine transformation matrices, the pipeline successfully segmented OM elements for large-scale datasets (3232×3232 pixel, 2048 slices) within ~5200 s from raw file acquisition to segmented output. The high-throughput approach enables the quantification of OM spatial distribution across diverse and heterogeneous soil.

Soil microbial biomass↗
DOE OSTI2021

Terahertz Nano-Imaging of Electronic Strip Heterogeneity in a Dirac Semimetal

Emerging topological semimetals offer promise of realizing topological electronics enabled by terahertz (THz) current persistent against impurity scattering. Yet most fundamental issues remain on how to image nanoscale conductivity inhomogeneity. Here in this paper we show noninvasive and contactless conductivity mapping at THz-nm limit of electronic heterogeneity and nanostrip junctions in a Dirac material ZrTe 5 . A clear Dirac Fermion density transition, manifested as the exclusive THz conductivity contrast, is quantitatively analyzed and profiled on both sides of the junction. This also allows the determination of variable junction width of ~25–220 nm, depending on the THz conductivity contrast of adjacent strips. The unique THz-nm contrast is absent in mid-infrared nano-imaging measurements since topological semimetals with small Fermi pockets exhibit a better matching of their plasma frequency and scattering rate to the THz spectral region. The first-principles calculations provide two compelling implications: the conductivity nanocontrast can be induced by a small anisotropic strain, even less than 0.5%, due to an extreme strain sensitivity in ZrTe 5 ; A nanoscale topological phase transition is realized across some junctions induced by the strain, between strong topological insulators (TIs) and weak TIs/Dirac semimetals (DSMs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗