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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 253 records · Page 14

Mapping 3D grain and precipitate structure during in situ mechanical testing of open-cell metal foam using micro-computed tomography and high-energy X-ray diffraction microscopy

Open-cell metal foams are ultra-low-density cellular metals with complex hierarchical structures that span bulk, cell, ligament, and sub-ligament scales and give rise to desirable properties such as high strength-to-weight ratio and excellent energy absorption. Although literature suggests that intrinsic material structures at sub-ligament length scales (e.g., grains and precipitates) play an important role in mechanical behavior of open-cell metal foams, there are very few experimental measurements of such structures in three dimensions and for meaningful volumes of foam. This study seeks to map and track the three-dimensional (3D) grain and precipitate structures of an intact volume of open-cell aluminum foam by advancing microstructural characterization techniques that leverage X-ray micro-computed tomography (μCT) and far-field high-energy X-ray diffraction microscopy (FF-HEDM). A 6%-relative-density aluminum foam sample was mechanically tested in compression while μCT and FF-HEDM measurements were collected at interrupted loading states at beamline 1-ID of the Advanced Photon Source. Further, a new scanning strategy and reconstruction algorithm were established to enable characterization of a foam volume with diameter approximately four times wider than the nominal width of the X-ray beam. The result is a set of maps that detail both the 3D grain and precipitate structures throughout the foam volume at successive strain steps. A novel grain tracking procedure was developed to track individual grains within the foam volume by accounting for the large rigid-body motions that individual ligaments can undergo during mechanical loading. The ability to track grains and precipitate structures in three dimensions throughout large bulk deformation of ultra-low-density polycrystalline materials enables new possibilities for validating numerical models and investigating local failure mechanisms. Furthermore, the methods and procedures developed in this study could be applied to other ultra-low-density structures, such as additively manufactured lattices.

36 MATERIALS SCIENCE↗

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. Further, the MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10%. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11%. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

42 ENGINEERING↗

Exploration of two surfaces observed in Weyl semimetal BaMnSb 2

Single crystalline BaMnSb 2 is considered as a 3D Weyl semimetal with the 2D electronic structure containing Dirac cones from the Sb sheet. We report experimental investigation of low-temperature cleaved BaMnSb 2 surfaces using scanning tunneling microscopy/spectroscopy and low energy electron diffraction. By natural cleavage, we find two terminations: one is Ba (above the orthorhombically distorted Sb sheet) and another Sb2 (at the surface of the Sb/Mn/Sb sandwich layer). Both terminations show the 2×1 surface reconstructions, with drastically different morphologies and electronic properties, however. The reconstructed structures, defect types and nature of the electronic structures of the two terminations are extensively studied. The quasiparticle interference (QPI) analysis is conducted at the energy range between -2 V and 2 V, although no interesting states are observed near the Fermi level, the surface-projected electronic band structures strongly depend on the surface termination above 1.6 V. The existence of defects can greatly modify the local density of states to create electronic phase separations on the surface in the order of tens of nm scale. Our observation on the atomic structures of the terminations and the corresponding electronic structures provides critical information towards an understanding of topological properties of BaMnSb 2 .

36 MATERIALS SCIENCE↗

Computed Tomography (CT) Analysis of 3D Printed Lattice Structures

LATTICE structures are increasingly used in product design across different industries, including the Department of Energy (DOE), due to their high strength and lightweight properties. These structures possess qualities such as high stiffness, energy absorption, large surface area, and structural support. To ensure lattice structures' quality and symmetry, it is crucial to have defect-free structures. However, in some cases, traditional non-destructive evaluation methods may not be practical due to encasing lattice structures in material. To analyze the lattice structures' quality, this project will employ CT imaging to gain access to the encased structures and perform a detailed analysis of each section. Three 3D printed complex lattice cubes were created, with two exposed and one encased in material, for this project. The CT X-ray cabinet will be used to scan all three cubes, and the data collected will be reconstructed and evaluated using complex interpretation software. This analysis will allow for a detailed examination of the structure's porosity, inclusions, cracks, wall thickness, and symmetry in each section.

36 MATERIALS SCIENCE↗

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry↗

The use of subchondral bone topography to approximate the center of rotation of the elbow joint in dogs

Abstract Objectives The aim of this study was to compare the approximate center of rotation in normal and diseased elbows in dogs. Study design Cross‐sectional study Sample population Computer tomography scans of nine dogs with unilateral fragmented medial coronoid process (FMCP). Methods A board certified radiologist confirmed that each dog had unilateral FMCP, and a normal contralateral elbow. Digital 3D models of all elbow joints were uploaded into a surgical planning software package. Four axes approximating the center of rotation (COR) of elbow joints were generated using five geometric shapes based on subchondral topography of the humeral condyle radius and ulna. Images showing the locations where axes exited the medial and lateral cortex of the humeral condyle were captured and imported into a second software package, for measurement of distances between exit points and the origin of a system of axes. Results In normal joints 20/27 (74%) axes exited the medial cortex, and 25/27 (93%) axes exited the lateral cortex cranial and distal to the medial and lateral epicondyles, respectively. In diseased joints 22/27 (81%) axes exited medial cortex and 19/27 (70%) axes exited the lateral cortex, caudal and distal to the medial and lateral epicondyles, respectively. Conclusion Based on CT‐ derived geometry, the COR of elbow affected with FMCP was generally more caudal than normal. Clinical significance External landmarks approximating the location of the elbow COR are provided, and while not validated, may assist in planning, creation, and assessment of procedures for FMCP.

Berger, Chen↗

Strangeness-neutral equation of state for QCD with a critical point

We present a strangeness-neutral equation of state for QCD that exhibits critical behavior and matches lattice QCD results for the Taylor-expanded thermodynamic variables up to fourth-order in µ B /T. It is compatible with the SMASH hadronic transport approach and has a range of temperatures and baryonic chemical potentials relevant for phase II of the Beam Energy Scan at RHIC. We provide an updated version of the software BES-EoS, which produces an equation of state for QCD that includes a critical point in the 3D Ising model universality class. This new version also includes isentropic trejectories and the critical contribution to the correlation length. Since heavy-ion collisions have zero global net-strangeness density and a fixed ratio of electric charge to baryon number, the BES-EoS is more suitable to describe this system. Comparison with the previous version of the EoS is thoroughly discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Airy light-sheet Raman imaging

Light-sheet fluorescence microscopy has greatly improved the speed and overall photostability of optically sectioning cellular and multi-cellular specimens. Similar gains have also been conferred by light-sheet Raman imaging; these schemes, however, rely on diffraction limited Gaussian beams that hinder the uniformity and size of the imaging field-of-view, and, as such, the resulting throughput rates. Here, we demonstrate that a digitally scanned Airy beam increases the Raman imaging throughput rates by more than an order of magnitude than conventional diffraction-limited beams. Overall, this, spectrometer-less, approach enabled 3D imaging of microparticles with high contrast and 1 µm axial resolution at 300 msec integration times per plane and orders of magnitude lower irradiation density than coherent Raman imaging schemes. We detail the apparatus and its performance, as well as its compatibility with fluorescence light-sheet and quantitative-phase imaging towards rapid and low phototoxicity multimodal imaging.

47 OTHER INSTRUMENTATION↗

Remote sensing images, DEM, and point clouds associated with “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds”

This data package is associated with the publication “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds” published in Frontiers in Environmental Science, Environmental Informatics and Remote Sensing (Bao et al., 2026; doi: 10.3389/fenvs.2026.1725258). This data package includes the drone photos for a section of Umtanum Creek in Washington, Unted States. The photos were used to reconstruct the 3-dimensional (3D) digital elevation model (DEM) of the riverbed for the investigated stream section. The reconstruction results from four approaches are provided: (1) unoccupied aerial vehicle (UAV, colloquially known as drone) imagery-based Structure-from-Motion (SfM), (2) a machine learning-based 3D reconstruction model, Visual Geometry Grounded Deep Structure from Motion (VGGSfM), (3) Visual Geometry Grounded Transformer for long sequence of images (VGGT-Long), and (4) handheld smartphone LiDAR scanning. The ground truth measurements by tripod-mounted optical level kit and ground control points GPS locations for evaluating the accuracy of the four reconstruction approaches are also provided in this data package. A preliminary version of this data package was published in October 2025 at the time of manuscript submission. It was updated in March 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) 8 folders; (2) the detailed flight configuration html files; (3) field metadata; (4) a readme; (5) a data dictionary; and (6) file-level metadata. The folders “2024_10_18_d01” and “2024_10_18_d02” contain the original drone photos for the two drone flights (d01 and d02) on October 18, 2024. The reconstruction results from each of the approaches are in the folders called “ODM_SfM”, “VGGSfM”, “VGGTLong”, and “LiDAR”. The ground truth measurements are in the folder called “optical_level_kit”. Lastly, results comparing the different approaches are in the folder called “comparisons”. All files are .csv, .html, .jpg, .obj, .txt, and .npy. For information on using the .obj and .npy files, see the readme files within the same folder as the files.

54 ENVIRONMENTAL SCIENCES↗

Automatic Determination of the Weak-Beam Condition in Dark Field X-ray Microscopy

Mechanical properties in crystals are strongly correlated to the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a new tool to image and interpret dislocations within crystals using multidimensional scans. However, the methods required to reconstruct meaningful dislocation information from high-dimensional DFXM scans are still nascent and require significant manual oversight (i.e. supervision). In this work, we present a new relatively unsupervised method that extracts dislocation-specific information (features) from a 3D dataset (x, y, Φ) using Gram-Schmidt orthogonalization to represent the large dataset as an array of 3-component feature vectors for each position, corresponding to the weak-beam conditions and the strong-beam condition. Finally, this method offers key opportunities to significantly reduce dataset size while preserving only the crystallographic information that is important for data reconstruction.

36 MATERIALS SCIENCE↗

Multimodal Nanoscale Mapping of Local Structure and CO 2 Adsorption in Metal–Organic Frameworks

Diamine functionalization of the metal−organic framework Mg 2 (dobpdc) (dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) significantly enhances its selectivity for CO 2 capture from flue gases and air. The structure and CO 2 capacity of such materials are typically assessed using bulk techniques that rely on averaging signal over large ensembles of unit cells, obscuring local heterogeneities, such as variations in CO 2 occupancy across individual nanocrystals. To resolve this limitation, we demonstrate a multimodal, nanoscale characterization of Mg 2 (dobpdc) appended with 1,3-diaminopropane. By employing recently developed characterization techniques at progressively smaller length scales, we uncover insights from correspondingly smaller populations of unit cells. First, we use parallel-beam 3D electron diffraction (3D ED) to identify a prominent expansion in lattice parameters upon desorption of CO 2 , as observed at the level of single nanocrystals. Second, we use convergent-probe 4D scanning transmission electron microscopy (4D-STEM) to quantify associated differences in lattice strain as a function of gas loading and diamine appending. These measurements sample small subvolumes within individual nanocrystals. Finally, we apply infrared scattering scanning near-field optical microscopy (IR s- SNOM) to confirm variable CO 2 chemisorption across adsorption sites at the surface of single nanocrystals. This multimodal, multiscale approach allows us to map heterogeneity within individual nanocrystals. Collectively, these findings emphasize the importance of local, nanoscale characterization of metal−organic frameworks in revealing previously unresolvable features that impact their performance.

Karstens, Sarah L. [University of California, Berk↗

A Novel Experimental Approach to Understand the Transport of Nanodrugs

Nanoparticle-based drugs offer attractive advantages like targeted delivery to the diseased site and size and shape-controlled properties. Therefore, understanding the particulate flow of the nanodrugs is important for effective delivery, accurate prediction of required dosage, and developing efficient drug delivery platforms for nanodrugs. In this study, the transport of nanodrugs including flow velocity and deposition is investigated using three model metal oxide nanodrugs of different sizes including iron oxide, zinc oxide, and combined Cu-Zn-Fe oxide synthesized via a modified polyol approach. The hydrodynamic size, size, morphology, chemical composition, crystal phase, and surface functional groups of the water-soluble nanodrugs were characterized via dynamic light scattering, transmission electron microscopy, scanning electron microscopy-energy dispersive X-ray, X-ray diffraction, and fourier transform infrared spectroscopy, respectively. Two different biomimetic flow channels with customized surfaces are developed via 3D printing to experimentally monitor the velocity and deposition of the different nanodrugs. A diffusion dominated mechanism of flow is seen in size ranges 92 nm to 110 nm of the nanodrugs, from the experimental velocity and mass loss profiles. The flow velocity analysis also shows that the transport of nanodrugs is controlled by sedimentation processes in the larger size ranges of 110–302 nm. However, the combined overview from experimental mass loss and velocity trends indicates presence of both diffusive and sedimentation forces in the 110–302 nm size ranges. It is also discovered that the nanodrugs with higher positive surface charges are transported faster through the two test channels, which also leads to lower deposition of these nanodrugs on the walls of the flow channels. The results from this study will be valuable in realizing reliable and cost-effective in vitro experimental approaches that can support in vivo methods to predict the flow of new nanodrugs.

36 MATERIALS SCIENCE↗

In-situ digital image correlation and thermal monitoring in directed energy deposition additive manufacturing

As in welding, directed energy deposition (DED) additive manufacturing (AM) generates complex residual stresses and distortions commensurate with the complexity of the scan pattern used for deposition. To date, measuring DED distortions on complex geometries has only been achieved post process, discarding the complex thermomechanical history that leads to that final material state. In this work, surround stereo digital image correlation (DIC) is used to 3D map surfaces and strain tensors in-situ in a powder-blown laser DED system. Infrared thermography is then projected onto these surfaces to record the full thermomechanical history of printed parts. DIC presents a unique challenge to DED AM, as no part exists at the beginning of deposition, which (a) prevents application of an appropriate speckle pattern and (b) denies the user a zero strain reference frame. Solutions to these problems are proposed and their limitations explored herein. In sum, this work presents a relatively low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies that was previously unobtainable.

42 ENGINEERING↗

Unraveling Impurity-Dependent Morphological and Chemical Evolution of Ni–20Cr Alloy in Eutectic LiCl–KCl Molten Salt

Understanding the interfacial evolution of alloys in molten salt with different amounts of water (H 2 O) and oxygen (O 2 ) impurities is significant for applications in many fields, including concentrated solar power, molten salt reactors, and applications in pyrochemical reprocessing and electrorefining. Additionally, the impurity-driven corrosion mechanisms that lead to various morphological and chemical evolution characteristics at the interfaces of structural alloys and molten salts are not fully understood. In the present work, the three-dimensional (3D) morphological evolution of Ni-20Cr microwires in LiCl-KCl was studied at 500 °C under different moisture and oxygen conditions using in situ synchrotron transmission X-ray microscopy (TXM) and scanning transmission electron microscopy (STEM) techniques. No significant morphological changes were observed in Ni-20Cr microwires under vacuum conditions. However, the wires exhibited distinct morphological evolutions when exposed to molten salt containing H 2 O alone, as well as when both H 2 O and O 2 were present. Furthermore, Cr 2 O 3 precipitates were observed in the molten salt during corrosion with only H 2 O present, while Cr 6+ species were identified in the salt when O 2 was added. Further, these findings are crucial for understanding the corrosion mechanisms of molten salt with different amounts of H 2 O and O 2 contamination, providing insights for developing corrosion mitigation methods and improving the stability of containment alloys in molten salt applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon nanospike coated nanoelectrodes for measurements of neurotransmitters

Here, carbon nanoelectrodes enable the detection of neurotransmitters at the level of single cells, vesicles, synapses and small brain structures. Previously, the etching of carbon fibers and 3D printing based on direct laser writing have been used to fabricate carbon nanoelectrodes, but these methods lack the ability of mass manufacturing. In this paper, we mass fabricate carbon nanoelectrodes by growing carbon nanospikes (CNSs) on metal wires. CNSs have a short, dense and defect-rich surface that produces remarkable electrochemical properties, and they can be mass fabricated on almost any substrate without using catalysts. Tungsten wires and niobium wires were electrochemically etched in batch to form sub micrometer sized tips, and a layer of CNSs was grown on the metal wires using plasma-enhanced chemical vapor deposition (PE-CVD). The thickness of the CNS layer was controlled by the deposition time, and a thin layer of CNSs can effectively cover the entire metal surface while maintaining the tip size within the sub micrometer scale. The etched tungsten wires produced tapered conical nanotips, while the etched niobium wires were long and thin. Both showed excellent sensitivity for the detection of outer sphere ruthenium hexamine and the inner sphere test compound ferricyanide. The CNS nanosensors were used for the measurement of dopamine, serotonin, ascorbic acid and DOPAC with fast-scan cyclic voltammetry. The CNS nanoelectrodes had a large surface area and numerous defect sites, which improved the sensitivity, electron transfer kinetics and adsorption. Finally, the CNS nanoelectrodes were compared with other nanoelectrode fabrication methods, including flame etching, 3D printing, and nanopipettes, which are slower to make and more difficult for mass fabrication. Thus, CNS nanoelectrodes are a promising strategy for the mass fabrication of nanoelectrode sensors for neurotransmitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando X-ray imaging reveals size-dependent evolution of cobalt oxide thermochemical material during thermal redox cycles

Multivalent metal oxides are promising thermochemical materials (TCMs) for energy storage and conversion owing to their high energy density, air compatibility, and high-temperature stability. Co 3 O 4 serves as a model system for examining particle-size- and structure-dependent redox behavior. While particle size and porosity are known to affect performance, their interplay and the kinetics of pore formation during cycling remain unclear. Here we show the chemical and 3D morphological evolution of Co 3 O 4 micro- and nanoparticles during redox cycles at 800–900 °C using thermal analysis, in-situ synchrotron transmission X-ray microscopy (TXM), and scanning electron microscopy. Thermal analysis shows that nanoparticles re-oxidize more rapidly than microparticles at 800 °C. In-situ nanotomography and chemical imaging reveals that nanoparticles undergo redox conversion without forming internal pores, whereas microparticles develop isolated porosity during reduction. These pores persist through re-oxidation, correlating to a lower conversion rate in subsequent cycles. Our results demonstrate distinct degradation kinetics in Co 3 O 4 micro- and nanoparticles, underscoring the critical role of particle size and porosity in redox performance and informing strategies to enhance the long-term efficiency of metal oxide TCMs.

25 ENERGY STORAGE↗

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗