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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

In situ imaging of three dimensional freeze printing process using rapid x-ray synchrotron radiography

Three dimensional freeze printing (3DFP) combines the advantages of freeze casting and additive manufacturing to fabricate multifunctional aerogels. Freeze casting is a cost-effective, efficient, and versatile method capable of fabricating micro-scale porous structures inside the aerogels for many different applications. The 3DFP provided the capability of fabricating highly customized geometries with controlled microporous structures as well. However, there are still many unexplained phenomena and features because of the complexity of post-processes and indirect observation methods. This study demonstrates the design and construction of the in situ imaging systems, which use the x-ray synchrotron radiography to observe freeze casting and 3DFP processes. With the advantages provided by the in situ x-ray imaging techniques, the ice crystal growth with its unique lamellar structures can be observed during the freeze casting process. Here, the movement of freeze front, material deposition, and growth of ice crystals can also be visualized during the inkjet-based 3DFP process.

3D printing↗
DOE OSTI2025

Online thermal profile prediction for large format additive manufacturing: A hybrid CNN-LSTM based approach

Large format additive manufacturing (LFAM) is an advanced 3D printing technique that efficiently fabricates large-scale components through a layer-by-layer extrusion and deposition process. Accurate surface layer temperature monitoring is essential to prevent manufacturing failures and ensure final product quality. Traditional physics-based offline approaches for simulating thermal behavior are often inefficient and complex, posing challenges on real-time, in-situ monitoring. Here, to address this, we propose a data-driven hybrid CNN-LSTM model to predict sequential thermal images of arbitrary length using real-time infrared thermal imaging. In this approach, a Convolutional Neural Networks (CNN) is trained offline to capture spatial features, reduce dimensional complexity, and enhance time efficiency, while a stacked Long Short-Term Memory (LSTM) is applied online to capture temporal information for improved prediction of future thermal behavior in subsequent printing layers. Model performance is evaluated using MSE, SSIM, and PSNR metrics and is benchmarked against stacked LSTM and convolutional LSTM models, demonstrating superior accuracy and applicability. Additionally, to mitigate noise from moving extruders and gantry backgrounds in thermal images, a fine-tuned semantic segmentation model is implemented offline to extract printing geometry, enabling precise temperature tracking along the tool path for further thermal analysis. The frameworks developed in this study significantly advance temperature monitoring, thermal analysis, and in-situ manufacturing control for LFAM, bridging the gap between theoretical modeling and practical application.

Geometry extraction↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2024

DESI Massive Poststarburst Galaxies at z ~ 1.2 Have Compact Structures and Dense Cores

Poststarburst galaxies (PSBs) are young quiescent galaxies that have recently experienced a rapid decrease in star formation, allowing us to probe the fast-quenching period of galaxy evolution. In this work, we obtained Hubble Space Telescope (HST)/WFC3 F110W imaging to measure the sizes of 171 massive (log(M $\ast$ /M ⊙ ) ~ 11) spectroscopically identified PSBs at 1 < z 1.3 selected from the DESI Survey Validation luminous red galaxy sample. This statistical sample constitutes an order of magnitude increase from the ~20 PSBs with space-based imaging and deep spectroscopy. We perform structural fitting of the target galaxies with pysersic and compare them to quiescent and star-forming galaxies in the 3D-HST survey. We find that these PSBs are more compact than the general population of quiescent galaxies, lying systematically ~0.1 dex below the established size–mass relation. However, their central surface mass densities are similar to those of their quiescent counterparts (log(Σ 1kpc /(M ⊙ kpc -2 ))~10.1). These findings are easily reconciled by later ex situ growth via minor mergers or a slight progenitor bias. These PSBs are round in projection (b/a median ~ 0.8), suggesting that they are primarily spheroids, not disks, in 3D. We find no correlation between the time since quenching and light-weighted PSB sizes or central densities. This disfavors apparent structural growth due to the fading of centralized starbursts in this galaxy population. Instead, we posit that the fast quenching of massive galaxies at this epoch occurs preferentially in galaxies with preexisting compact structures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Fabrication of a novel 3D-printed perfusion bioreactor for complex cell culture models

We introduce a novel fabrication method for developing a 3D-printed perfusion bioreactor (3D-PBR) to facilitate the in situ growth and differentiation of human bone marrow (BM)-derived mesenchymal stem cells (MSCs) while enabling coculture with vascular cells. To recapitulate human physiology, in vitro platforms must incorporate several key features of their native target organ. This often entails a supportive 3D architecture for growing and differentiating multiple human cell types in situ under perfusion. Other essential characteristics include reproducibility, ease of customization, and biocompatibility. Our 3D-PBR combines these features and was fabricated using a biocompatible resin-based polymer, which was 3D-printed, followed by the addition of a permeable membrane to create a coculture microenvironment. MSCs were encapsulated in a collagen-fibrin gel alongside human endothelium within the 3D-PBR. The physical cues that our 3D-PBR provided facilitated the differentiation of MSCs into specific lineages, such as adipocytes and osteoblasts. Immunohistochemistry images demonstrated that cells grown in the 3D-PBR exhibited more physiologically relevant BM perivascular niche markers compared to static culture models. Our method utilizes emerging 3D printing techniques and alternative materials, departing from traditional PDMS-based soft lithography. These advancements in fabrication further enhance in vitro platforms for diverse cell culture models and vascular permeability assays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Imaging Light‐Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Abstract In recent years, halide perovskite materials have been used to make high‐performance solar cells and light‐emitting devices. However, material defects still limit device performance and stability. Here, synchrotron‐based Bragg coherent diffraction imaging is used to visualize nanoscale strain fields, such as those local to defects, in halide perovskite microcrystals. Significant strain heterogeneity within MAPbBr 3 (MA = CH 3 NH 3 + ) crystals is found in spite of their high optoelectronic quality, and both 〈100〉 and 〈110〉 edge dislocations are identified through analysis of their local strain fields. By imaging these defects and strain fields in situ under continuous illumination, dramatic light‐induced dislocation migration across hundreds of nanometers is uncovered. Further, by selectively studying crystals that are damaged by the X‐ray beam, large dislocation densities and increased nanoscale strains are correlated with material degradation and substantially altered optoelectronic properties assessed using photoluminescence microscopy measurements. These results demonstrate the dynamic nature of extended defects and strain in halide perovskites, which will have important consequences for device performance and operational stability.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Defect and structural evolution under high-energy ion irradiation informs battery materials design for extreme environments

Understanding defect evolution and structural transformations constitutes a prominent research frontier for ultimately controlling the electrochemical properties of advanced battery materials. Herein, for the first time, we utilize in situ high-energy Kr ion irradiation with transmission electron microscopy to monitor how defects and microstructures evolve in Na- and Li-layered cathodes with 3d transition metals. Our experimental and theoretical analyses reveal that Li-layered cathodes are more resistant to radiation-induced structural transformations, such as amorphization than Na-layered cathodes. The underlying mechanism is the facile formation of Li-transition metal antisite defects in Li-layered cathodes. The quantitative mathematical analysis of the dynamic bright-field imaging shows that defect clusters preferentially align along the Na/Li ion diffusion channels ( a-b planes), which is likely governed by the formation of dislocation loops. Our study provides critical insights into designing battery materials for extreme irradiation environments and understanding fundamental defect dynamics in layered oxides.

25 ENERGY STORAGE↗
DOE OSTI2020

"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components

Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.

3D printing, Additive Manufacturing, polymer, sint↗
DOE OSTI2020

Feature‐shared adaptive‐boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images

Purpose In clinical practice, invasiveness is an important reference indicator for differentiating the malignant degree of subsolid pulmonary nodules. These nodules can be classified as atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). The automatic determination of a nodule's invasiveness based on chest CT scans can guide treatment planning. However, it is challenging, owing to the insufficiency of training data and their interclass similarity and intraclass variation. To address these challenges, we propose a two‐stage deep learning strategy for this task: prior‐feature learning followed by adaptive‐boost deep learning. Methods The adaptive‐boost deep learning is proposed to train a strong classifier for invasiveness classification of subsolid nodules in chest CT images, using multiple 3D convolutional neural network (CNN)‐based weak classifiers. Because ensembles of multiple deep 3D CNN models have a huge number of parameters and require large computing resources along with more training and testing time, the prior‐feature learning is proposed to reduce the computations by sharing the CNN layers between all weak classifiers. Using this strategy, all weak classifiers can be integrated into a single network. Results Tenfold cross validation of binary classification was conducted on a total of 1357 nodules, including 765 noninvasive (AAH and AIS) and 592 invasive nodules (MIA and IAC). Ablation experimental results indicated that the proposed binary classifier achieved an accuracy of with an AUC of 81.3 . These results are superior compared to those achieved by three experienced chest imaging specialists who achieved an accuracy of , , and , respectively. About 200 additional nodules were also collected. These nodules covered 50 cases for each category (AAH, AIS, MIA, and IAC, respectively). Both binary and multiple classifications were performed on these data and the results demonstrated that the proposed method definitely achieves better performance than the performance achieved by nonensemble deep learning methods. Conclusions It can be concluded that the proposed adaptive‐boost deep learning can significantly improve the performance of invasiveness classification of pulmonary subsolid nodules in CT images, while the prior‐feature learning can significantly reduce the total size of deep models. The promising results on clinical data show that the trained models can be used as an effective lung cancer screening tool in hospitals. Moreover, the proposed strategy can be easily extended to other similar classification tasks in 3D medical images.

Wang, Jun↗
DOE OSTI2020

In situ/operando synchrotron x-ray studies of metal additive manufacturing

Additive manufacturing (AM) comprises a group of transformative technologies that are likely to revolutionize manufacturing. In particular, laser-based metal AM techniques can not only fabricate parts with extreme complexity, but also provide innovative means for designing and processing new metallic systems. However, there are still several technical barriers that constrain metal AM. Overcoming these barriers requires a better understanding of the physics underlying the complex and dynamic laser–metal interaction at the heart of many AM processes. Furthermore, this article briefly describes the state of the art of in situ/operando synchrotron x-ray imaging and diffraction for studying metal AM, mostly the laser powder-bed fusion process. It highlights the immediate impact of operando synchrotron studies on the advancement of AM technologies, and presents future research challenges and opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In Situ Strain Evolution on Pt Nanoparticles during Hydrogen Peroxide Decomposition

Fundamental understanding of structural changes during catalytic reactions is crucial to understanding the underlying mechanisms and optimizing efficiencies. Surface energy and related catalytic mechanisms are widely studied. However, the catalyst lattice deformation induced by catalytic processes is not well understood. Here, we study the strain in an individual platinum (Pt) nanoparticle (NP) using Bragg coherent diffraction imaging under in situ oxidation and reduction reactions. When Pt NPs are exposed to H 2 O 2 , a typical oxidizer and an intermediate during the oxygen reduction reaction process, alternating overall strain distribution near the surface and inside the NP is observed at the (111) Bragg reflection. In contrast, relatively insignificant changes appear in the (200) reflection. Density functional theory calculations are employed to rationalize the anisotropic lattice strain in terms of induced stress by H 2 O 2 adsorption and decomposition on the Pt NP surface. Our study provides deeper insight into the activity-structure relationship in this system.

3D imaging↗
DOE OSTI2021

Operando 3D imaging of defects dynamics of twinned-nanocrystal during catalysis

Using operando Bragg coherent x-ray diffraction imaging, we visualised three-dimensionally a single twinned-gold nanocrystal during the CO oxidation reaction. We describe the defect dynamics process occurring under operating conditions and indicate the correlation between the nucleation of highly strained regions at the surface of the nanocrystal and its catalytic activity. Understanding the twinning deformation mechanism sheds light on the creation of active sites, and could well contribute to the understanding of the catalytic behaviour of other catalysts. Furthermore, with the start-up of 4th generation synchrotron sources, we anticipate that coherent hard x-ray diffraction imaging techniques will play a major role in imaging in situ chemical processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

In-situ X-ray scattering study of isotactic polypropylene/graphene nanocomposites under shear during fused deposition modeling 3D printing

Complementary techniques were applied to characterize the structure property relationships of FDM printed isotactic polypropylene/graphene nanocomposites. Raman spectroscopy indicated that graphene was mostly exfoliated during the nozzle extrusion process. Rheological measurements of the viscosity indicated that the presence of graphene induced shear thinning during extrusion. Azimuthal scans of wide angle x-ray scattering indicate correlated thermal fluctuations of the graphene platelets which stops abruptly at the onset of transcrystallization, or templating of the iPP chains on the graphene. X-ray microbeam SAXS analysis show the formation of ‘shish-kebab’ structures at the core of the unfilled filaments, where the ‘kebab’ component vanishes at the fiber-fiber interface enabling interdiffusion. Weak lamellar structure, and a corresponding decrease in the storage modulus are observed with the addition of 5% graphene. The lamellar structure disappears entirely with the addition of 10% graphene, while the storage modulus is decreased by nearly 50%. Thermal imaging of heat flux dissipation across molded and printed samples shows no orientational effects in pure iPP despite differences in crystal structure. Thermal conductivity increases dramatically in the samples with 10% graphene, and strong orientational effects are observed where the thermal coefficients differ by 180% between samples printed parallel or perpendicular to the heat flux.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Real-time visualization of particle evolution during reactive flux-assisted processing of aluminum melts

Here, a multi-modal, multi-scale correlative tomography investigation of Al-TiC metal matrix composites processed via flux-assisted reaction synthesis is reported. Synchrotron X-ray microradiography is utilized to visualize the reaction and particle evolution in real-time. Changes in particle diameter and areal number density suggest that the process is nucleation- rather than growth-dominated. At 950 °C, the bulk of the reaction takes place in a relatively short time span of less than 600 s. The microstructure is imaged at higher resolution in 2D (scanning electron microscopy) and 3D (synchrotron X-ray nanotomography), revealing the formation of carbide particles with a hexagonal platelet morphology. We propose that the morphology arises due to the incorporation of Si impurities during the experiment. It is expected that the correlative tomography workflow and analysis may guide future metal matrix composite (MMC) processing strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CO 2 /Brine/Rock Interactions in the Cedar Keys-Lawson Formation

It has been reported that among the various geologic storage options, deep saline aquifers have the largest estimated capacity for CO 2 storage. Obtaining knowledge of possible artificially geochemically induced changes to the permeability and porosity of host CO 2 storage deposits will enable us to gain insight on long-term reservoir behavior under CO 2 storage conditions. An experimental study of the interaction of CO 2 /brine/rock on saline formations was conducted in a static system under CO 2 storage conditions. Chemical interactions in the Cedar Keys-Lawson Formation carbonate during exposure to CO 2 and brine under sequestration conditions were studied. Samples were exposed to the simulated in-situ reaction conditions for one and six months. The samples were exposed to a model brine at 55 °C and CO 2 pressure of 23.8 MPa (3,500 psig). Computed tomography (CT), x-ray diffraction (XRD), scanning electron microscopy (SEM)-energy dispersive x-ray spectroscopy (EDS), brine composition, core porosity, and core permeability analyses were conducted prior to and after the exposure experiments. Preliminary permeability measurements obtained from the core samples showed changes after they were exposed to CO 2 -saturated brine for one and six months. This observation suggests that mineral dissolution and mineral precipitation could occur in the host deposit altering its characteristics for CO 2 storage over time. The 3D images of the pore space clearly illustrate the degree of dissolution that occurred during exposure. It is noted that the dissolution that occurred during the six-month exposure could have enhanced the connectivity between voids. This may contribute the increase of permeability after the CO 2 /brine exposure. In addition, the primary minerals comprising the core are dolomite and gypsum. Both minerals could dissolve in the CO 2 /brine environment resulting in the increase of permeability after the six-month exposure.

58 GEOSCIENCES↗
DOE OSTI2023

Facile hermetic TEM grid preparation for molecular imaging of hydrated biological samples at room temperature

Abstract Although structures of vitrified supramolecular complexes have been determined at near-atomic resolution, elucidating in situ molecular structure in living cells remains a challenge. Here, we report a straightforward liquid cell technique, originally developed for real-time visualization of dynamics at a liquid-gas interface using transmission electron microscopy, to image wet biological samples. Due to the scattering effects from the liquid phase, the micrographs display an amplitude contrast comparable to that observed in negatively stained samples. We succeed in resolving subunits within the protein complex GroEL imaged in a buffer solution at room temperature. Additionally, we capture various stages of virus cell entry, a process for which only sparse structural data exists due to their transient nature. To scrutinize the morphological details further, we used individual particle electron tomography for 3D reconstruction of each virus. These findings showcase this approach potential as an efficient, cost-effective complement to other microscopy technique in addressing biological questions at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comparison and calibration of dose delivered by 137 Cs and x-ray irradiators in mice

Objective. The Office of Radiological Security, U.S. Department of Energy's National Nuclear Security Administration, is implementing a radiological risk reduction program which seeks to minimize or eliminate the use of high activity radiological sources, including 137 Cs, by replacing them with non-radioisotopic technologies, such as x-ray irradiators. The main goal of this paper is to evaluate the equivalence of the dose delivered by gamma- and x-ray irradiators in mice using experimental measurements and Monte Carlo simulations. We also propose a novel biophantom as an in situ dose calibration method. Approach. We irradiated mouse carcasses and 3D-printed mouse biophantoms in a 137 Cs irradiator (Mark I-68) and an x-ray irradiator (X-Rad320) at three voltages (160 kVp, 225 kVp and 320 kVp) and measured the delivered radiation dose. A Geant4-based Monte Carlo model was developed and validated to provide a comprehensive picture of gamma- and x-ray irradiation in mice. Main Results. Our Monte Carlo model predicts a uniform dose delivered in soft-tissue for all the explored irradiation programs and in agreement with the absolute dose measurements. Our Monte Carlo model shows an energy-dependent difference between dose in bone and in soft tissue that decreases as photon energy increases. Dose rate depends on irradiator and photon energy. We observed a deviation of the measured dose from the target value of up to –9% for the Mark I-68, and up to 35% for the X-Rad320. The dose measured in the 3D-printed phantoms are equivalent to that in the carcasses within 6% uncertainty. Significance. Our results suggest that 320 kVp irradiation is a good candidate to substitute 137 Cs irradiation barring a few caveats. There is a significant difference between measured and targeted doses for x-ray irradiation that suggests a strong need for in situ calibration, which can be achieved with 3D-printed mouse biophantoms. A dose correction is necessary for bone doses, which can be provided by a Monte Carlo calculation. Lastly, the biological implications of the differences in dose rates and dose per photon for the different irradiation methods should be carefully assessed for each small-animal irradiation experiment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗