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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

In situ TEM observation of calcium silicate hydrate nanostructure at high temperatures

Fire poses a substantial threat to concrete structures because calcium silicate hydrate (C-S-H) is not thermally stable at high temperatures. Herein, in situ TEM at temperatures from 20 to 800 °C was conducted to study the thermal-induced structural changes in C-S-H. We captured C-S-H shrinks at an average rate of 0.02 μm{sup 2}/{sup o}C upon heating with three stages observed, including induction, constant, and rapid periods. Our observation revealed that an 800 nm pore could be healed during pore structure evolution owing to the reconstruction and deformation among C-S-H blocks. The Ca/Si ratio was dropped at higher temperatures because of the leakage of calcium ions from the C-S-H structure to form CaO precipitates. The temperature-driven phase transformation and degradation were also detected using electron diffraction that C-S-H was transformed into metastable calcium silicate minerals above 800 °C. This work provides insights into the nanoscale transformation of C-S-H at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Size Effect of Local Current-Voltage Characteristics of MX 2 Nanoflakes: Local Density of States Reconstruction from Scanning Tunneling Microscopy Experiments

Local current-voltage characteristics for low-dimensional transition-metal dichalcogenides (LDTMD), as well as the reconstruction of their local density of states (LDOS) from scanning tunneling microscopy (STM) experiments, are of fundamental interest and can be useful for advanced applications. Most of the existing models either have limited applicability for complex-shaped LDTMDs (e.g., those based on the Simmons approach) or require solving of an ill-defined integral equation to deconvolute the unknown LDOS (e.g., those based on the Tersoff approach). Using a serial expansion of the Tersoff formulas, we propose a flexible method to reconstruct the LDOS from local current-voltage characteristics measured in STM experiments. We establish a set of key physical parameters, which characterize the tunneling current of a STM-probe–sample contact and the sample LDOS expanded in Gaussian functions. Using a direct variational method coupled with probabilistic analysis, we determine these parameters from the STM experiments for MoS2 nanoflakes with different numbers of layers. The main result is the reconstruction of the LDOS in a relatively wide energy range around the Fermi level, which allows us to gain insight into the local band structure of LDTMDs. The reconstructed LDOS reveal pronounced size effects for the single-layer, two-layer, and three-layer MoS 2 nanoflakes, which we relate to the low dimensionality and strong bending or corrugation of the nanoflakes. We hope that the proposed elaboration of the Tersoff approach, allowing LDOS reconstruction, will be of critical interest for the quantitative description of STM experiments and also of use to better understand the microscopic physical aspects of the surface, strain, and bending contributions to the LDTMDs’ electronic properties.

42 ENGINEERING↗
DOE OSTI2020

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Resolution of Virtual Depth Sectioning from Four-Dimensional Scanning Transmission Electron Microscopy

Abstract One approach to three-dimensional structure determination using the wealth of scattering data in four-dimensional (4D) scanning transmission electron microscopy (STEM) is the parallax method proposed by Ophus et al. (2019. Advanced phase reconstruction methods enabled by 4D scanning transmission electron microscopy, Microsc Microanal25, 10–11), which determines the scattering matrix and uses it to synthesize a virtual depth-sectioning reconstruction of the sample structure. Drawing on an equivalence with a hypothetical confocal imaging mode, we derive contrast transfer and point spread functions for this parallax method applied to weakly scattering objects, showing them identical to earlier depth-sectioning STEM modes when only bright field signal is used, but that improved depth resolution is possible if dark field signal can be used. Through a simulation-based study of doped Si, we show that this depth resolution is preserved for thicker samples, explore the impact of shot noise on the parallax reconstructions, discuss challenges to making use of dark field signal, and identify cases where the interpretation of the parallax reconstruction breaks down.

3D imaging↗
DOE OSTI2025

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗
DOE OSTI2025

A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques

Assessing the fingerprint of a material’s microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ultrasparse View X-ray Computed Tomography for 4D Imaging

X-ray computed tomography (CT) is a noninvasive, nondestructive approach to imaging materials, material systems, and engineered components in two and three dimensions. Acquisition of three-dimensional (3D) images requires the collection of hundreds or thousands of through-thickness X-ray radiographic images from different angles. Such 3D data acquisition strategies commonly involve suboptimal temporal sampling for in situ and operando studies (4D imaging). Herein, we introduce a sparse-view imaging approach, Tomo-NeRF, which is capable of reconstructing high-fidelity 3D images from <10 twodimensional radiographic images. Experimental 2D and 3D X-ray images were used to test the reconstruction capability in two-view, four-view, and six-view scenarios. Tomo-NeRF is capable of reconstructing 3D images with a structural similarity of 0.9971–0.9975 and a voxel-wise accuracy of 81.83–89.59% from 2D experimentally obtained images. Furthermore, the reconstruction accuracy for the experimentally obtained images is less than the synthetic structures. Experimentally obtained images demonstrate a similarity of 0.9973–0.9984 and a voxelwise accuracy of 84.31–95.77%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Transport anomalies in the layered compound BaPt 4 Se 6

We report a layered ternary selenide BaPt 4 Se 6 featuring sesqui-selenide Pt 2 Se 3 layers sandwiched by Ba atoms. The Pt 2 Se 3 layers in this compound can be derived from the Dirac-semimetal PtSe 2 phase with Se vacancies that form a honeycomb structure. This structure results in a Pt (VI) and Pt (II) mixed-valence compound with both PtSe 6 octahedra and PtSe 4 square net coordination configurations. Temperature-dependent electrical transport measurements suggest two distinct anomalies: a resistivity crossover, mimic to the metal-insulator (M-I) transition at ~150 K, and a resistivity plateau at temperatures below 10 K. The resistivity crossover is not associated with any structural, magnetic, or charge order modulated phase transitions. Magnetoresistivity, Hall, and heat capacity measurements concurrently suggest an existing hidden state below 5 K in this system. Angle-resolved photoemission spectroscopy measurements reveal a metallic state and no dramatic reconstruction of the electronic structure up to 200 K.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification of a low-energy metastable 1 T -type phase for monolayer VSe 2

Elucidating the polymorphism of transition metal dichalcogenide layers and the interplay between structure and properties is a key challenge for the application of these materials. We identify a low-energy metastable phase of monolayer VSe 2 and elucidate its magnetic and electronic properties. This structure is distinct from the previously identified charge density wave (CDW) phase. However, while having rather distinct properties it is very close in energy to the CDW phase and is likely to be realized in experiments. Importantly, local bonding instabilities, as characterized by reconstruction of the electronic structure over a wide energy range, are important for this distortion, which includes both V off-centering in the octahedral coordination cages and a partial disproportionation into two distinct types of V. The phase does not have a ferromagnetic ground state. Furthermore, the results show that the physics of 1T–VSe 2 are richer than previously known with an interplay of Fermi surface instabilities and local bonding effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Revealing latent pole and zone line information in atom probe detector maps using crystallographically correlated metrics

Poles and zone lines observed within atom probe field evaporation images are useful for a range of atom probe crystallography studies, including calibration of the reconstruction and crystallographic characterisation of microstructural features such as grain boundaries. However, this information is not always readily apparent. Techniques for plotting crystallographically correlated metrics contained within atom probe data to enhance pole and zone line contrast across the detector space are developed. This includes consideration of the electric field, molecular ions, lattice structure retained within the reconstruction, specific elemental species, the number of pulses between detection events, and the lateral distance between sequential detection events. These approaches are then applied to experimental atom probe tomography datasets on technically pure Al, nanocrystalline Al, highly doped Si, and additively manufactured Inconel 738, Haynes 282, and Ti–6Al–4V. The results facilitate the extension of atom probe crystallography studies to a broader range of crystalline datasets where crystallographic information is not readily apparent from existing methods, as well as a deeper understanding of field evaporation behaviour during an atom probe experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-‘Herringbone,’ Au(110)-(1 × 2)-‘Missing-Row,’ and Au(100)-‘Quasi-Hexagonal’ reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling

We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) technique, via Gaussian Process (GP) methods. Even for weakly informative priors, GP methods allow unambiguous determination of the characteristic length scales of the imaging process both in spatial and frequency domains. We further show that BE data set tends to be oversampled in the spatial domains, with ~30% of original data set sufficient for high-quality reconstruction, potentially enabling faster BE imaging. At the same time, reliable reconstruction along the frequency domain requires the resonance peak to be within the measured band. This behavior suggests the optimal strategy for the BE imaging on unknown samples. Finally, we discuss how GP can be used for automated experimentation in SPM, by combining GP regression with non-rectangular scans.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A measure of active interfaces in supported catalysts for high-temperature reactions

Formulating knowledge of structure-function relationships in heterogeneous catalysis is central to the design of efficient catalysts; yet, the elucidation of dominant reaction sites has remained as a challenge. Here, in this paper, we present a methodology that can be used to visualize metal-gas and metal-oxide-gas interfaces in three dimensions and to quantify their catalytic activity levels. As a case study, CH 4 oxidation occurring in a Pt/CeO 2 system is chosen. By employing thermally robust Pt@CeO 2 model catalysts with size-tunable and monodisperse cores, and gas-permeable shells, we reconstruct a series of structures in 3D via electron tomography and match the information to activity data and theoretical calculations. This strategy reveals that two different interfaces catalyze the CH 4 oxidation and that their contribution to the overall rate changes with the Pt size, temperature, and gas atmosphere. Our results provide an analytic platform on which to explore reaction pathways and mechanisms applicable to multiple reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Valence transition and termination-dependent surface states in the topological Kondo semimetal YbPtBi

Here, the Yb-terminated and Bi-terminated (111) surface electronic structure of topological Kondo semimetal YbPtBi is investigated using both density-functional-theory (DFT) -based calculations and angle-resolved photoemission spectroscopy (ARPES). The cleavage plane is found to be between Yb-layers and Bi-layers in both experiment and theory, and the broken inversion symmetry ensures the Yb-terminated surface does not mix with the Bi-terminated surface. The ARPES results at the Bi-terminated surface are similar to those reported for YPtBi or LuPtBi, and they can be well explained using DFT calculations assuming trivalent Yb atoms. In contrast, at the Yb-terminated surface, a trivalent to divalent transition and reduced hybridization with conduction electrons for the topmost Yb atoms are observed, as a result of reduced bonding with Bi-atoms. In addition, the Fermi arc features induced by the triply degenerate-points, which are missing at the Bi-terminated surface, can be identified at the Yb-terminated surface. Our study demonstrates unambiguously the reconstruction of surface electronic structure due to the valence transition of the lanthanide element in a Kondo lattice system.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Visualizing a viral genome with contrast variation small angle X-ray scattering

Despite the threat to human health posed by some single-stranded RNA viruses, little is understood about their assembly. The goal of this work is to introduce a new tool for watching an RNA genome direct its own packaging and encapsidation by proteins. Contrast variation small-angle X-ray scattering (CV-SAXS) is a powerful tool with the potential to monitor the changing structure of a viral RNA through this assembly process. The proteins, though present, do not contribute to the measured signal. As a first step in assessing the feasibility of viral genome studies, the structure of encapsidated MS2 RNA was exclusively detected with CV-SAXS and compared with a structure derived from asymmetric cryo-EM reconstructions. Additional comparisons with free RNA highlight the significant structural rearrangements induced by capsid proteins and invite the application of time-resolved CV-SAXS to reveal interactions that result in efficient viral assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Revealing the Structure and Dynamics of Self-Generated Electric and Magnetic Fields Near Plasma Stagnation in Laser-Driven Hohlraums

By coupling newly developed triparticle charged particle radiography with radiography reconstruction algorithms and novel reconstruction postprocessing techniques, the spatial structure and time evolution of self-generated electric and magnetic fields in laser-driven vacuum hohlraums have been quantitatively revealed. Through high-fidelity data from a series of experiments, it is shown that late in the hohlraum evolution (after the end of laser drive) these fields are strongly correlated in both space and time, providing evidence that their evolution is primarily dominated by advection with the plasma flow. At these late times, plasma flow velocities inferred from both gross radiography analysis and field reconstructions (and corroborated with Thomson scattering measurements) indicate that the plasma is approaching stagnation near the hohlraum axis. Finally, these experiments provide not only new physical insight into spontaneously generated hohlraum fields, but also provide important spatially and temporally resolved information for future benchmarking of numerical codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Upgrading the Performance and Stability of Lithium, Manganese-Rich Layered Oxide Cathodes with Combined-Formic Acid and Spinel Coating Treatment

We report improving sluggish rate performance and cycling stability of Li, Mn-rich cathode materials (LMR) is of great importance for practical implementation. Here, dual surface modification on LMR particles with formic acid washing and spinel coating improves the electrochemical performance. Dilute formic acid can remove the Li2CO3 surface impurities and selectively reduce Ni while significantly increasing specific surface area by ~32 %, unlocking more electrochemically active surfaces. Spinel coating enhances cycle stability by suppressing detrimental side reactions at electrode-electrolyte interfaces at high voltage. Post-annealing temperature was found to significantly affect the cathode performance. Higher temperature favors diffusion of transition metal (TM)/Li ions of the spinel coating from surface to the bulk, removing the coating by possible reconstruction into the layered structure and thus degrading the performance. The spinel coating also appears to increase Co 3+ segregation on the particle surface. Compared to the original material, the optimized sample demonstrates 47 % higher capacity retention at 3C and retains 89 % of initial capacity after 150 cycles at 0.5C. Besides, the specific energy density of 523 Wh kg -1 can be attained after 150 cycles at 0.5C. Moreover, the post-cycling analysis of modified sample verifies a better structural integrity with less particle cracking. Altogether, this study portrays an alternative strategy to overcome the shortcomings of LMR cathode materials.

25 ENERGY STORAGE↗