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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Processing of tungsten through electron beam melting

Additive manufacturing (AM) presents a new design paradigm for the manufacture of engineering materials through the layer-by-layer approach combined with welding theory. In the instance of difficult to process materials such as tungsten and other refractory metals, AM offers an opportunity for radical redesign of critical components for next-generation energy technologies including fusion. In this work, electron beam powder bed fusion (EB-PBF) is applied to process pure tungsten to study the influence of process parameters on the defect density of the material. Here, an in-situ image analysis algorithm is applied to pure tungsten for the first time, and is used to visualize the defect structure in AM tungsten. Finally, a cracking mechanism for AM tungsten is proposed, and suggestions for suppression of cracks in pure tungsten are offered.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of Li metal addition on corrosion control of Hastelloy N and stainless steel 316H in molten LiF-NaF-KF

Molten fluoride salts are used in various energy harvesting applications such as solar collectors and molten salt nuclear reactors (MSRs). Thermodynamically driven selective dissolution of alloying elements due to impurities present within the fluoride salts have been identified to be the main corrosion mechanism for structural alloys in molten fluoride salts. Impurities in these salts, during salt preparation as well as during operation, can be difficult to control. One way to prevent the selective dissolution of active alloying elements is to make the molten salt reducing by either purifying it to remove impurities or to add some reactive metal that will react with the impurities and make the salt reducing. Here this study is focused on the corrosion behaviour of Hastelloy N and 316H stainless steel in molten LiF-NaF-KF eutectic mixture (FLiNaK) at 700°C and how this behaviour changes with the addition of Li metal as a reducing impurity. Our results indicate that the active metal addition like Li can be very effective in controlling the redox behaviour of salt, which in-turn can mitigate corrosion. Even the addition of small quantities of Li metal can mitigate the selective dissolution of active alloying elements for the tested structural materials in FLiNaK. Our results also suggest that the presence of excess amounts of Li, above the minimum concentration required to react with the impurities in FLiNaK, does not have any detrimental effect in terms of formation of new intermetallic phases at the surface of the selected alloys under tested conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterization of radiation damage in 3D printed SiC

The SiC fuel matrix for advanced gas-cooled high temperature reactors as part of the Transformational Challenge Reactor program serves as the fuel particle container structure, a barrier to fission gas release, and a heat transfer medium. Its performance is particularly important because the fuel matrix must demonstrate good structural stability and thermal behaviors. An additive manufacturing methodology combining a binder jet 3D printing process with chemical vapor infiltration (CVI) for the production of SiC was recently developed. In this study, post irradiation examination by transmission electron microscopy shows that defect accumulation within the printed particles is very similar to other forms of high-purity SiC. However, damage accumulation was not directly observed in the CVI matrix because black spot damage and dislocation loops are difficult to image within the nanoscale highly faulted CVI matrix and because interstitial defects may rapidly annihilate at the stacking faults. Therefore, electron energy loss spectroscopy (EELS) analysis was used to analyze defect swelling in both the printed particles and the CVI matrix. The EELS analysis helped reveal that the radiation-induced swelling in the CVI matrix is similar to that of the printed SiC particles. This work shows that 3D printed SiC has behavior that is comparable to SiC processed by other means and that 3D printing could serve as a suitable processing technique for high-purity SiC for nuclear applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal-shock experiments for separate-effects validation of UO 2 fuel fracture models

Because of the important role that fracture plays in the behavior of ceramic UO2 fuel in a nuclear reactor environment, fracture models are a major component of fuel performance codes. As with any aspect of fuel performance, it is crucial to validate these fracture models against experimental data; however, obtaining well-controlled data for conditions representative of a reactor environment is difficult. Quenching is proposed here as a relatively simple approach for using a laboratory environment to achieve conditions that approximate those of a reactor environment. In this paper, an experimental apparatus containing a single instrumented fuel pellet in a sealed section of copper tubing is developed. It is then applied to a series of seven experiments in which the apparatus is first heated to a high temperature (580-680°C) by immersion in a molten salt bath, then quenched in a cold bath (-10-4 °C). Development of these experiments was guided by numerical simulations, and post-test simulations were performed to aid in understanding the experimental behavior and assessing the accuracy of the predictions of fracture initiation and propagation. In addition, similar experiments were performed on solid copper rods to provide temperature-dependent heat transfer coefficients for use in simulations of these experiments. Here, this study demonstrates that quenching is a viable approach for generating thermal gradients representative of those in prototypical light-water reactor conditions at powers of about 5–10 kW/m. Fracture is expected to begin at these power levels, and moderate amounts of radial and axial cracking was observed in these quenching tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Possible impacts of Mo chemical banding and second phase impurities on the irradiation behavior of monolithic U-10Mo fuels

This study investigated the microstructural behavior of both full-size and mini-size monolithic U-10Mo fuel plates irradiated to high burnup with a focus on the evolution of the second phase impurities in monolithic U-Mo using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and wavelength dispersive spectroscopy (WDS). Key indicators of possible mechanical and thermal compromise include cracks, large fission gas porosity, and interconnection of fission gas pores. For the fission densities evaluated in this work (3.5 × 10 21 fissions/cm 3 -5.1 × 10 21 fissions/cm 3 ), fine porosity can develop along the UC phase boundary; however, the size of the fission gas pores is no more than those observed in the U-Mo fuel phase. Further, other inclusions such as Si-rich second-phase impurities found in the as-fabricated microstructure were difficult to resolve post-irradiation because they can become overshadowed by porosity development in the fuel phase. Additionally, the presence of a Fe-rich sublayer formed in the Zr diffusion layer during fabrication remained enriched in the Zr layer in the irradiated U-10Mo microstructures near the U-Mo/Zr interface; however, based on the burnup assessed in this study the identified impurities did not appear to contribute to notable microstructural degradation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Molybdenum and Tungsten isotope compositions of UO 2 fuel pellets: Implications for isotopically enriched taggants

The addition of isotopically enriched taggants to material at the front end of the nuclear fuel cycle could be a powerful tool used to assist law enforcement authorities should material outside of regulatory control be found. Two potential candidates for this purpose are molybdenum (Mo) and tungsten (W) as both elements have five or more stable isotopes and are trace elements contained within nuclear fuel. So there is a concern that Mo and W could undergo isotope fractionation during processes like uranium enrichment and to date, it is unknown if nuclear fuels have natural Mo and W isotope compositions. If Mo and W isotopic variability is present in nuclear fuels, this would hinder the use of these elements as isotopic taggants because it would be difficult to discern the original taggant isotope composition with high confidence. Therefore, a set of 16 low enriched uranium (LEU) fuel pellets from US commercial producers was analyzed using multi collector-inductively coupled plasma mass spectrometry (MC-ICPMS) to determine Mo and W isotope compositions (i.e., 94 Mo/ 92 Mo, 95 Mo/ 92 Mo, 96 Mo/ 92 Mo, 97 Mo/ 92 Mo, 98 Mo/ 92 Mo, 183 W/ 182 W, 184 W/ 182 W, and 186 W/ 182 W). Relative to terrestrial standards, LEU fuel pellets have variable Mo and W isotope compositions, thereby complicating the use of these elements as isotopically enriched taggants. As such, this work demonstrates that the isotope composition of any potential taggant must be well characterized in the base nuclear fuel prior to any taggant addition. Furthermore, these results suggest that Mo and W are not ideal candidates for isotopically enriched taggants.

58 GEOSCIENCES↗
DOE OSTI2024

Effect of heat treatment on the microstructure of medium burn-up U-Mo monolithic fuel foils

Using scanning electron microscopy (SEM), this study evaluates the microstructure evolution of U-Mo fuel foils made with and without heat treatment at medium burn-up (of approximately 5 x 10 21 f/cm 3 ). The impact of annealing treatments on critical microstructural properties of the U-Mo fuel foils, including porosity, grain structure, Mo homogeneity, and fuel interaction with the Zr interlayer, was examined using large area lift outs (LALOs). The heat-treated specimens presented less grain refining at these burnups when compared to the un-heated specimens. Grain refinement was associated with porosities and fission products precipitation. Heat treatment can reduce fuel swelling during irradiation. Chemical inhomogeneity (Mo banding) was found to persist in the un-heated samples but was not present in the heat-treated samples. Thus, heat-treated U-Mo foils allows for more predictable fuel behavior under irradiation with respect to un-heated foils. The U-Mo and Zr interaction layer appears to be thicker and more continuous in the heat-treated sample which has been associated with stronger interface integrity during irradiation, as also observed in previous studies. These observations may indicate an overall improved performance of heat-treated fuel foil in a reactor. Further, the effect of local burn-up on grain size/refinement and porosities in each LALO specimen, sampled from different positions in the fuel foil, was difficult to analyze due to the large standard deviation of these parameters. Finally, evidence of grain refinement by polygonization may be present in these specimens.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Physicochemical evolution of uranium nitride kernel microstructure with varying carbon distribution for advanced TRISO fuel forms

Uranium nitride (UN) has emerged as a fuel candidate for advanced nuclear reactor concepts due to its superior uranium density, thermal conductivity, and high melting temperature. However, the fabrication route for converting UO 2 to UN is complex and difficult to standardize. Although the chemistry of this conversion process is well-studied, more insight into the physicochemical dynamics of this conversion using advanced characterization techniques can help further our understanding of this material system. This work leveraged thermogravimetric analysis (TGA), X-ray diffraction (XRD), and nondestructive 3D X-ray computed tomography (XCT) to characterize dynamic microstructural changes in the UO 2 → UCO → UN fabrication pathway for two kernels with a varying carbon distribution in the starting composition. TGA and XRD were used to quantify changes in the mass, density, and chemical composition of the two kernels, while three-dimensional image processing and segmentation of XCT data were used to quantify the volume, surface area, and spatial distribution of features within each kernel for multiple steps along the fabrication pathway. The analysis indicates distinct differences between the two kernels that are correlated to downstream conversion efficiency. In conclusion, this work is among the first to perform 3D quantification of physicochemical evolution during UN conversion, providing quantitative correlation between processing, properties, and expected fuel performance.

Nuclear fuel↗
DOE OSTI2026

A comparison of wrought and powder metallurgical FeCrAl claddings under simulated LWR accident transients

Iron-chromium-aluminum (FeCrAl) alloys are potential accident tolerant fuel (ATF) cladding candidates for light-water reactors but are difficult to fabricate as thin-walled tubes via conventional cast-and-wrought routes. Powder metallurgy (PM) offers a manufacturing alternative with improved compositional control, but its transient accident performance has not been directly benchmarked against wrought variants. This study evaluates the burst behavior of commercially developed PM-processed FeCrAl alloys, PM-C26M (Fe-12Cr-6Al-2Mo) and the high precipitate density FA-SMT (Fe-22Cr-5Al-3Mo), under simulated light-water reactor accident transient conditions. Burst testing was conducted using the Severe Accident Test Station with heating rates of 5 °C/s and 50 °C/s and internal pressures ranging from 25 MPa to 100 MPa. PM-C26M reproduced wrought C26M burst behavior within 7–37 °C across the stress range, indicating that PM processing does not compromise transient strength. FA-SMT exhibited markedly higher burst temperatures and reduced heating-rate sensitivity, consistent with its engineered precipitate strengthening. FA-SMT rupture exhibited axial "unzipping" rather than the lateral tearing characteristic of PM- and wrought C26M. Post-test EBSD and fractography indicate that this behavior is strongly correlated with strain-gated intergranular void nucleation associated with the dense precipitate architecture of FA-SMT, a response absent in the comparatively clean PM-C26M matrix and consistent with rupture morphologies reported for oxide-dispersion strengthened (ODS) FeCrAl of similar base-matrix chemistry to PM-C26M. These findings highlight the potential of powder metallurgy as a viable fabrication route for ATF claddings from an accident performance standpoint.

Bell, Sam [ORNL] (ORCID:0000000251905657)↗
DOE OSTI2022

Low rank approximation in simulations of quantum algorithms

Simulating quantum algorithms on classical computers is challenging when the system size, i.e., the number of qubits used in the quantum algorithm, is moderately large. However, some quantum algorithms and the corresponding quantum circuits can be simulated efficiently on a classical computer if the input quantum state is a low rank tensor and all intermediate states of the quantum algorithm can be represented or approximated by low rank tensors. Here, in this paper, we examine the possibility of simulating a few quantum algorithms by using low-rank canonical polyadic (CP) decomposition to represent the input and all intermediate states of these algorithms. Two rank reduction algorithms are used to enable efficient simulation. We show that some of the algorithms preserve the low rank structure of the input state and can thus be efficiently simulated on a classical computer. However, the rank of the intermediate states in other quantum algorithms can increase rapidly, making efficient simulation more difficult. To some extent, such difficulty reflects the advantage or superiority of a quantum computer over a classical computer. As a result, understanding the low rank structure of a quantum algorithm allows us to identify algorithms that can benefit significantly from quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A machine learning pipeline for membrane segmentation of cryo-electron tomograms

We describe how to use several machine learning techniques organized in a learning pipeline to segment and identify cell membrane structures from cryo electron tomograms. These tomograms are difficult to analyze with traditional segmentation tools. The learning pipeline in our approach starts from supervised learning via a special convolutional neural network trained with simulated data. It continues with semi-supervised reinforcement learning and/or a region merging technique that tries to piece together disconnected components belonging to the same membrane structure. A parametric or non-parametric fitting procedure is then used to enhance the segmentation results and quantify uncertainties in the fitting. Domain knowledge is used in generating the training data for the neural network and in guiding the fitting procedure through the use of appropriately chosen priors and constraints. We demonstrate that the approach proposed here works well for extracting membrane surfaces in two real tomogram datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Rapid mapping of electrochemical processes in energy-conversion devices

Electrochemical impedance spectroscopy (EIS) is ubiquitously applied to identify physicochemical processes governing the performance of energy-conversion devices. However, deconvolution and interpretation of impedance phenomena are limited by measurement throughput and a dearth of scalable analysis methods. Here, we demonstrate an approach to quickly collect and coherently analyze large volumes of electrochemical data. In this study, we accelerate impedance characterization by combining rapid measurements in time and frequency domains, which are interpretably transformed using the distribution of relaxation times (DRT) and a new distribution of phasances (DOP) model. This method provides excellent agreement with EIS and decreases measurement time by an order of magnitude. High-throughput spectra are then distilled into detailed electrochemical maps. This approach is applied to a Li-ion battery and a protonic ceramic electrochemical cell as practical case studies, demonstrating how mapping can richly characterize physicochemical relationships that are difficult to decipher with conventional measurement and analysis methods.

25 ENERGY STORAGE↗
DOE OSTI2020

Magnetic oxygen in transition metal oxides: A case study of Ba 2 CoO 4

Transition metal oxides (TMOs) exhibit exotic magnetic properties in both naturally formed and artificially structured materials, often difficult to understand in conventional wisdom. Magnetic insulator Ba 2 CoO 4 has mystified the community, because the CoO 4 tetrahedron is completely isolated with the nearest Co atoms far apart (~5 Å), making it impossible to account for long-range magnetic ordering seen experimentally using only Co. By theoretically investigating magnetism and relating our findings to experimental observations in bulk Ba 2 CoO 4 , we illustrate for the first time that the magnetic moment on oxygen atoms are the origin of the unexpected long-range magnetic ordering and low magnetic dimensionality. We find that the magnetic moment is not only localized on Co atoms, as assumed in all conventional data analysis, but also distributed on its tetrahedrally-coordinated O atoms. The total magnetic moment of the CoO 4 building block is 4.63μ B with the magnetic moment on Co being only 3.08μ B . Therefore, the magnetic building block is CoO 4 not Co. Furthermore, our first principles calculations are capable of explaining the origin of the unique magnetic response, including the presence of long-range magnetic ordering with two-dimensional character, and a one-dimensional magnetoelastic behavior. Having oxygen contribute to the magnetic moment will undoubtedly be identified as a universal property of magnetic TMOs, which will require a fresh look at conventional models of magnetism in TMOs.

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

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Use of a segmented cell for the combinatorial development of platinum group metal-free electrodes for polymer electrolyte fuel cells

The development of novel platinum group metal (PGM)-free catalysts is a difficult task, particularly when coupled with the integration into a cathode catalyst layer (CCL). The optimization of such PGM-free electrode structures is often non-linear and iterative, making it a demanding task due to the high number of parameters that affect performance. To accelerate both materials discovery and electrode development, this work demonstrates the application of a high-resolution segmented cell (SC) with 121 segments of 0.413 cm 2 size for combinatorial high-throughput PGM-free catalyst screening and CCL optimization. The approach utilizes three flow-field strips with active areas of 4.45 cm 2 each, distributed over 11 segments. Electrodes with identical catalyst material and fabrication method result in reproducible data with typically less than 10% variation between each segment and match in performance with differential single cell data. High throughput testing of combinatorial sample sets, with varied PGM-free electrocatalyst materials or electrode composition, demonstrated the ability to rapidly discern high performing outliers, and establish or confirm trends in electrode optimization. The results indicated significant performance benefits of electrodes with ionomer content of 45 wt% over lower values, and of water rich inks with 82% water content over those with 50%.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Correlative acoustic time-of-flight spectroscopy and X-ray imaging to investigate gas-induced delamination in lithium-ion pouch cells during thermal runaway

It remains difficult to detect internal mechanical deformation and gas-induced degradation in lithium-ion batteries, especially outside specialized diagnostics laboratories. In this work, we demonstrate that electrochemical acoustic time-of-flight (EA-ToF) spectroscopy can be used as an insightful and field-deployable diagnostic/prognostic technique to sense the onset of failure. A 210 mAh commercial lithium-ion cell undergoing thermal abuse testing is probed with in situ and operando EA-ToF spectroscopy, together with simultaneous fractional thermal runaway calorimetry (FTRC) and synchrotron X-ray imaging. The combination of X-ray imaging and EA-ToF analysis provides new understanding into the through-plane mechanical deformation in lithium-ion batteries through direct visualisation and the acoustic ToF response. Internal structural changes, such as gas-induced delamination, are identified using EA-ToF spectroscopy due to variations in the attenuation and signal peak shifts. This is corroborated using X-ray imaging, demonstrating EA-ToF spectroscopy as a promising technique for detecting onset of battery failure.

25 ENERGY STORAGE↗
DOE OSTI2020

Polysulfide reduction and Li 2 S phase formation in the presence of lithium metal and solid electrolyte interphase layer

Lithium sulfur battery is an attractive next generation technology that can meet many demands of modern society. Unfortunately, the lithium sulfur battery faces unique issues related to the polysulfide shuttle effect, that is due to reduction products dissolving in the electrolyte and their subsequent reduction on the lithium metal electrode. This adds further problems to the already challenging needs of understanding and engineering a solid electrolyte interphase (SEI) layer with desired properties. One of the most important SEI properties is its passivation of lithium metal which is critically important to the overall battery performance. Passivation is difficult to measure experimentally without the influence of many factors. This study reports an investigation of the reduction of the intermediate Li 2 S 8 over lithium already passivated with Li 2 O, Li 2 CO 3 , LiOH, LiF and Li 2 S along with exploration of Li 2 S 8 reduction over pristine lithium nanoclusters using first principles computational models. Significant formation of Li 2 S phase nucleation is found to stabilize the reduction products of the Li 2 S 8 . Here, the formation of Li 2 S is explored in-depth with lithium nanocluster-based models determining a 2 V potential increase for the reduction of polysulfides due to the formation of Li 2 S. This investigation demonstrates passivation effects of important SEI components including Li 2 S.

25 ENERGY STORAGE↗