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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deep learning enhanced super-resolution x-ray fluorescence microscopy by a dual-branch network

X-ray fluorescence (XRF) microscopy is a powerful technique for quantifying the distribution of elements in complex materials, which makes it a crucial imaging technique across a wide range of disciplines in physical and biological sciences, including chemistry, materials science, microbiology, and geosciences. However, as a scanning microscopy technique, the spatial resolution of XRF imaging is inherently constrained by the x-ray probe profile and scanning step size. Here we propose a dual-branch machine learning (ML) model, which can extract scale-variant features and bypass abundant low-frequency information separately, to enhance the spatial resolution of the XRF images by mitigating the effects of blurring from the probe profile. The model is trained by simulated natural images, and a two-stage training strategy is used to overcome the domain gap between the natural images and experimental data. The tomography reconstruction from enhanced XRF projections shows an improvement in resolution by a scale factor of four and reveals distinct internal features invisible in low-resolution XRF within a battery sample. This study offers a promising approach for obtaining high-resolution XRF imaging from its low-resolution version, paving the way for future investigations in a broader range of disciplines and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Represent precipitation-induced geological hazards in Earth system models using artificial intelligence

Precipitation-induced geological hazards, such as debris flow, landslides, mudflow and rockfalls (hereafter referred to as landslides), pose serious threats to public safety in many areas through the world. As residential properties and infrastructure in the US have increasingly expanded into landslide-prone areas and the drivers of landslides (e.g., wildfires and hurricanes) are predicted to intensify under climate warming, losses and fatalities from landslides are likely to increase in the future. Although our understanding of geoenvironmental factors and mechanisms contributing to landslides has greatly improved, only moderate progress has been made in predicting landslides out of well-studied watersheds. Furthermore, explicitly representing various landslide-related processes in Earth system models (ESMs), from the buckling of local bearing elements in granular materials, to frictional sliding between grains, formation of microcracks in the soil matrix, rupture of capillary bridges, or breakage of plant roots3 is still very unlikely within the next decade, even with the help of exascale computers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

RCT Continuing Training: Item Release and RAM Control [Slides]

Welcome to the online RCT Continuing Training. This quarter’s topic will review the fundamental elements of radioactive material control and releasing items from controlled areas to include: evaluation if an item may be released and the actions necessary to perform a release from a controlled area.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Sigma Division Capability Strategy

Sigma Division maintains a unique manufacturing science capability at Los Alamos National Laboratory that has made substantial contributions to weapons component process development for more than 70 years. This mission requires the ability to handle a range of radiological and hazardous materials, work with a variety of metallic and non-metallic components, and process materials systems with elements spanning hydrogen to uranium. Today, Sigma serves as a national resource for uranium research and development, provides hardware for experimental campaigns, supports production by demonstrating modern fabrication technologies, and conducts manufacturing science research primarily for customers across the nuclear weapons complex, including the Department of Energy, National Nuclear Security Administration, and Office of Defense Programs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Explicit Dynamic Impact Analysis of the Building 3525 Packages

This report describes the methodology used for the safety basis analysis of the Building (Bldg.) 3525 casks and presents preliminary results for a selected geometry. The specific problem analyzed is a free fall load case onto an unyielding target at various orientations. The various orientations were analyzed to ensure that the packages were subjected to the orientation that causes the most damage. The analysis approach, material modeling, finite element modeling, and results for the selected case are presented, along with a brief discussion of conservatism and uncertainties. The results for the analyzed load cases show that through selected administrative controls, no breach of the container or loss of shielding will occur in the package.

42 ENGINEERING↗
DOE OSTI2021

Polypeptide organic radical batteries

In only a few decades, lithium-ion batteries have revolutionized technologies, enabling the proliferation of portable devices and electric vehicles, with substantial benefits for society. However, the rapid growth in technology has highlighted the ethical and environmental challenges of mining lithium, cobalt and other mineral ore resources, and the issues associated with the safe usage and non-hazardous disposal of batteries. Only a small fraction of lithium-ion batteries are recycled, further exacerbating global material supply of strategic elements. A potential alternative is to use organic-based redox-active materials to develop rechargeable batteries that originate from ethically sourced, sustainable materials and enable on-demand deconstruction and reconstruction. Making such batteries is challenging because the active materials must be stable during operation but degradable at end of life. Further, the degradation products should be either environmentally benign or recyclable for reconstruction into a new battery. Here we demonstrate a metal-free, polypeptide-based battery, in which viologens and nitroxide radicals are incorporated as redox-active groups along polypeptide backbones to function as anode and cathode materials, respectively. These redox-active polypeptides perform as active materials that are stable during battery operation and subsequently degrade on demand in acidic conditions to generate amino acids, other building blocks and degradation products. Here, such a polypeptide-based battery is a first step to addressing the need for alternative chemistries for green and sustainable batteries in a future circular economy.

25 ENERGY STORAGE↗
DOE OSTI2023

Nuclear fuel elements including protective structures, and related method of forming a nuclear fuel element

A nuclear fuel element includes a core comprising a fissile element and an additional element. A protective structure surrounds the core and comprises at least a first material surrounding the nuclear fuel. The first material comprises the fissile element and the additional element and comprises a greater than stoichiometric amount of the additional element. An outer portion of the nuclear fuel element comprises a metal. Related nuclear fuel elements, and related methods are also disclosed.

Griffith, George W.↗
DOE OSTI2021

Inorganic characterization of switchgrass biomass using laser-induced breakdown spectroscopy

The inorganic characterization of 74 samples of switchgrass using laser-induced breakdown spectroscopy (LIBS) was undertaken. Determination of ash and inorganic elements content in biomass materials is vital for feedstock screening for bioconversion processes. Hierarchical models using principal component analysis (PCA) and partial least square analysis (PLS) were used to determine the presence of specific elemental micronutrients that are important in determining plant health for robust biomass production. LIBS uses a 532 nm laser with 45 mJ of laser power to excite the samples of switchgrass plant material and the emission of all the elements present in the plant samples were recorded in single spectra with a wide wavelength range of 200–800 nm. The results were compared to the laboratory standard technique, e.g., ICP-OES technique, to determine the true values for major micronutrients such as, silicon (Si), potassium (K), calcium (Ca), magnesium (Mg), phosphorus (P), and sulfur (S). Overall, our objectives were: 1) To determine the spectral features of switchgrass containing different amounts of these elements and 2) To examine the viability of this technique for determining the quality of the feedstock in terms of its inorganic composition. Cross-validation results showed that the broad-based model developed is promising for inorganics prediction in switchgrass. The LIBS validation prediction for the micronutrient elements mentioned here have been obtained. The regression coefficients for Si, were obtained to be 0.995, 0.994 for calibration and validation respectively, in case of Ca the regression coefficients were, 0.994 and 0.992 for calibration and validation. Similarly, in the case of Mg and K these were calculated to be 0.992 and 0.985, and 0.994 and 0.993 respectively. The regression coefficients are not as good as those for the elements mentioned, in case of the two elements S and P. They are 0.957, and 0.878, and 0.952 and 0.894 respectively for calibration, validation for the two elements. This demonstrates that LIBS-based techniques are inherently well suited for diverse environmental applications. Furthermore, LIBS along with PLS model can show capability in determining the viability of switchgrass as a biomass in the production of biofuels and survivability of switchgrass in processes associated with climate change. LIBS can help determining which switchgrass would be appropriate for a specific conversion process that favors low ash content overall or low value of specific inorganics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Superconductivity in a uranium containing high entropy alloy

Abstract High entropy alloys (HEA) are an unusual class of materials where mixtures of elements are stochastically arrayed on a simple crystalline lattice. These systems exhibit remarkable functionality, often along several distinct axes: e.g., the examples [TaNb] 1-x (TiZrHf) x are high strength and damage resistant refractory metals that also exhibit superconductivity with large upper critical fields. Here we report the discovery of an f -electron containing HEA, [TaNb] 0.31 (TiUHf) 0.69 , which is the first to include an actinide ion. Similar to the Zr-analogue, this material crystallizes in a body-centered cubic lattice with the lattice constant a = 3.41(1) Å and exhibits phonon mediated superconductivity with a transition temperatures T c ≈ 3.2 K and upper critical fields H c2 ≈ 6.4 T. These results expand this class of materials to include actinide elements, shows that superconductivity is robust in this sub-group, and opens the path towards leveraging HEAs as functional waste forms for a variety of radioisotopes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Finite Element Modeling of Diffusion in Fractured Porous Media by Using Hierarchical Material Properties

Abstract Fractured porous media challenge modeling approaches due to high computational costs and excessive mesh refinement imposed by the extreme scale variability of fractures and the heterogeneity of the surrounding porous rock. To overcome such difficulties, we utilize the hierarchical finite element method ( Hi ‐FEM) that has been developed previously to simulate the electrical potential distribution in complex geologic environments. The method employs the hierarchical basis functions in classical finite element analysis to enable representation of material properties on each dimensional component of a given 3D unstructured finite element, thereby inherently allowing for interactions at the boundary between fracture and a host rock. In this study, we extend its application to transient fluid flow and heat conduction in the Laplace domain. Time‐domain flow solutions are obtained by numerical inverse Laplace transform. We evaluate the accuracy of the method using different flow models and demonstrate its robustness for large‐scale, rock mass models featuring complex fracture networks. Moreover, for the computation of nodal Darcian velocity fields in fractured porous media where the fractures are represented as 2D features, a new approach that employs the Yeh's Galerkin model for both volume and facet elements is proposed. Results show that Hi ‐FEM can produce accurate flow solutions for fractured porous media without any need of coupling or transfer mechanism while still being computationally economical and numerically robust, even for large‐scale simulations.

Beskardes, G. D.↗
DOE OSTI2020

Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A New Family of Ternary Intermetallic Compounds with Dualistic Atomic Ordering – The ZIP Phases

A new family of nanostructured ternary intermetallic compounds − named the ZIP phases − is introduced in this work. The ZIP phases exhibit dualistic atomic ordering, i.e., they form two structural variants: one with the fcc diamond cubic structure (space group Fd$\bar{3}$m) and one with the hexagonal structure (space group P6 3 /mmc). They are also characterized by metallic behavior, ionic bonding, and atomic zigzagging. Powder metallurgical routes involving pressure-assisted densification are adopted to demonstrate ZIP phase synthesis in the Nb-Si-Ni, Nb-Si-Co, Ta-Si-Ni, V-Si-Ni, and Nb-Si-Fe ternary systems. Crucially, reactive hot pressing is capable of producing high-purity ZIP phase materials after the judicious, elemental system-specific optimization of the processing route. Synthesis of phase-pure materials – demonstrated in the Nb-Si-Ni ternary system by the synthesis of quasi phase-pure Nb 3 SiNi 2 and Ni 3 SiNb 2 ZIP phase-based materials – is a steppingstone to the prospective exploitation of the ZIP phases. Characterization of Nb 3 SiNi 2 and Ni 3 SiNb 2 involves crystal structure determination, spatially resolved chemical analysis, and determination of select thermal, electrical, magnetic, mechanical, and physical properties. Density functional theory is used to assess the stability of Nb 3 SiNi 2 & Ni 3 SiNb 2 and derivative binary compounds at different temperatures, also exploring the exfoliation of these two ZIP phases along specific surfaces to produce 2D derivatives.

Intermetallic compounds (IMCs)↗
DOE OSTI2021

The Effect of Material Properties on Oxygen Evolution Activity and Assessing Half-Cell Screening as a Predictive Tool in Electrolysis

Iridium-based oxygen evolution catalysts are screened in this study for activity and stability with rotating disk electrode (RDE) half-cells. This study focuses on the electrochemical and materials approaches needed to characterize oxygen evolution catalysts, and include testing for activity, stability, composition, oxide content, and structure. Findings also discuss recommendations for data interpretation and detail the difficulties of comparing catalysts across materials sets with different elemental and oxide compositions, and linking RDE activity to device-level performance. The materials evaluated are a mixture of oxides and metals, and several methods are used to quantify metal content, qualitatively assess oxide content, and determine total surface area. Oxygen evolution activities and stabilities are compared, where a wide range of results are reported. In general, higher RDE performances are found for catalysts that contained larger amounts of ruthenium and metals. Higher durability, however, is found for catalysts that only contained iridium and a higher proportion of oxides. Additionally, catalysts are evaluated for performance in membrane electrode assemblies to assess RDE as a predictive tool in electrolysis. While activity trends within individual material sets generally held between ex- and in-situ testing, RDE tends to overestimate the activity of more metallic catalysts when compared to device-level performance. These results stress the need for multiple metal/oxide baselines for mixed catalysts, to better project in-situ kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of off-diagonal elements in the Wannier Hamiltonian on DFT + DMFT for low-symmetry materials: Study of Li 2 MnO 3

Here, we study the effect of the off-diagonal elements of the Wannier Hamiltonian on the electronic structure of the low-symmetry material Li 2 MnO 3 ( C2/m ), using dynamical mean field theory calculations with a continuous-time quantum Monte Carlo impurity solver. The presence of significant off-diagonal elements leads to a pronounced suppression of the energy gap. The off-diagonal elements are largest when the Wannier projection is used based on the global coordinate, and they remain substantial even with the projection using the local coordinate close to the direction of Mn-O bonds. We show that the energy gap is enhanced by the diagonalization of the Mn d block in the full p-d Hamiltonian with the application of a unitary rotation matrix. Additionally, the inclusion of small double counting energy is crucial for achieving the experimental gap by reducing p-d hybridization. Furthermore, we establish the efficiency of a low-energy (d-only basis) model for studying the electronic structure of Li 2 MnO 3 , as the Wannier basis represents a hybridized state of Mn d and O p orbitals. These findings suggest an appropriate approach for investigating low-symmetry materials using the density functional theory plus dynamical mean field theory (DFT + DMFT) method. We also find that the antiferromagnetic ground state $\Gamma$ 2u is stable with U ≤ 2 eV within density functional theory+$U$ calculations, which is much smaller than the widely used U = 5 eV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗