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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Accelerated and heterogeneous corrosion of Cr-doped uranium nitride fuel pellets

The steam oxidation of Cr-doped UN fuel pellets is analyzed during sequential isothermal holds up to 720 °C. In situ neutron diffraction results show how Cr is accommodated in a secondary U 2 CrN 3 phase, leading to the formation of a duplex UN/U 2 CrN 3 microstructure. Under corrosion, the oxidation of the two phases begins at 400 °C for UN and 430 °C for U 2 CrN 3 , respectively. Because the UN phase is preferentially oxidized in the presence of U 2 CrN 3 , addition of Cr in UN based nuclear fuel is found to accelerate the corrosion rate. At 430 °C the oxidation of UN in the UN/U 2 CrN 3 microstructure is ~ 5 times faster than pure UN, increasing to ~19 times faster at 460 °C. The oxidation of U 2 CrN 3 produces UO 2 via the formation of two transient intermediate phases. In situ neutron diffraction enables oxidation processes of UN and U 2 CrN 3 components to be followed separately within the two-phase system.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Predicting the proximity to macroscopic failure using local strain populations from dynamic in situ X-ray tomography triaxial compression experiments on rocks

Predicting the proximity of large-scale dynamic failure is a critical concern in the engineering and geophysical sciences. Here we use evolving contractive, dilatational, and shear strain deformation preceding failure in dynamic X-ray tomography experiments to examine which strain components best predict the proximity to failure. We develop machine learning models to predict the proximity to failure using time series of three-dimensional local incremental strain tensor fields acquired in rock deformation experiments under stress conditions of the upper crust. Three-dimensional scans acquired in situ throughout triaxial compression experiments provide a distribution of density contrasts from which we estimate the three-dimensional incremental strain that accumulates between each scan acquisition. Training machine learning models on multiple experiments of six rock types provides suites of feature importance that indicate the predictive power of each feature. Comparing the average importance of groups of features that include information about each strain component quantifies the ability of the contractive, dilatational and shear strain to predict the proximity of macroscopic failure. A total of 24 models of four machine learning algorithms with six rock types indicate that 1) the dilatational strain provides the best predictive power of the strain components, and 2) the intermediate values (25th-75th percentile) of the strain population provide the best predictive power of the statistics of the strain populations. In addition, the success of the predictions of models trained on one rock type and tested on other rock types quantifies the similarities and differences of the precursory strain accumulation process in the six rock types. These similarities suggest the potential existence of a unified theory of brittle rock deformation for a range of rock types.

58 GEOSCIENCES↗
DOE OSTI2020

Unraveling the dislocation–precipitate interactions in high-entropy alloys

The precipitates play a significant role in not only enhancing the strength, but also maintaining the high toughness in alloys. However, the interactions of the nanoscale precipitates with dislocations in the high entropy alloys (HEAs) are difficult to observe directly by in-situ TEM experiments due to the limits of the resolution and time. Here, using atomic simulations we report the synergistic strengthening of the coherent precipitate and atomic-scale lattice distortion in the HEAs at cryogenic/elevated temperatures. The effects of temperature, chemical disorder, precipitate spacing, precipitate size, elemental segregation, and dislocation-cutting number on the critical stress for the dislocation to overcome a row of precipitates are studied. A random stacking fault energy landscape along the slip plane, the lattice distortion at different temperatures, and the interface/surface energy at various crystallographic orientations are obtained. Compared with the traditional metals and alloys, HEAs have the severe atomic-scale lattice distortions to generate the local high tensile/compressive stress fields. This complex stress causes the dislocation line to bend, and thus improves the dislocation slip resistance, resulting in the strong solid-solution strengthening. The stacking fault strengthening induced by the obvious difference of the stacking fault energies between the HEA matrix and precipitate (within the inner of the HEA matrix), and the formation of the antiphase domain boundary contribute to the high strength. The precipitate embedded by the solute atoms produces the strong lattice distortion to enhance the dislocation slip resistance at high temperatures. Hence, the current results provide the mechanistic insight into the phenomenon that the coherent precipitate combined with the severe atomic-scale lattice distortion can enhance the strength at cryogenic/elevated temperatures to further broaden the scope of applications of advanced HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A continuum damage mechanics (CDM) based Wilshire model for creep deformation, damage, and rupture prediction

In this report, a new constitutive model is derived that combines the Wilshire equations with continuum damage mechanics (CDM) to enable the long-term prediction of creep deformation, damage, and rupture. The Wilshire equations have been demonstrated to accurately extrapolate the stress-rupture, minimum-creep-strain-rate, and time-to-strain of various alloys across decade of life. Recently, the time-to-creep-strain equation has been rearranged to predict creep deformation curves; however, the resulting equation is difficult to calibrate and does not track damage. The CDM-based Sinh constitutive model accurately predicts creep deformation, damage, and stress-rupture for a variety of alloys; however, it lacks an explicit description of stress and temperature co-dependence which limits interpolation and extrapolation ability. In this study, the Wilshire and the CDM-based Sinh equations are combined to create the “WCS” model. The WCS model combines the best features of each model while eliminating their deficiencies. Experimental data for alloy P91 is gathered and the WCS model is calibrated to the data. The WCS model accurately predicts the stress rupture, minimum-creep-strain-rate, creep deformation, and damage of alloy P91 across the experimental stress and temperature range as well as consistency in parametric simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fracture characteristics and heat treatment of laser powder bed fusion additively manufactured GRCop-84 copper

Laser Powder Bed Fusion (LPBF) of Glenn Research Copper 84 (GRCop-84), a Cr 2 Nb (8 at. % Cr, 4 at. % Nb) precipitation hardened alloy, produces a fully dense high conductivity alloy with a yield strength of 500 MPa and ultimate tensile strength (UTS) of 740 MPa, superior to other competing copper alloys, and 20% elongation at fracture for material stressed perpendicular to the build direction. The high thermal stability of the Cr 2 Nb precipitate in the copper matrix reduces coarsening and maintains a 300 MPa yield, 520 MPa UTS and 26% elongation after a 900 °C, 5-h heat treatment, while a 3 h 450 °C heat treatment increases yield to 810 MPa, UTS to 970 MPa with 9% elongation at fracture, for samples stressed perpendicular to the build direction. Tensile strength anisotropy based on print direction was attributed to internal stress and columnar grain formation. Void nucleation during tensile fracture was initiated by brittle fracture of precipitate particles within the copper matrix. Fracture cusps contain matching precipitate fragment geometry on opposing sides located near the cusp center in at least 80% of fracture cusps. An optimal precipitate size of 100 nm is predicted for maximum tensile strength from precipitates on fracture surfaces, while tensile testing with varying heat treatments shows maximum strength with 100 nm and smaller precipitates. Cr2Nb precipitates are shown to transition between polycrystalline and monocrystalline structures at high temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evidence of hexagonal germanium grains on annealed monolayer MoS 2

Growing three-dimensional (3D) materials on two-dimensional (2D) van der Waals surface has shown its effectiveness in overcoming materials incompatibility for stacking transferrable membranes toward advanced device manufacturing. Herein, we demonstrate that the nucleation of hexagonal germanium (Ge) grains within a continuous crystalline film, which has been unfeasible through traditional epitaxy techniques, is realized by chemical vapor deposition on top of n-type monolayer molybdenum disulfide (MoS 2 ) substrates. Suggested by quantum molecular dynamics calculation, the hexagonal Ge nucleation is thermodynamically preferable to cubic Ge when growing on monolayer MoS 2 with sulfur vacancies. The strained hexagonal Ge grains have been confirmed by transmission electron microscopy analyses from both real space and reciprocal space. Scanning probe microscopy shows that the hexagonal Ge film possesses higher reflectivity in infrared spectral range, implying a higher carrier concentration resulted from the narrower band gap, as compared to cubic Ge.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Livermore tomography tools: Accurate, fast, and flexible software for tomographic science

Livermore Tomography Tools (LTT) is a customizable scientific software package that enables a broad range of research and development efforts into computed tomography (CT). Here, it was developed to process x-ray and neutron CT data accurately and rapidly from raw detector counts to reconstructed volumes with the flexibility to handle many special cases. LTT fulfills long-term CT software goals to provide quantitatively accurate results reported in physical units (e.g., mm -1 or cm -1 ) while exploiting all available computational advantages to maximize speed. Written in C/C++ with support for multiple CPUs and GPUs, LTT runs on many computing platforms (Linux/Unix, Windows, and Mac; laptops to supercomputers). As a result, LTT can:process data acquired from various custom-built and commercially available CT scanners, model and simulate x-ray and neutron interactions to encourage algorithm prototyping, and allow for rapid insertion of the latest algorithms.We describe LTT’s software architecture, user interfaces, and its 88 algorithms (as of this writing) for pre-processing, reconstruction, post-processing, and simulation that support many scanner geometries (parallel-, fan-, cone-beam, and custom). Several applications are presented that illustrate LTT’s accuracy, speed, and flexibility relative to other solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Porosity evolution under increasing tension in wire-arc additively manufactured aluminum using in-situ micro-computed tomography and convolutional neural network

Internal defects such as porosities are often formed in additively manufactured metal components. The pores nucleate, grow, and coalesce to form cracks under loads, leading to eventual catastrophic failure. Here, in this paper, the full-field porosity evolution, including pore growth and coalescence in a wire-arc additively manufactured (WAAM) aluminum alloy cylinder under tension is observed with in-situ X-ray micro-computed tomography (μCT). The pore size distribution, density, and tensile stress are calculated from the volumetric images analyzed by a convolutional neural network (CNN) algorithm, which provides rapid analysis of 12,950 slice images from μCT volumetric images at the reference state and 13 tensile strains. The results show the quantitative evolution of the growth and coalescence of macropores under tension. A strong correlation is found between the local pore volume fraction and the true tensile stress when the tensile strain is larger than 5%.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Three-dimensional morphology of an ultrafine Al-Si eutectic produced via laser rapid solidification

Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characterization and computer vision techniques, we perform a three-dimensional analysis of the branching behavior of the ultrafine eutectic and compare it against an impurity-modified eutectic as well as a random fractal (as a benchmark). Differences in the branching statistics point to different microstructural origins of the impurity- and quench-modified eutectic. Finally, our quantitative approach is not limited to the data presented here but can be used to extract abstract information from other volumetric datasets, without customization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Selective recovery of rare earth elements with ligand-functionalized polymers in fixed-bed adsorption columns

Rare earth elements (REE) are a group of valuable metals with growing demand and broad applications. Mineral ores, the traditional sources of REE, require significant capital investment and their refinement has been a source of environmental contamination. Industrial fluids and natural REE-bearing liquids are potential alternative sources for these metals. This work investigated the performance and REE selectivity of polymer resin beads functionalized with N,N-bis(phosponomethyl)glycine (BPG) for extraction of REE from saline solutions in fixed-bed adsorption columns. Competitive batch adsorption experiments were conducted with various metals (Nd, Gd, Ho, Al, Fe, Co, Ni, Ba, Pb, Th, and U) and the BPG-functionalized resins were up to 137 times more selective for REE than aminated resins. In column experiments, the BPG-functionalized resins preferentially adsorbed heavier metals and REE were strongly retained in the functionalized column, taking 270 times longer than the amine column to reach 10% breakthrough and 128 times longer to reach 50% breakthrough. REE bound to the BPG-functionalized resins were recovered with a dilute HNO3 solution, yielding REE concentrations up to 236 times higher than the influent feedstock. This work provides new insight into the operational performance of novel functionalized adsorbents for recovery of REE from saline fluids.

42 ENGINEERING↗
DOE OSTI2020

Poly(lactic acid)-Based Ink for Biodegradable Printed Electronics With Conductivity Enhanced through Solvent Aging

Biodegradable electronics is a rapidly growing field, and the development of controllably biodegradable, high-conductivity materials suitable for additive manufacturing under ambient conditions remains a challenge. Here, printable conductive pastes that employ poly(lactic acid) (PLA) as a binder and tungsten as a conductor are demonstrated. These composite conductors can provide enhanced stability in applications where moisture may be present, such as environmental monitoring or agriculture. Post-processing the printed traces using a solvent-aging technique increases their conductivity by up to 2 orders of magnitude, with final conductivities approaching 5000 S/m. Such techniques could prove useful when thermal processes including heating or laser sintering are limited by the temperature constraints of typical biodegradable substrates. Finally, both accelerated oxidative and hydrolytic degradation of the printed composite conductors are examined, and a fully biodegradable capacitive soil moisture sensor is fabricated and tested.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An unsupervised machine learning based approach to identify efficient spin-orbit torque materials

Materials with large spin–orbit torque (SOT) hold considerable significance for many spintronic applications because of their potential for energy-efficient magnetization switching. Unfortunately, most of the existing materials exhibit an SOT efficiency factor that is much less than unity, requiring a large current for magnetization switching. The search for new materials that can exhibit an SOT efficiency much greater than unity is a topic of active research, and only a few such materials have been identified using conventional approaches. In this paper, we present a machine learning-based approach using a word embedding model that can identify new results by deciphering non-trivial correlations among various items in a specialized scientific text corpus. We show that such a model can be used to identify materials likely to exhibit high SOT and rank them according to their expected SOT strengths. The model captured the essential spintronics knowledge embedded in scientific abstracts within various materials science, physics, and engineering journals and identified 97 new materials to exhibit high SOT. Among them, 16 candidate materials are expected to exhibit an SOT efficiency greater than unity, and one of them has recently been confirmed with experiments with quantitative agreement with the model prediction.

Sayed, Shehrin↗
DOE OSTI2021

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

Recent advances in detectors for imaging and spectroscopy have afforded in situ, rapid acquisition of hyperspectral data. While electron energy loss spectroscopy (EELS) data acquisition speeds with electron counting are regularly reaching 400 frames per second with near-zero read noise, signal to noise ratio (SNR) remains a challenge owing to fundamental counting statistics. In order to advance understanding of transient materials phenomena during rapid acquisition EELS, trustworthy analysis of noisy spectra must be demonstrated. In this study, we applied machine learning techniques to denoise high frame rate spectra, benchmarking with slower frame rate “ground truths”. The results provide a foundation for reliable use of low SNR data acquired in rapid, in-situ spectroscopy experiments. Such a tool-set is a first step toward both automation in microscopy as well as use of these methods to interrogate otherwise poorly understood transformations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient crystal structure materials as reactive sorbent for the CO 2 and CH 4 adsorption and storage

The efficient dirubidium cobalt bis(dihydrogendiphosphate) dihydrate compound is successfully synthesized in a solution and used as a reactive sorbent for the CO 2 and CH 4 gases adsorption and storage. A crystal of this Rb 2 Co(H 2 P 2 O 7 ) 2 ·2H 2 O compound has been isolated and characterized by single X-ray diffraction analysis and was found to crystallize in the triclinic system (P$\overline{1}$) with the cell parameters (Å): 6.980(1), 7.370(1), 7.816(1), 81.74(1), 70.35(1), 86.34(1); V = 374.68(9) Å3, Z = 2. The crystal-packing consists of a three-dimensional framework made upon corners and edges sharing of [RbO 7 ], [H 2 P 2 O 7 ] and [CoO 6 ] entities, furthermore linked by a network of H-bonds. The UV–Vis spectroscopy revealed usual transitions between the ground state 4T1g and the upper levels 4T2g, 4A2g and 4T1g (P). Moreover, the CO 2 and CH 4 gases sorption measurements were successfully performed at two different temperatures (25 and 45 °C) and various pressures ranging from vacuum to 50 bar. Our results show that rate of CO 2 and CH 4 capturing was 3.10 mmol/g and 2.35 mmol/g at temperature 25 °C and pressure 50 bar, respectively. This compound showed a clear potential for CO 2 /CH 4 adsorption and storage thereby paving the way towards its exploration and adaptation for capturing and collecting carbon dioxide and greenhouse gases from the air, and their conversion into hydrocarbon fuels using existing mature technologies. We have also conducted density functional theory calculations to study the CO 2 and CH 4 adsorption properties of Rb 2 Co(H 2 P 2 O 7 ) 2 ·2H 2 O. The simulation results show enhanced adsorption of both types of molecules on the surface of the material.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Energy and physical resource impacts of quantum computing merit greater attention

Quantum computing research and development is growing worldwide; yet the energy and physical resource demands of future quantum-accelerated data centres are unknown. Planning for quantum computing requires strong collaboration between research communities across engineering, physics, environmental sciences, economics, policy, and energy systems and scenario modelling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Advances in bioelectronics: Materials, devices, and translational applications

Modern electronics and materials science are bringing revolutionary advances to biointerface design and are shattering the limits of what is possible in the areas of biomedical diagnostics and sensing, neuroscience, and prosthetics. Furthermore, this special issue highlights the rapid progress in all areas of bioelectronics and includes contributions that explore the interfaces between electronics, materials science, and other engineering disciplines, as well as biochemistry, biophysics, and general biology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗