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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Tuning SPT-3G Transition-Edge-Sensor Electrical Properties with a Four-Layer Ti–Au–Ti–Au Thin-Film Stack

We have developed superconducting Ti transition-edge sensors with Au protection layers on the top and bottom for the South Pole Telescope’s third-generation receiver (a cosmic microwave background polarimeter, due to be upgraded this austral summer of 2017/2018). The base Au layer (deposited on a thin Ti glue layer) isolates the Ti from any substrate effects; the top Au layer protects the Ti from oxidation during processing and subsequent use of the sensors. We control the transition temperature and normal resistance of the sensors by varying the sensor width and the relative thicknesses of the Ti and Au layers. The transition temperature is roughly six times more sensitive to the thickness of the base Au layer than to that of the top Au layer. The normal resistance is inversely proportional to sensor width for any given film configuration. For widths greater than five micrometers, the critical temperature is independent of width.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review

The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Friction Extrusion: Solid-State Metal Synthesis and Recycling in Sustainable Manufacturing

Friction extrusion (FE) is a novel solid-state process for synthesis and recycling of metals and alloys. The novelty of FE is that it utilizes the frictional heating and extensive plastic deformation intrinsic in the process to stir, mechanically alloy, consolidate, and convert powders, chips, and other recyclable feedstock metals into a usable product form of highly engineered materials. FE represents a potentially transformational sustainable manufacturing technology. Being a solid-state process, it eliminates the energy-intensive melting and solidification steps, which are necessary in the conventional metal recycle and synthesis processes. Therefore, FE is a highly energy-efficient, practically zero-emission, and economically competitive process. Here, in this work, the concept and configuration of FE are introduced, the energy-saving advantage of FE is analyzed, the feasibility of FE is demonstrated with synthesizing Al alloys, and the results of some metallographic and mechanical properties studies are presented. A prognosis of the friction extrusion technology is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Imaging doxorubicin and polymer-drug conjugates of doxorubicin-induced cardiotoxicity with bispecific anti-myosin-anti-DTPA antibody and Tc-99m-labeled polymers

Background: Radiolabeled anti-myosin imaging is well-established for imaging doxorubicin-induced cardiotoxicity. However, to enable imaging of drug-induced cardiotoxicity in small experimental animals, pretargeting with bispecific anti-myosin-anti-DTPA-Fab-Fab’ and targeting with high-specific radioactivity Tc-99m-DTPA-succinylated-polylysine (DSPL) was developed. Methods: Mice were injected biweekly with 10 mg/kg Dox or its equivalent as D-Dox-PGA. Tc-99m-DSPL myocardial activity after pretargeting with bsAb-Fab-Fab’ was determined after gamma imaging performed at day 7 for Dox-treated mice and day 39 for all others. Results: Mice treated with 10 mg/kg Dox lost 10% total body weight in 1 week and 20% after a second dose. Pretargeted mice treated with 30 mg/kg cumulative D-Dox-PGA dose showed no loss of body weight for the duration of the study. Cardiotoxicity was confirmed by gamma imaging and scintillation counting (1.9 ± 0.25 [mean% ID/g ± SD]) after 1 dose of Dox. Mice injected with 3 × 10 mg/kg Dox equivalent as D-Dox-PGA (0.4 ± 0.04, P < .01) and untreated 2 control groups (0.20 ± 0.05 and 0.19 ± 0.04, P < .01) showed significantly lower myocardial anti-myosin radioactivity relative to the 10 mg/kg Dox group. Conclusion: Pretargeting with bsAb-Fab-Fab’ and targeting with Tc-99m labeled high-specific activity polymers enabled early visualization of doxorubicin induce cardiotoxicity in mice. Tolerated dose of D-Dox-PGA was greater than to 30 mg/kg Dox-equivalent dose with minimal cardiotoxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

A study of deformation and strain induced in bulk by the oxide layers formation on a Fe-Cr-Al alloy in high-temperature liquid Pb-Bi eutectic

At elevated temperatures, heavy liquid metals and their alloys are known to create a highly corrosive environment that causes irreversible degradation of most iron-based materials. In this paper, it has been found that an appropriate concentration of oxygen in the liquid alloy can significantly reduce this issue by creating a passivating oxide scale that controls diffusion, especially if Al is present in Fe-based materials (by Al-oxide formation). However, the increase of the temperature and of oxygen content in liquid phase leads to the increase of oxygen diffusion into bulk, and to promotion of the internal Al oxidation. This can cause a strain in bulk near the oxide layer, due either to mismatch between the thermal expansion coefficients of the oxides and bulk material, or to misfit of the crystal lattices (bulk vs. oxides). This work investigates the strain induced into proximal bulk of a Fe-Cr-Al alloy by oxide layers formation in liquid lead-bismuth eutectic utilizing synchrotron X-ray Laue microdiffraction. Finally, it is found that internal oxidation is the most likely cause for the strain in the metal rather than thermal expansion mismatch as a two-layer problem.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Quantified uncertainty in thermodynamic modeling for materials design

Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach. Here, the accuracy of CALPHAD predictions vary widely in X-T-P space due to experimental error, model inadequacy and unequal data coverage. In response, researchers have developed frameworks to quantify the uncertainty of thermodynamic property model parameters and propagate it to phase diagram predictions. In most previous studies, uncertainty was represented as intervals on phase boundaries (with respect to composition or temperature) and was unable to represent the uncertainty in invariant reactions or in the stability of phase regions. In this work, we propose a suite of tools that leverages samples from the multivariate model parameter distribution to represent uncertainty in forms that surpass previous limitations and are well suited to materials design. These representations include the distribution of phase diagrams and their features, as well as the dependence of phase stability and the distributions of phase fraction, composition, activity and Gibbs energy on X-T-P location - irrespective of the total number of components. Most critically, the new methodology allows the material designer to interrogate a certain composition and temperature domain and get in return the probability of different phases to be stable, which can positively impact materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A spall and diffraction study of nanosecond pressure release across the iron ε-α phase boundary

The extreme response of polycrystalline iron at high pressures and high strain rates is revealed by means of high-power laser pulses. The compression portion of the pulse coupled with x-ray diffraction identifies the expected body-centered cubic (α) to hexagonal close packed (ε) displacive transformation. Upon release, observation shows that the complete reverse transformation takes approximately 8 ns and that the structure returns to its initial microstructural configuration, in a reversible transformation path. This is in good agreement with molecular dynamics (MD) simulations which predict an inverse dependence between transformation time and strain rate. The grain size is reduced from μm to nm range during compression and begins increasing back to the original grain size on decompression. The kinetics of the transition is dictated by heterogenous nucleation as it follows the Johnson-Mehl-Avrami-Kolmogorov equation with the appropriate time exponent of ~1. This is confirmed by MD simulations which also identify profuse twinning and dislocation generation. Here, the tensile pulse generated upon reflection at the free surface is captured by time-resolved free surface velocity measurements from which a peak tensile stress of 7 GPa is obtained, in stark contrast with its quasi-static value of ~200 MPa. At these strain rates, the strength of grain interiors, which is determined by twinning and slip exceeds the strength of the boundaries, and failure initiates preferentially in the latter.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlations between thermal history and keyhole porosity in laser powder bed fusion

Additive manufacturing has the potential to revolutionize the production of metallic components as it yields near net shape parts with complex geometries and minimizes waste. At the present day, additively manufactured components face qualification and certification challenges due to the difficulty in controlling defects. This has driven a significant research effort aimed at better understanding and improving processing controls – yielding a plethora of in-situ measurements aimed at correlating defects with material quality metrics of interest. In this work, we develop machine-learning methods to learn correlations between thermal history and subsurface porosity for a variety of print conditions in laser powder bed fusion. Un-normalized surface temperatures (in the form of black-body radiances) are obtained using high-speed infrared imaging and porosity formation is observed in the sample cross-section through synchrotron x-ray imaging. To demonstrate the predictive power of these features, we present four statistical machine-learning models that correlate temperature histories to subsurface porosity formation in laser fused Ti-6Al4V powder.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Observed compression of in situ tree stems during freezing

Freezing temperatures can influence the material properties of trees. Understanding how forest biometeorological interactions respond to freezing temperatures is important for forest science and management, as its effects can cascade through coupled hydrological and ecological processes including limitations on tree growth, changes to canopy interception, and influences on atmospheric turbulence. This short communication details the effect of sub-freezing temperatures on the mechanical displacement of three in situ Pinus contorta Douglas (lodgepole pine) stems during a winter season (2013–2014) at Niwot Ridge Mountain Research Station (CO, USA). Although previous research on harvested trees suggests longitudinal stem expansion should occur as temperatures decrease below freezing, we observed longitudinal compression in live stems below -3 °C that linearl y correlated with sub-zero air temperatures ranging down to -22 °C. Freeze-related compression of stems frequently achieved displacement magnitudes comparable to applying 55 kN of compressive force (800 μm). Hypotheses are proposed to explain the significant mechanical displacement observed due to freezing: (1) internal gas release as freezing fronts propagate through stems; (2) short-term relocation of water via sap exudation or preferential ice crystal growth. As the observed stem compression response to freezing is substantial, future work on underlying processes and consequences is merited. The measurement technique used here may prove useful to others interested in the dynamics of stem freezing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Fallout melt debris and aerodynamically-shaped glasses in beach sands of Hiroshima Bay, Japan

An intricate association of millimeter-sized, aerodynamically-shaped debris, including glass spherules, glass filaments, and composite-fused melt particles was recovered from beach sands on the shores of the Motoujina Peninsula in Hiroshima Bay, Japan. Based on optical microscopy, this debris comprises six morphological groups ranging from clear glasses to rubber-like constituents. Scanning electron microscopy and synchrotron X-ray microdiffraction revealed dominant aluminum, silicon and calcium (Al-Si-Ca) elemental composition with some iron, mainly in glass, associated with precipitates of mullite and anorthite microcrystals, hematite dendrites and iron-chromium globules, indicative of original temperature conditions >1800 °C. Aerodynamically-shaped fallout debris, including glass spherules described in this study, are generally produced by single high-energy catastrophic events, such as an extraterrestrial body impacting Earth or a nuclear explosion. Our work interprets the large volumes of fallout debris generated under extreme temperature conditions as products of the Hiroshima August 6th, 1945 atomic bomb aerial detonation. The chemical composition of the melt debris provides clues to their origin, particularly with regard to city building materials. This study is the first published record and description of fallout resulting from the destruction of an urban environment by atomic bombing.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Orientation-dependent structural properties during growth and growth mechanism of CoO films

The orientation-dependent local structural properties of CoO films on sapphire substrates during growth were investigated through linearly-polarized extended X-ray absorption fine structure (EXAFS) measurements. Specifically, CoO(1 1 1) and (100) crystals with a rock-salt structure (Fm3m) were epitaxially grown on alpha-Al2O3(0001) and (1012) substrates, respectively, at 700 degrees C using a radio-frequency sputtering system. The local structural properties of CoO films in the in-plane and out-of-plane orientations were quantitatively determined using linearly-polarized EXAFS at the Co K-edge during growth. The EXAFS analysis revealed that during the initial stages of growth, the local structural properties exhibit significant differences compared to thick films, with short atomic distances and large (small) Debye-Waller factors observed in the out-of-plane (in-plane) orientations. The local structural strain mostly diminished when approximately 20 CoO layers accumulated on the substrate. Density functional theory (DFT) calculations further supported these findings by confirming that cobalt atoms initially form stable bonds with the sapphire surface, leading to the simultaneous growth of oxygen and cobalt layers in a coordinated manner through layer-by-layer growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermodynamics of monoclinic and tetragonal hafnium dioxide (HfO 2 ) at ambient pressure

Accurate and precise thermodynamic models of oxide compounds and their phases are important for calculating the phase stability of oxide materials. We develop and use a coupled quantum mechanical and molecular dynamics approach to create thermodynamic models of hafnia (HfO2) polymorphs from 0 K to 3000 K at ambient pressure. The approach is based on the quasi-harmonic approximation below the Debye temperature and on ab-initio molecular dynamics calculations above the Debye temperature to predict constant pressure heat capacities (C-p). A Bayesian model provides interpolated values between these regimes. As a case study, we develop thermodynamic models of monoclinic and tetragonal HfO2 polymorphs. The predicted heat capacities are in excellent agreement with experiment, and the predicted temperature of the monoclinic to tetragonal phase transition (2173 K) is in good agreement with the experimental value (2078K). These results provide a comprehensive and accurate thermodynamic model of the monoclinic and tetragonal phases of hafnia on a broad range of temperatures and can serve as input to CALPHAD assessment of multi-component hafnia-based phase diagrams.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗
DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗