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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Activity Coefficients of Siderophile Elements in Fe-Si Liquids at High Pressure

Metallic core formation in differentiated bodies in the inner solar system can takeplace between low pressures (near 1 bar) to much higher pressures (up to 100 GPa). Mostthermodynamic models of metal-silicate equilibria utilize activity coefficients for metallic tracersin Fe liquids, nearly all of which have been carried out at low pressures. This study focuses onthe effect of pressure on activity coefficients for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb inliquid Fe-Si alloys. From a series of experiments at 10 GPa, 2373 K containing variable Sicontent in a metallic liquid we have derived epsilon interaction parametersin FeSi liquids (εMSi). Comparison of 1 GPa and 10 GPa data shows no difference except for Nb. Epsilonparameters derived from low pressure experiments can thus be used to calculate activitycoefficients for application to higher pressure processes (at least to 10 GPa).

K Righter↗
DOE OSTI2025

Mesoscale Modeling Approach for Quantifying Microstructure-Aware Micromechanical Responses in Metal Hydrides

Metal hydrides can undergo significant volume changes upon hydrogen uptake and release, which induce a mechanical response that depends not only on the evolving hydrogen composition but also on the microstructure. We present a comprehensive mesoscale modeling framework based on microelasticity theory to quantify the micromechanical responses of metal hydrides, specifically focusing on a hydrogenating polycrystalline MgH 2x particle within a host material as a model micromechanical system. Utilizing digitally generated realistic microstructures and density-functional-theory-derived parameters, we analyzed highly nonuniform local stress profiles in the polycrystalline hydrides under the clamping force exerted by the host during hydrogenation. Our framework also allows us to predict the corresponding strain energy accumulation and mechanical hot spots formation in the hydrides, highlighting their roles in thermodynamic destabilization and mechanical failure, respectively. Through extensive parametric simulations, we further quantified the influence of interface type, crystallinity, grain size, loading ratio, and host stiffness, providing practical guidance for optimizing microstructural design and host material selection. This proposed approach is broadly applicable to micromechanical systems with complex microstructural features involving chemical reaction- and/or phase-transformation-induced deformation.

36 MATERIALS SCIENCE↗
NASA NTRS1993

On the Shape of Liquid Metal Droplets in Electromagnetic Levitation Experiments

We present calculations and measurements on the shape of liquid metal droplets in electromagnetic levitation experiments. A normal stress balance model was developed to predict the shapes of liquid metal droplets that will be obtained in a microgravity experiment to measure the viscosity and surface tension of undercooled metals. This model was tested by calculating the droplet shapes in containerless experiments conducted to determine the surface tension of liquid metals. Inconsistencies associated with the results of a previous paper are elucidated. The computational results of the mathematical model are compared with the results of ground-based experiments for two different metals. The importance of the ratio of electromagnetic skin depth-to-droplet radius to the accuracy of the mathematical model is discussed. A planned alternate approach to modeling the shape by consideration of the entire droplet rather than only the surface is presented. As an example of an application. the influence of the shape on the splitting of the surface oscillation modes of levitated liquid metal droplets is discussed.

Schwartz, E.↗
DOE OSTI2023

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗
DOE OSTI2024

Time-Resolved X-ray Emission Spectroscopy and Synthetic High-Spin Model Complexes Resolve Ambiguities in Excited-State Assignments of Transition-Metal Chromophores: A Case Study of Fe-Amido Complexes

To fully harness the potential of abundant metal coordination complex photosensitizers, a detailed understanding of the molecular properties that dictate and control the electronic excited-state population dynamics initiated by light absorption is critical. In the absence of detectable luminescence, optical transient absorption (TA) spectroscopy is the most widely employed method for interpreting electron redistribution in such excited states, particularly for those with a charge-transfer character. The assignment of excited-state TA spectral features often relies on spectroelectrochemical measurements, where the transient absorption spectrum generated by a metal-to-ligand charge-transfer (MLCT) electronic excited state, for instance, can be approximated using steady-state spectra generated by electrochemical ligand reduction and metal oxidation and accounting for the loss of absorptions by the electronic ground state. However, the reliability of this approach can be clouded when multiple electronic configurations have similar optical signatures. Using a case study of Fe(II) complexes supported by benzannulated diarylamido ligands, we highlight an example of such an ambiguity and show how time-resolved X-ray emission spectroscopy (XES) measurements can reliably assign excited states from the perspective of the metal, particularly in conjunction with accurate synthetic models of ligand-field electronic excited states, leading to a reinterpretation of the long-lived excited state as a ligand-field metal-centered quintet state. Furthermore, a detailed analysis of the XES data on the long-lived excited state is presented, along with a discussion of the ultrafast dynamics following the photoexcitation of low-spin Fe(II)-N amido complexes using a high-spin ground-state analogue as a spectral model for the 5 T 2 excited state.

14 SOLAR ENERGY↗
DOE OSTI2020

Activity coefficients of siderophile elements in Fe-Si liquids at high pressure

Metallic core formation in differentiated bodies in the inner solar system can take place between low pressures (near 1 bar) to much higher pressures (up to 100 GPa). Most thermodynamic models of metal-silicate equilibria utilise activity coefficients for metallic tracers in Fe liquids, nearly all of which have been carried out at low pressures. This study focuses on the effect of pressure on activity coefficients for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb in liquid Fe-Si alloys. From a series of experiments at 10 GPa, 2373 K containing variable Si content in a metallic liquid we have derived epsilon interaction parameters in Fe-Si liquids ($ε^{Si}_{M}$). Comparison of 1 GPa and 10 GPa data shows no difference except for Nb. Epsilon parameters derived from low pressure experiments can thus be used to calculate activity coefficients for application to higher pressure processes (at least to 10 GPa).

58 GEOSCIENCES↗
NASA NTRS1973

Characterization of fines from the Apollo 16 site

We describe the characteristics of Apollo 16 fines samples 61281,8; 65701,13; 66031,6; 67701,26; and 67712,16 observed microscopically during the course of size and magnetic separations. Sample 67712,16 is unique in that almost all grains are rounded and no glass welded aggregates are present. All samples except 67712,16 contained about 0.5 wt.% of metal fragments 45 microns or more in diameter including occasional spheres and large single crystals. Some of this metal showed rust spots. Moessbauer spectra showed all the samples to be high in olivine compared to samples from other Apollo sites and to vary significantly in modal composition from each other. The fine grained Fe metal content and the excess absorption area near zero velocity in the Moessbauer spectra both vary with particle size and regolith maturity in the way one would predict from our model of Fe metal reduction and agglomeration during glass aggregate formation.

Housley, R. M.↗
NASA NTRS1988

Finite element (MARC) solution technologies for viscoplastic analyses

A need for development of realistic constitutive models for structural components operating at high temperatures, accompanied by appropriate solution technologies for stress/life analyses of these components is studied. Viscoplastic models provide a better description of inelastic behavior of materials, but their mathematical structure is very complex. The highly nonlinear and stiff nature of the constitutive equations makes analytical solutions difficult. Therefore, suitable solution, finite element or other numerical, technologies must be developed to make these models adaptable for better and rational designs of components. NASA-Lewis has developed several solution technologies and successfully applied them to the solution of a number of uniaxial and multiaxial problems. Some of these solution technologies are described along with the models and representative results. The solution technologies developed and presented encompass a wide range of models, such as, isotropic, anisotropic, metal matrix composites, and single crystal models.

Arya, V. K.↗
NASA NTRS2023

First VLTI/GRAVITY Observations of HIP 65426 b: Evidence for a Low or Moderate Orbital Eccentricity

Giant exoplanets have been directly imaged over orders of magnitude of orbital separations, prompting theoretical and observational investigations of their formation pathways. In this paper, we present new VLTI/GRAVITY astrometric data of HIP 65426 b, a cold, giant exoplanet which is a particular challenge for most formation theories at a projected separation of 92 au from its primary. Leveraging GRAVITY's astrometric precision, we present an updated eccentricity posterior that disfavors large eccentricities. The eccentricity posterior is still prior dependent, and we extensively interpret and discuss the limits of the posterior constraints presented here. We also perform updated spectral comparisons with self-consistent forward-modeled spectra, finding a best-fit ExoREM model with solar metallicity and C/O = 0.6. An important caveat is that it is difficult to estimate robust errors on these values, which are subject to interpolation errors as well as potentially missing model physics. Taken together, the orbital and atmospheric constraints paint a preliminary picture of formation inconsistent with scattering after disk dispersal. Further work is needed to validate this interpretation. Analysis code used to perform this work is available on GitHub: https://github.com/sblunt/hip65426.

Sarah Blunt↗
DOE OSTI2021

Analytical models of the strength and ductility of CNT reinforced metal matrix nano composites under elevated temperatures

Carbon nanotubes (CNTs) can greatly enhance the strength of metal matrix composites while resulting in ductility loss. This strength-ductility tradeoff dilemma always confines the development of material design and real-life applications. Here in this work, a temperature dependent strengthening analytical model is proposed for CNT reinforced metal matrix composites which considers three common strengthening mechanisms: Orowan looping effect, thermal expansion mismatch effect, and load bearing effect. The proposed model can predict composite material strength with different volume fractions of CNTs and under different temperatures. Combining the strengthening model with the stress based modified Mohr-Coulomb (sMMC) ductile fracture model, a ductility analytical model is then derived. This ductility analytical model includes the influences of temperature, multi-axial stress loading conditions, as well as the aforementioned three strengthening mechanisms. A good agreement has been achieved between literature published experimental data and analytical predictions for both composite material strength and ductility loss. The proposed two analytical models can provide a straightforward way to study the strength-ductility relationship for CNT reinforced metal matrix composites over a wide range of temperatures and different stress states, and then provide guidance on new material design and processing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions

Abstract To generate material models with fewer limiting assumptions while maintaining closed-form, interpretable solutions, we propose using genetic programming based symbolic regression (GPSR), a machine learning (ML) approach that describes data using free-form symbolic expressions. To maximize interpretability, we start from an analytical, derived material model, the Gurson model for porous ductile metals, and systematically relax inherent assumptions made in its derivation to understand each assumption’s contribution to the GPSR model forms. We incorporate transfer learning methods into the GPSR training process to increase GPSR efficiency and generate models that abide by known mechanics of the system. The results show that regularizing the GPSR fitness function is critical for generating physically valid models and illustrate how GPSR allows a high level of interpretability compared with other ML approaches. The method of systematic assumption relaxation allows the generation of models that address limiting assumptions found in the Gurson model, and the symbolic forms allow conjecture of decreased material strength due to void interaction and non-symmetric void shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unraveling the Correlation between Raman and Photoluminescence in Monolayer MoS 2 through Machine‐Learning Models

Abstract 2D transition metal dichalcogenides (TMDCs) with intense and tunable photoluminescence (PL) have opened up new opportunities for optoelectronic and photonic applications such as light‐emitting diodes, photodetectors, and single‐photon emitters. Among the standard characterization tools for 2D materials, Raman spectroscopy stands out as a fast and non‐destructive technique capable of probing material's crystallinity and perturbations such as doping and strain. However, a comprehensive understanding of the correlation between photoluminescence and Raman spectra in monolayer MoS 2 remains elusive due to its highly nonlinear nature. Here, the connections between PL signatures and Raman modes are systematically explored, providing comprehensive insights into the physical mechanisms correlating PL and Raman features. This study's analysis further disentangles the strain and doping contributions from the Raman spectra through machine‐learning models. First, a dense convolutional network (DenseNet) to predict PL maps by spatial Raman maps is deployed. Moreover, a gradient boosted trees model (XGBoost) with Shapley additive explanation (SHAP) to bridge the impact of individual Raman features in PL features is applied. Last, a support vector machine (SVM) to project PL features on Raman frequencies is adopted. This work may serve as a methodology for applying machine learning to characterizations of 2D materials.

Lu, Ang‐Yu↗
DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗
NASA NTRS2004

Cyclic Oxidation Modeling and Life Prediction

The cyclic oxidation process can be described as an iterative scale growth and spallation sequence by a number of similar models. Model input variable include oxide scale type and growth parameters, spalling geometry, spall constant, and cycle duration. Outputs include net weight change, the amounts of retained and spalled oxide, the total oxygen and metal consumed, and the terminal rates of weight loss and metal consumption. All models and their variations produce a number of similar characteristic features. In general, spalling and material consumption increase to a steady state rate, at which point the retained scale approaches a constant and the rate of weight loss becomes linear. For one model, this regularity was demonstrated as dimensionless, universal expressions, obtained by normalizing the variables by critical performance factors. These insights were enabled through the use of the COSP for Windows cyclic oxidation spalling program.

Smialek, James L.↗
DOE OSTI2021

The Effect of Mechanical State on the Equilibrium Potential of Alkali Metal/Ceramic Single–Ion Conductor Systems

The relationship between mechanical stress states and interfacial electrochemical thermodynamics of Li metal/Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 and Na metal/ Na-β”-Al 2 O 3 systems are examined in two experimental configurations with an applied uniaxial load; the solid electrolytes are pellets and the metal electrodes high-aspect-ratio electrodes. The experimental results demonstrate that 1) the change in equilibrium potential at the metal/electrolyte interface, when stress is applied to the metal electrode, is linearly proportional to the molar volume of the metal electrode, and 2) the mechanical stress in the electrolyte has a negligible effect on the equilibrium potential for an experimental setup in which the electrolyte is stressed and the electrode is left unstressed. Solid mechanics modeling of a metal electrode on a solid electrolyte pellet indicates that pressure and normal stress are within ≈0.5 MPa of each other for the high aspect ratio (≈1:100 thickness:diameter in our study) Li metal electrodes under loads that exceed yield conditions. Furthermore, this work should aid in advancing the quantitative understanding of alkali metal dendrite formation within incipient cracks and their subsequent growth, and pore formation upon stripping, both situations where properly accounting for the impact of mechanical state on the equilibrium potential is of critical importance for calculating the current distribution.

25 ENERGY STORAGE↗
DOE OSTI2025

Unconventional low temperature decomposition of a saturated hydrocarbon over atomically-dispersed titanium-aluminum-boron catalyst

Sonochemically-synthesized atomically-dispersed titanium-aluminum-boron nanopowder (TiAlB NP) exhibits a remarkable low-temperature catalytic activation of aliphatic C-H bonds at 750 K followed by C-C bond activation thus emerging as a potent low-cost alternative to expensive platinum group metals. Here, the model saturated hydrocarbon, exo-tetrahydrodicyclopentadiene (C10H16), undergoes catalytic decomposition on TiAlB NPs in a chemical microreactor to produce 1,3-cyclopentadiene (c-C5H6), cyclopentene (c-C5H8), and molecular hydrogen (H2) as detected in situ via isomer-selective, single-photon ionization time-of-flight mass spectrometry. Extensive electronic structure theory calculations on model clusters of the catalyst decode a unique synergy among the atomic constituents of the catalyst and chemical bonding in this stepwise, retro Diels Alder reaction: Ti, although insensitive to C-H activation in its metallic state, initiates the catalysis via chemisorption of the hydrocarbon, adjacent B centers readily abstract hydrogen atoms and store them during the catalytic cycle, while Al stabilizes the catalyst structure yet providing space for critical docking sites for the departing hydrocarbons.

Biswas, Souvick↗
NASA NTRS1986

Life prediction and constitutive models for engine hot section anisotropic materials program

This report presents the results of the first year of a program designed to develop life prediction and constitutive models for two coated single crystal alloys used in gas turbine airfoils. The two alloys are PWA 1480 and Alloy 185. The two oxidation resistant coatings are PWA 273, an aluminide coating, and PWA 286, an overlay NiCoCrAlY coating. To obtain constitutive and/or fatigue data, tests were conducted on coated and uncoated PWA 1480 specimens tensilely loaded in the 100 , 110 , 111 , and 123 directions. A literature survey of constitutive models was completed for both single crystal alloys and metallic coating materials; candidate models were selected. One constitutive model under consideration for single crystal alloys applies Walker's micromechanical viscoplastic formulation to all slip systems participating in the single crystal deformation. The constitutive models for the overlay coating correlate the viscoplastic data well. For the aluminide coating, a unique test method is under development. LCF and TMF tests are underway. The two coatings caused a significant drop in fatigue life, and each produced a much different failure mechanism.

Swanson, G. A.↗
NASA NTRS2004

Chemical models for simulating single-walled nanotube production in arc vaporization and laser ablation processes

Chemical kinetic models for the nucleation and growth of clusters and single-walled carbon nanotube (SWNT) growth are developed for numerical simulations of the production of SWNTs. Two models that involve evaporation and condensation of carbon and metal catalysts, a full model involving all carbon clusters up to C80, and a reduced model are discussed. The full model is based on a fullerene model, but nickel and carbon/nickel cluster reactions are added to form SWNTs from soot and fullerenes. The full model has a large number of species--so large that to incorporate them into a flow field computation for simulating laser ablation and arc processes requires that they be simplified. The model is reduced by defining large clusters that represent many various sized clusters. Comparisons are given between these models for cases that may be applicable to arc and laser ablation production. Solutions to the system of chemical rate equations of these models for a ramped temperature profile show that production of various species, including SWNTs, agree to within about 50% for a fast ramp, and within 10% for a slower temperature decay time.

Nanotubes, Carbon/chemistry↗