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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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85 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Experimental Techniques for Thermodynamic Measurements of Ceramics

Experimental techniques for thermodynamic measurements on ceramic materials are reviewed. For total molar quantities, calorimetry is used. Total enthalpies are determined with combustion calorimetry or solution calorimetry. Heat capacities and entropies are determined with drop calorimetry, differential thermal methods, and adiabatic calorimetry . Three major techniques for determining partial molar quantities are discussed. These are gas equilibration techniques, Knudsen cell methods, and electrochemical techniques. Throughout this report, issues unique to ceramics are emphasized. Ceramic materials encompass a wide range of stabilities and this must be considered. In general data at high temperatures is required and the need for inert container materials presents a particular challenge.

Jacobson, Nathan S.↗
DOE OSTI2022

Direct utilization of gaseous fuels in metal supported solid oxide fuel cells

Direct utilization and internal reforming of gaseous fuels is investigated on symmetric-architecture metal supported solid oxide fuel cells (MS-SOFCs) with thin ceramic electrolyte and scaffold backbone layers, and low cost ferritic stainless steel supports on both sides. Infiltrated Pr-oxide and Ni/samarium-doped ceria catalysts are added to the cathode and anode electrodes, respectively. Initial performance and durability is evaluated for MS-SOFCs operating with natural gas, propane, ammonia, and dimethyl ether at 700 °C. Cells for natural gas and propane utilize a novel high entropy alloy (HEA) catalyst for internal reforming with performance and degradation rates similar to H 2 (0.5W cm -2 and ~12%/100 h). In conclusion, initial testing with sulfur shows reversible degradation for levels found in natural gas and irreversible degradation for higher levels found in commercial propane. Overall, MS-SOFCs show successful fuel flexibility.

08 HYDROGEN↗
DOE OSTI2024

Solid State Reduction Driven Synthesis of Mn Containing Multi-principal Component Alloys

In recent years, high entropy alloys (HEAs), also known as multi-principal component alloys (MPCAs) have emerged as a new and exciting class of materials. This paper reports on the solid state reduction synthesis of a series of CoFeNiMn-based MPCA compositions, starting from a mixture of the corresponding oxides. One of the aims of the study was to test whether the degree of reduction of MnO, a highly stable oxide, could be enhanced by tailoring the alloy composition. Specifically, the influence of Ni content was studied because Ni exhibits a significant negative enthalpy of mixing with Mn. High purity precursor powders of Co(OH) 2 , Fe 2 O 3 , MnO 2 , and NiO were milled and mixed using standard ceramic processing methods. Here, the nominal sample compositions (assuming complete oxide reduction) were (CoFeMn) x Ni (1-x) , for x = 0, 0.083, 0.166, and 0.25. The oxide samples were subjected to a series of isothermal reduction anneals in flowing 3 pct H 2 –Ar at 1100 °C. The resulting microstructures were characterized using scanning electron microscopy (SEM), X-ray energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD). The composition of the resulting MPCAs was determined quantitatively using wavelength dispersive spectroscopy (WDS) in the electron microprobe. The study revealed that for each of the initial oxide compositions studied, it was possible to achieve an MPCA with ~ 25 at. pct Mn. These results were found to be consistent with the predictions of a thermodynamic model whereby a negative enthalpy of mixing (ΔH mix ), combined with a contribution from configurational entropy, can offset a positive free energy of reduction (ΔG red ). The incorporation of vibrational entropy into first principles calculations was found to have a significant effect on the predicted crystal structure of the MPCAs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring the structural durability and proton conductivity of electrolytes for highly fuel-flexible and reversible ceramic cells

A durable and high ionic conducting electrolyte is critical for achieving fuel-flexible and reversible protonic ceramic cells (PCCs) at reduced temperatures since the developed electrolyte materials are vulnerable to steam, CO 2 , or coking deterioration. Here, we report a fast-conducting electrolyte material BaZr 0.06 Ce 0.7 Y 0.06 Yb 0.06 Hf 0.06 Gd 0.06 O 3−δ (BZCYYbHG), demonstrating excellent durability against CO 2 and H 2 O under the realistic electrolysis operations, and a high conductivity of 0.017 S cm −1 at 550 °C for lowering the PCC operating temperature. Further, density functional theory calculations indicate that the higher configurational entropy of mixing at the B-site cations slightly reduces the hydrogen adsorption energy, suggesting a higher incorporation rate of protons or hydrogen atoms into the electrolyte bulk. Ultimately, single cells with the BZCYYbHG electrolyte deliver peak power densities of 1.39, 1.12, and 0.7 W cm −2 in H 2 , NH 3 , and wet CH 4 at 550 °C with promising durability. In addition, the PCCs achieve a current density of −1.61 A cm −2 at 1.3 V and 550 °C with a high faradaic efficiency of 91.3% at −0.5 A cm −2 , enabling stable operations in steam electrolysis mode under humid air (30% H 2 O), wet air containing CO 2 (up to 10%), and reversible cycling.

25 ENERGY STORAGE↗
NASA NTRS2018

Scale-Resolving Simulations of Low-Pressure Turbine Cascades with Wall Roughness Using A Spectral-Element Method

The accurate prediction of wall-roughness effects in turbomachinery is becoming critical as turbine designers address airfoil surface quality and degradation concerns arising from the shift to advanced ceramic matrix composite (CMC) or additively-manufactured airfoils operating in higher temperature environments. In this paper, a recently developed computational capability for accurate and efficient scale-resolving simulations of turbomachinery is extended to analyze the boundary- layer separation and transition characteristics in a rough-wall low-pressure turbine (LPT) cascade. The computational capability is based on an entropy-stable discontinuous-Galerkin spectral-element approach that extends to arbitrarily high orders of spatial and temporal accuracy, and is implemented in an efficient manner for a modern high performance computer architecture. Results from the scale-resolving simulations of both smooth and rough airfoil cascades are presented and compared to previous experiments and numerical simulations. The results show that the suction surface boundary layer undergoes laminar separation, transition, and turbulent reattachment for the smooth airfoil cascade, while in the presence of roughness the separation and transition behavior of the suction surface boundary layer is substantially modified. The differences between the smooth and rough airfoil cascades are then highlighted by a detailed analysis of their respective turbulent flow fields.

Spectral-Element↗
DOE OSTI2022

What is in a name: Defining “high entropy” oxides

High entropy oxides are emerging as an exciting new avenue to design highly tailored functional behaviors that have no traditional counterparts. Study and application of these materials are bringing together scientists and engineers from physics, chemistry, and materials science. The diversity of each of these disciplines comes with perspectives and jargon that may be confusing to those outside of the individual fields, which can result in miscommunication of important aspects of research. In this Perspective, we provide examples of research and characterization taken from these different fields to provide a framework for classifying the differences between compositionally complex oxides, high entropy oxides, and entropy stabilized oxides, which is intended to bring a common language to this emerging area. We highlight the critical importance of understanding a material’s crystallinity, composition, and mixing length scales in determining its true definition.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
NASA NTRS1990

Heat transfer in space systems; Proceedings of the Symposium, AIAA/ASME Thermophysics and Heat Transfer Conference, Seattle, WA, June 18-20, 1990

Theoretical and experimental studies of heat-tranfer in a space environment are discussed in reviews and reports. Topics addressed include a small-scale two-phase thermosiphon to cool high-power electronics, a low-pressure-drop heat exchanger with integral heat pipe, an analysis of the thermal performance of heat-pipe radiators, measurements of temperature and concentration fields in a rectangular heat pipe, and a simplified aerothermal heating method for axisymmetric blunt bodies. Consideration is given to entropy production in a shock wave, bubble-slug transition in a two-phase liquid-gas flow under microgravity, plasma arc welding under normal and zero gravity, the Microgravity Thaw Experiment, the flow of a thin film on stationary and rotating disks, an advanced ceramic fabric body-mounted radiator for Space Station Freedom phase 0 design, and lunar radiators with specular reflectors.

Chan, S. H.↗
DOE OSTI2023

High-entropy materials: fundamentals and applications

Metallic high-entropy materials (HEMs), also known as high-entropy alloys (HEAs), are an exotic class of materials that possess desirable properties, such as exceptional strength and ductility, high wear resistance, and corrosion resistance. Due to these positive attributes, HEAs have been proposed for use in the automotive and aerospace industries, nuclear reactor technology, and the biomedical field. In terms of composition, HEAs contain five or more elements in amounts ranging from 5 to 35 atomic percent (at.%) each, resulting in a vast compositional space that is still mainly unexplored to this day. More recently, the field of HEMs has broadened to include materials such as polymers and ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ab-initio informed cluster dynamics simulation of self- and Xe diffusivity in uranium mononitride under irradiation

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuels considered for light water reactor and advanced reactor designs, as it presents significant advantages such as high uranium density (better economics) and high thermal conductivity and melting point (increased safety). Self- and fission gas diffusivities need to be better understood, given that they influence key fuel performance phenomena like swelling and fission gas release. Recently, radiation enhanced diffusivity was investigated in UN by means of cluster dynamics simulations relying on empirical potential-based parameterizations, the reliability of which highly depends on the interatomic potential accuracy. Here, in this work, we refine this approach by determining, using ab-initio calculations, the properties of defect clusters containing vacancies, self-interstitials and Xe impurities. We also consider larger clusters than previous studies. The obtained dataset (formation enthalpies, entropies, and migration barriers) is used to parameterize a cluster dynamics model of mobile clusters, and to calculate the defect cluster concentrations under irradiation. This gives us access to the radiation enhanced self- and fission gas diffusivities. Although the resulting diffusivities are close to the values reported in the literature, we find important qualitative differences in the diffusion mechanisms. Capturing the correct mechanisms is crucial to properly describe the chemistry and fission rate dependence of the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Complex Oxide Nanoparticle Synthesis: Where to Begin to Do It Right?

Synthesis of advanced ceramics requires a high degree of control over the particle size and stoichiometry of the material. When choosing a synthesis method for complex oxides it is important to begin with the correct precursors and solvents to achieve high purity nanoparticles. Here, we detail the selection process for precursors and solvents for liquid-phase precipitation synthesis. Data for metal nitrate, chloride, acetate, and oxalate precursors has been compiled to assist future synthesis. The role of hydration within the precursors is discussed as it affects the final stoichiometry of the material. Melting temperatures are also compiled for these compounds to assist in material selection. The solubility of the precursors in different solvents is examined to determine the correct solvent during synthesis. As an example, using the methodology presented here, two different materials are synthesized based on commonly available precursors. A catalyst based on a quaternary perovskite and an advanced ionic conductor based on a high entropy fluorite oxide are synthesized using precipitation methods and their characterization is detailed.

Gager, Elizabeth (ORCID:0000000306046571)↗
DOE OSTI2025

Yttrium Contenting Compositionally Complex Medium-Entropy Li-Garnet Electrolyte with Improved Ionic Conductivity

The compositionally complex medium/high-entropy design concept can greatly expand the categories and affect the properties of the materials. With such a designing concept, a medium-entropy Li-garnet electrolyte with appropriate yttrium content (formula Li 6.6 La 3 ZrNb 0.3 Ta 0.3 Hf 0.3 Y 0.1 O 12 ) shows a record-high ionic conductivity of ∼5.7 × 10 –4 S/cm, the highest reported for any single-site substituted high/medium-entropy Li-garnet. The assembled Li metal symmetric cells also show stable long-term cycling (0.1 mA/cm 2 for over 200 h). Neutron powder diffraction and Rietveld refinement results indicate that a competing conduction mechanism between (1) occupancy on high mobility of 96h sites and (2) the associated site vacancies and the bond length requires an appropriate content of Y for enhanced ionic conductivity. Li-ion hopping through the bottleneck can also contribute to the conductivity. Finally, density functional theory and Born–Oppenheimer molecular dynamics simulations also indicate the high mobility and number of hopping transitions of Li ions, contributing to the high ionic conductivity.

Li-garnet↗
DOE OSTI2023

Phase evolution during conventional and reactive flash sintering of (Mg,Ni,Co,Cu,Zn)O via in situ X-ray diffraction

Reactive flash sintering (RFS) enables the simultaneous synthesis and sintering of ceramics and has been shown to affect the reaction pathway of different materials. Herein, in situ synchrotron X-ray diffraction (XRD) is used to investigate the (Mg,Ni,Co,Cu,Zn)O entropy-stabilized oxide formation during: (i) conventional heating and (ii) RFS under current rate-controlled mode. The same reaction pathway is verified in both instances: the starting rock-salt (RS), spinel (Co 3 O 4 ), tenorite (CuO), and wurtzite (ZnO) phases transform into a single RS phase with a (1 1 1) to (2 0 0) intensity ratio of 0.67, consistent with a random distribution of the cations into the structure. Pt lattice peak shift from the XRD patterns is used as standard to monitor the sample surface temperature, revealing a strong endothermic reaction during the RS single-phase formation (Pt peaks shift toward higher angles while increasing sample temperature/current density). Furthermore, in RFS, the single-phase RS structure is formed in just 60 s at a furnace temperature of 600°C and a current rate of 220 mA mm -2 /min. Therefore, RFS greatly accelerates the synthesis of (Mg,Ni,Co,Cu,Zn)O, however, it does not play a role in the reaction pathway for this material formation.

36 MATERIALS SCIENCE↗