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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The heat capacity of titanium disilicide

The heat capacity of TiSi2 has been measured in the temperature range 105-500 K. The heat capacity of TiSi2 varies monotonically between temperatures of 100 and 500 K with a reference value of 22.0 +/- 0.2 J/g atom K at 298.15 K. Based upon our heat capacity data, the standard molar entropy of TiSi2 at 298.15 K estimated to be 22.2 +/- 0.8 J/g atom K. Our data support estimates of the higher temperature heat capacity of TiSi2 based upon previously measured heat capacities of different, but similar, substances. A number of TiSi2 samples were prepared by rapidly quenching (greater than 10(exp 5) K/s) from the melt. The structure and the measured heat capacity of these samples were similar to those of well annealed samples, underscoring the thermal stability of this material.

Sylla, W. K.↗
DOE OSTI2019

Magnetocaloric Effect and Critical Behavior Investigations in La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} Manganite Oxide

Structural, magnetic, and magnetocaloric effect (MCE) properties and the critical behavior of the La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} sample prepared by the sol–gel method have been investigated. The X-ray diffraction characterization reveals that our sample crystallizes in the orthorhombic structure with Pnma space group. Magnetization versus temperature measurement shows that our compound exhibits a ferromagnetic–paramagnetic transition. The Curie temperature is found to be 348 K. Close to this temperature, the maximum values of the magnetic entropy change (ΔS{sub M}) and the relative cooling power (RCP) are found to be 2.84 J/kg/K and 230 J/K under µ{sub 0}H = 5 T, respectively. The Arrott plots revealed that this compound exhibits a second-order magnetic phase transition at T{sub C}. The critical behavior has been investigated by several techniques which are the modified Arrott plot method, the Kouvel–Fisher method, and the critical isotherm analysis. The obtained critical exponents β, γ, and δ are consistent with those predictions of the mean-field model. Their reliability was confirmed by Widom’s scaling relation, as well as the universal scaling hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Predicting Thermochemical Equilibria with Interacting Defects: Sr 1 − x Ce x Mn O 3 − δ Alloys for Water Splitting

Solar thermochemical hydrogen is one of the few potential routes towards direct fuel production from renewable energy sources, but the thermodynamic boundary conditions for efficient and economic energy conversion are challenging. Success or failure of a given oxide working material depends on the subtle balance between enthalpy and entropy contributions in the redox processes. Developing a mechanistic understanding of the behavior of materials on the basis of atomistic models and first-principles calculations is an important part of advancing the technology. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox-active defects start to interact with each other, thereby impeding the formation of additional defects. This problem is of more general importance to applications that rely on high levels of off-stoichiometry or doping, including, for example, batteries, thermoelectrics, and ceramic fuel cells. To account for such repulsive defect interactions, we introduce a statistical mechanics approach, defining an expression for the free energy of defect interaction based on limited sampling of defect configurations in density functional theory supercell calculations. The parameterization of this energy contribution as a function of defect concentration and temperature allows on-the-fly simulation of thermochemical equilibria. The approach consistently incorporates finite temperature effects by including the leading contributions to the temperature-dependent free energy for the case at hand, i.e., the ideal gas and configurational enthalpies and entropies. We demonstrate the capability and utility of the approach by simulating the water splitting redox processes for Sr 1 − x Ce x Mn O 3 − δ alloys. Published by the American Physical Society 2024

08 HYDROGEN↗
DOE OSTI2015

Design and Validation Testing of TruckScan to Assay Large Sacks of Fukushima Radioactive Debris on a Truck

As a result of the March 2011 earthquake and resulting tsunami in Japan, there was a serious accident at the Fukushima Dai-ichi Nuclear Power Plant. This accident has contaminated soil and vegetation in a wide area around the plant. Decontamination projects over the last 4 years have resulted in large numbers of 1 cubic meter canvas bags of debris, commonly called Super Sacks [SS]. These are currently stored nearby where they were generated, but starting in 2015, they will be moved to various Interim Storage Facilities [ISF]. Trucks will typically carry 8-20 of these SSs. When the trucks arrive at the ISF they need to be rapidly sorted into groups according to radioactivity level, for efficient subsequent processing. Canberra Industries, Inc. [CI] has designed a new truck monitoring system 'TruckScan' for use at these ISFs. The TruckScan system must measure the entire truck loaded with multiple closely packed SSs, and generate a nuclide specific assay report showing the radioactivity in each individual SS. The Canberra-Japan office, along with Obayashi Corporation have performed validation testing to demonstrate to the regulatory authorities that the proposed technique was sufficiently accurate. These validation tests were conducted at a temporary storage area in Fukushima prefecture. Decontaminated waste of various representative types and of various levels of radioactivity was gathered and mixed to create homogeneous volumes. These volumes were sampled multiple times and assayed with laboratory HPGe detectors to determine the reference concentration of each pile. Multiple SSs were loaded from each pile. Some of the SSs were filled 50% full, others 75% full, and others 100% full, to represent the typical loading configuration of the existing SSs in the field. The content of the SSs are either sand, soil, or vegetation with densities ranging from 0.3 g/cc - 1.6 g/cc. These SSs with known concentrations of Cs-134 and Cs-137 were then loaded onto trucks in a variety of configurations, typical of how they might be on the real trucks. A partial system was installed at the site and used to assay these trucks with the various loading configurations. Whereas the full system will have 8 collimated 3 x 3'' NaI detectors, the test system only had two detectors; therefore the truck was moved and counted 4 times. The data were acquired and analyzed with the Canberra Genie software to determine the peak counts for both Cesium nuclides. That data was then analyzed with a prototype version of a Maximum Entropy algorithm, to determine the individual SS activity. The goal of the validation tests was to demonstrate that the system could detect 1000 Bq/kg in 15 seconds, and to determine how accurately it could quantify individual SSs. The validation tests demonstrated that the product would perform as predicted. The TruckScan results were consistent with the sample assay results [y = 1.0029 x, R{sup 2} = 0.914]. The Total Propagated Uncertainty, including both uncertainties from these tests and others that were estimated but not tested was 16.6% percent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds

A minimax estimator has the minimum possible error (“risk”) in the worst case. Here we construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O (1/$\sqrt{N}$ ) —in contrast to that of classical probability estimation, which is O (1/N) —where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. Lastly, this makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Microstructure and Mechanical Behavior of High-Entropy Alloys

High entropy alloys (HEA) have generated interest in recent years due to their unique positioning within the alloy world. By incorporating a number of elements in high proportion, usually of equal atomic percent, they have high configurational entropy, and thus, they hold the promise of interesting and useful properties such as enhanced strength and alloy stability. The present study investigates the mechanical behavior, fracture characteristics and microstructure of two singlephase FCC high-entropy alloys (HEA's) CoCrFeNi and CoCrFeNiMn with some detailed attention given to melting, homogenization and thermo-mechanical processing. Ingots approaching 8 kg in mass were made by vacuum induction melting (VIM) to avoid the extrinsic factors inherent to small scale laboratory button samples. A computationally based homogenization heat treatment was given to both alloys in order to eliminate any solidification segregation. The alloys were then fabricated in the usual way (forging, followed by hot rolling) with typical thermo-mechanical processing parameters employed. Transmission electron microscopy (TEM) was subsequently used to assess the single phase nature of the alloys prior to mechanical testing. Tensile specimens (ASTM E8) were prepared with tensile mechanical properties obtained from room temperature through 800°C. Material from the gage section of selected tensile specimens was extracted to document room and elevated temperature deformation within the HEA's. Fracture surfaces were also examined to note fracture failure modes. The tensile behavior and selected tensile properties were compared with results in the literature for similar alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Synthesis of the p-type semiconducting ternary oxide CuAlO{sub 2} using the Pechini method

Graphical abstract: - Highlights: • We have prepared single-phase samples of the semiconducting oxide CuAlO{sub 2} using the Pechini method. • Reaction times are reduced relative to conventional solid-state synthesis. • Products have high surface area suitable for ceramic processing. • Product composition is dictated by thermodynamic control; CuAl{sub 2}O{sub 4} is obtained preferentially at lower temperature. - Abstract: The synthesis of the delafossite phase CuAlO{sub 2} using the Pechini method was investigated. Powder X-ray diffraction data showed that pure, single-phase samples were obtained after only 3 h heating at 1100 °C. CuAl{sub 2}O{sub 4}, which contains Cu(II) rather than Cu(I), was the dominant phase between 700 and 1100 °C. Conversion to CuAlO{sub 2} is promoted by the positive entropy change associated with the evolution of oxygen. No mixed Cu–Al oxide was formed below 700 °C.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Simplified Digital Subband Coders And Decoders

Simplified digital subband coders and decoders developed for use in converting digitized samples of source signals into compressed and encoded forms that maintain integrity of source signals while enabling transmission at low data rates. Examples of coding methods used in subbands include coarse quantization in high-frequency subbands, differential coding, predictive coding, vector quantization, and entropy or statistical coding. Encoders simpler, less expensive and operate rapidly enough to process video signals.

Glover, Daniel R.↗
DOE OSTI2024

Effects of electron beam irradiation on CrMnV and CrMnTiV high entropy alloys: Nano-mechanical, structural, and thermodynamic perspectives

Beam exit windows are crucial components of any particle accelerator as they provide an interface between the beamline vacuum and target material at atmospheric media. For high beam power machines, special materials and designs are required to withstand high radiation and mechanical loads, while minimizing energy loss during transition and maximizing window lifetime. This research investigates the impact of electron beam exposure to bulk CrMnV and CrMnTiV high entropy alloys (HEAs) with the primary goal of identifying suitable candidate materials for the design of robust and durable exit window settings. The selection criteria include intrinsic characteristics, power dissipation, and mechanical responses. According to the thermodynamic calculations, both equiatomic CrMnV and the addition of 7% of Ti with equiatomic CrMnV yield solid-solutions phases. The structural and mechanical properties of CrMnV and CrMnTiV samples were tested using field emission scanning electron microscopy, atomic force microscopy, scanning electron microcopy with energy dispersive x-ray spectroscopy, x-ray diffraction, and nanoindentation before and after exposure to a dose of ~66 kGy from a 10 MeV e-beam accelerator. Despite exhibiting beam transmission characteristics comparable to Cr and V, the indentation hardness of HEAs exceeded that of the Cr and V samples by five to six times. The examination of the CrMnTiV irradiated samples revealed organized deformation patterns depicting new features, which we suspect twinning and twin boundaries due to the addition of Ti to CrMnV. Ti, a hexagonal-close-packed crystal structure, is commonly known for deformation twinning behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model-free estimation of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Abstract An accurate description of information is relevant for a range of problems in atomistic machine learning (ML), such as crafting training sets, performing uncertainty quantification (UQ), or extracting physical insights from large datasets. However, atomistic ML often relies on unsupervised learning or model predictions to analyze information contents from simulation or training data. Here, we introduce a theoretical framework that provides a rigorous, model-free tool to quantify information contents in atomistic simulations. We demonstrate that the information entropy of a distribution of atom-centered environments explains known heuristics in ML potential developments, from training set sizes to dataset optimality. Using this tool, we propose a model-free UQ method that reliably predicts epistemic uncertainty and detects out-of-distribution samples, including rare events in systems such as nucleation. This method provides a general tool for data-driven atomistic modeling and combines efforts in ML, simulations, and physical explainability.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The effect of submicron grain size on thermal stability and mechanical properties of high-entropy carbide ceramics

(Hf 0.2 Zr 0.2 Ta 0.2 Nb 0.2 Ti 0.2 )C high-entropy ceramics (HEC) with a submicron grain size of 400 to 600 nm were fabricated by spark plasma sintering using a two-step sintering process. Both X-ray and neutron diffractions confirmed the formation of single-phase with rock salt structure in the as-fabricated (Hf 0.2 Zr 0.2 Ta 0.2 Nb 0.2 Ti 0.2 )C samples. The effect of submicron grain size on the thermal stability and mechanical properties of HEC was investigated. The grain growth kinetics in the fine-grained HEC was small at 1300 and 1600°C, suggesting high thermal stability that was possibly related to the compositional complexity and sluggish diffusion in HEC. Compared to the coarse-grain HEC with a grain size of 16.5 µm, the bending strength and fracture toughness of fine-grained HEC were 25% and 20% higher respectively. The improvement of mechanical properties in fine-grained HEC may be attributed to micromechanistic mechanisms such as crack deflection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Experimental investigation of thermal conductivity of high entropy ceramics

In this talk, we will present the experimental investigation of thermal conductivity of high entropy carbides (HEC) and borides (HEB) with different compositions. Thermal conductivity determines the capability of a material to transport thermal energy and is considered as one critical physical property, specially in the energy industry. Due to the presences of disordered cation sublattice, it is expected that thermal conductivity of high entropy ceramics is lower than the counterparts with simpler compositions, but the experimental studies are relatively few. Using laser-based spatial-domain and frequency-domain thermoreflectance technique, we measured thermal conductivity of HECs and HEBs in a temperature range from 77K to 773K. Furthermore, by focusing the laser using an objective lens, we were able to perform the thermal property mapping on samples with the spatial resolution of micrometer. Such measurements could reveal important microstructure information in a rapid and efficient way without using scanning electron microscopy. The high spatial resolution also enables thermal conductivity measurements on ion-irradiated HECs with the damage layer of merely 1.1µm. These measurements can provide valuable information to predict the performances of HECs and HEBs with different compositions and from different manufacturing processes, and in the extreme environments such as nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 10 6 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Nucleation rate controlled grain boundary and lattice creep

Nucleation versus diffusion rate-limited bicrystal and single crystal creep exhibit different scaling dependencies that enable the mechanisms to be isolated when measured as a function of sample size. It has recently been suggested that nucleation rate-limited kinetic models generally describe the non-Newtonian portion of the creep response well, but more direct evidence is required. This work analyzes the grain boundary creep response of UO 2 , a pyrochlore high entropy oxide, silver, and palladium, along with the lattice creep of silver using small-scale in situ loading in the transmission electron microscope. At small sizes, each system exhibits scale dependence associated with nucleation rate-limited kinetics. Fits of the data produce activation volumes on the order of a few Burgers vectors cubed with positive temperature coefficients as expected for nucleation kinetics. The activation enthalpies fall in the range of about 0.4 eV to 1.7 eV, being lower for the metals and higher for the oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Logical quantum processor based on reconfigurable atom arrays

Suppressing errors is the central challenge for useful quantum computing, requiring quantum error correction (QEC) for large-scale processing. However, the overhead in the realization of error-corrected ‘logical’ qubits, in which information is encoded across many physical qubits for redundancy, poses substantial challenges to large-scale logical quantum computing. Here we report the realization of a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. Using logical-level control and a zoned architecture in reconfigurable neutral-atom arrays, our system combines high two-qubit gate fidelities, arbitrary connectivity, as well as fully programmable single-qubit rotations and mid-circuit readout. Operating this logical processor with various types of encoding, we demonstrate improvement of a two-qubit logic gate by scaling surface-code distance from d = 3 to d = 7, preparation of colour-code qubits with break-even fidelities, fault-tolerant creation of logical Greenberger–Horne–Zeilinger (GHZ) states and feedforward entanglement teleportation, as well as operation of 40 colour-code qubits. Finally, using 3D [[8,3,2]] code blocks, we realize computationally complex sampling circuits with up to 48 logical qubits entangled with hypercube connectivity with 228 logical two-qubit gates and 48 logical CCZ gates. We find that this logical encoding substantially improves algorithmic performance with error detection, outperforming physical-qubit fidelities at both cross-entropy benchmarking and quantum simulations of fast scrambling. These results herald the advent of early error-corrected quantum computation and chart a path towards large-scale logical processors.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Neutrino-driven Outflows and the Elemental Abundance Patterns of Very Metal-poor Stars

Abstract The elemental abundances between strontium and silver ( Z = 38–47) observed in the atmospheres of very metal-poor stars in the Galaxy may contain the fingerprint of the weak r -process and ν p -process occurring in early core-collapse supernovae explosions. In this work, we combine various astrophysical conditions based on a steady-state model to cover the richness of the supernova ejecta in terms of entropy, expansion timescale, and electron fraction. The calculated abundances based on different combinations of conditions are compared with stellar observations, with the aim of constraining supernova ejecta conditions. We find that some conditions of the neutrino-driven outflows consistently reproduce the observed abundances of our sample. In addition, from the successful combinations, the neutron-rich trajectories better reproduce the observed abundances of Sr–Zr ( Z = 38–40), while the proton-rich ones, Mo–Pd ( Z = 42–47).

Astronomy & Astrophysics↗
DOE OSTI2021

Exceptionally high spallation strength for a high-entropy alloy demonstrated by experiments and simulations

High-entropy alloys are materials with an increasing number of technological applications. Amongst them, the Cantor alloy, FeMnCoCrNi, shows desirable mechanical properties at normal loading conditions. In this study we focus on the performance of the Cantor alloy at the ultra-high deformation rates of shock waves. We study shock-induced spallation using both experiments and atomistic simulations. Experimental loading is achieved using high power laser, with VISAR to obtain velocity profiles and spall strength, followed by transmission electron microscopy of the recovered samples. Molecular Dynamics (MD) simulations of shock-induced spallation are compared with experiments. Both experiments and simulations show a high spall strength which would be beneficial for certain applications, with experiments giving ~8 GPa at ~10 7 s -1 and MD giving almost ~30 GPa at ~10 9 s -1 . The difference between experiments and simulations can be explained by the difference in strain rate. Post-mortem analysis of the experimental samples shows nanotwins near the spall plane, while MD simulations show a highly disordered region giving rise to void nucleation and spall during loading.

36 MATERIALS SCIENCE↗