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Results for “high-entropy”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

The alpha-process and the r-process

The paper explores the alpha-rich freeze-out for values of neutron excesses larger than previously treated, and reports the discovery of nuclear systematics that, for neutron excesses greater than about 0.05, allow the creation of heavier elements all the way up to A of about 100, even when most of the ejecta is in the form of heavy elements. It is found that a large part of the nuclear flow in the r-process may be carried by charged particle reactions up to about A of about 100. It is speculated that the site of these processes is the high-entropy 'wind' of a young neutron star in which neutrino energy deposition is driving mass loss. The pass of r-process ejected per supernova is expected to be about 0.0001 solar mass per Type II or Ib supernova, but this is sensitive to details of the presupernova structure, the explosion mechanism, and the amount of material that falls back onto the neutron star when the reverse shock arrives there.

Woosley, S. E.↗
NASA NTRS1994

The delayed-detonation model of a type Ia supernovae. 1: The deflagration phase

The nature of the 'delayed detonation' mechanism of Khokhlov for the explosion of Type Ia supernovae is investigated by using two-dimensional numerical hydrodynamics simulations. A new algorithm is used to treat the deflagration front. Assuming that it propagates locally at the laminar flame speed, the deflagration is insufficient to unbind the star. Expansion shuts of the flame; much of this small production of iron group nuclei occurs at lower densities, which reduces the electron-capture problem. The burning front does become wrinkled, but the wavelength of the instability is much larger than the computational grid size and is resolved; this is consistent with previous analysis. Because the degenerate star has an adiabatic exponent only slightly above 4/3, the energy released by deflagration drives a pulsation of large amplitude. During the first expansion phase, adiabatic cooling shuts off the burning, and a Rayleigh-Taylor instability then gives mixing of high-entropy ashes with low-entropy fuel. During the first contraction phase, compressional heating reignites the material. This paper deals with the deflagration phase, from the onset of burning, through expansion and quenching of the flame, to the first contraction.

Arnett, David↗
NASA NTRS1994

The delayed-detonation model of Type Ia supernovae. 2: The detonation phase

The investigation, by use of two-dimensional numerical hydrodynamics simulations, of the 'delayed detonation' mechanism of Khokhlov for the explosion of Type Ia supernovae is continued. Previously we found that the deflagration is insufficient to unbind the star. Expansion shuts off the flame; much of this small production of iron group nuclei occurs at lower densities, which reduces the electron-capture problem. Because the degenerate star has an adiabatic exponent only slightly above 4/3, the energy released by deflagration drives a pulsation of large amplitude. During the first expansion phase, adiabatic cooling shuts off the burning, and a Rayleigh-Taylor instability then gives mixing of high-entropy ashes with low-entropy fuel. During the first contraction phase, compressional heating reignites the material. The burning was allowed to develop into a detonation in these nonspherical models. The detonation grows toward spherical symmetry at late times. At these densities (rho approx. 10(exp 7) to 10(exp 8) g cm(exp -3)), either Ni-56 or nuclei of the Si-Ca group are the dominant products of the burning. The bulk yields are sensitive to the density of the star when the transition to detonation occurs. The relevance of the abundances, velocities, mixing, and total energy release to the theory and interpretation of Type Ia supernovae is discussed.

Arnett, David↗
NASA NTRS2016

The Merging Galaxy Cluster A520 - A Broken-Up Cool Core, A Dark Subcluster, and an X-Ray Channel

We present results from a deep Chandra X-ray observation of a merging galaxy cluster A520. A high-resolution gas temperature map reveals a long trail of dense, cool clumpsapparently the fragments of a cool core that has been stripped from the infalling subcluster by ram pressure. The clumps should still be connected by the stretched magnetic field lines. The observed temperature variations imply that thermal conductivity is suppressed by a factor greater than 100 across the presumed direction of the magnetic field (as found in other clusters), and is also suppressed along the field lines by a factor of several. Two massive clumps in the periphery of A520, visible in the weak-lensing mass map and the X-ray image, have apparently been completely stripped of gas during the merger, but then re-accreted the surrounding high-entropy gas upon exit from the cluster. The mass clump that hosted the stripped cool core is also re-accreting hotter gas. An X-ray hydrostatic mass estimate for the clump that has the simplest geometry agrees with the lensing mass. Its current gas mass to total mass ratio is very low, 1.5 percent to 3 percent, which makes it a "dark subcluster." We also found a curious low X-ray brightness channel (likely a low-density sheet in projection) going across the cluster along the direction of an apparent secondary merger. The channel may be caused by plasma depletion in a region of an amplified magnetic field (with plasma Beta approximately equal to 10-20). The shock in A520 will be studied in a separate paper.

galaxies: clusters: individual (A520) – intergal↗
NASA NTRSDate not supplied

Guided Design of Alloys, Strengthened via Precipitation

Using theoretical and computational guidance, we are designing stronger middle and high-entropy alloys and superalloys for the airspace applications. We focus on improving mechanical properties of materials at cryogenic and elevated temperatures. Here we discuss basic science and fundamental theory that are being used for guided design of next-generation alloys. As examples, we consider the medium-entropy NiCoCr alloy and precipitated superalloys with a local phase transformation strengthening. This research is funded by NASA’s Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Alloys↗
NASA NTRSDate not supplied

GRX-810: NASA High Temperature Alloy Development for Additive Manufacturing

High-entropy alloys, and by extension, medium entropy alloys are an exciting new class of materials due to their impressive mechanical properties, especially at cryogenic and elevated temperatures. In this study, a novel oxide dispersion strengthened (ODS) NiCoCr-based alloy is presented which exhibits exceptional high temperature properties compared to conventional wrought superalloys. This new ODS alloy, GRX-810, leverages additive manufacturing to disperse nanoscale Y2O3 particles throughout the microstructure without the use of resource intensive processing steps, such as mechanical alloying. Microstructural and mechanical characterization confirms the successful incorporation and dispersion of nano-scale oxides throughout the build volume. As a result, this recently discovered processing route presents a new alloy design and production path that is synergistic between additive manufacturing and dispersion strengthening, possibly enabling a new generation of high-performance alloys.

Tim Smith↗
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↗
DOE OSTI2025

Development of Innovative Non-Concentrated Alloy (NCA) Fuel Cladding for Advanced Nuclear Reactors

As the nuclear energy sector advances toward next-generation reactors, the need for high-performance fuel cladding materials has become increasingly urgent. Traditional alloys like zirconium and stainless steel are reaching their performance limits under higher temperatures, more corrosive coolants, and extended irradiation. This report presents the development of a new class of fuel cladding materials based on Non-Concentrated Alloys (NCAs) ? multi-element systems designed to deliver enhanced mechanical strength, corrosion resistance, and radiation tolerance. Through a combination of computational modeling (Computer Coupling of Phase Diagrams and Thermochemistry: CALPHAD), simulation-guided alloy selection, and experimental fabrication via arc melting and spark plasma sintering (SPS), three strategic alloy design paths were explored: (1) FeCrAl-based NCAs, (2) refractory-lean neutron-efficient alloys, and (3) equimolar high-entropy compositions. Microstructural analysis confirmed the formation of stable body-centered cubic BCC_A2 phases, while mechanical testing demonstrated hardness values significantly exceeding those of conventional cladding materials. The results highlight the tunability of NCA systems and their potential for balancing strength and ductility ? a critical consideration for in-reactor performance. Looking forward, future work will focus on thermomechanical optimization, CALPHAD refinement, and benchmarking against industry standards to enable scalable deployment. This work not only advances the science of nuclear materials but also supports broader goals in nuclear safety, performance, and nuclear energy innovation.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Fast and bright scintillators for ultrafast materials dynamics using 4th generation synchrotron

We present recent advances in fast and bright scintillators for ultrafast X-ray phase contrast imaging of dynamic materials experiments at the upgraded Advanced Photon Source (APS-U), a fourth generation synchrotron. APS-U enables hard X-ray imaging at frame rates of at least 13 MHz (corresponding to 77 ns or shorter interframe intervals), creating a new need for scintillators with faster response and higher light output than lutetium yttrium oxyorthosilicate (LYSO). For indirect imaging and diffraction with ultrafast cameras, commercial lanthanum bromide (LaBr3) and cerium bromide (CeBr3) are promising candidates. These materials exhibit decay times approximately a factor of two shorter than LYSO (around 40 ns) and lutetium oxyorthosilicate (LSO), while maintaining comparable light yield per incident X-ray photon. However, their implementation at APS-U requires addressing several challenges, including material limitations due to hygroscopicity, efficient optical coupling to imaging systems, and high quantum efficiency for conversion of scintillation light, predominantly at wavelengths below 400 nm, into detectable electronic signals. We report results from material characterization, detector integration and packaging, and beamline experiments of materials with impact. In addition, emerging scintillator classes, including perovskites and high-entropy materials, are discussed as potential alternatives for next-generation ultrafast X-ray diagnostics.

Wang, Zhehui [Los Alamos] (ORCID:0000000178264063)↗
DOE OSTI2024

Design and Synthesis of PtPdNiCoMn High‐Entropy Alloy Electrocatalyst for Enhanced Alkaline Hydrogen Evolution Reaction: A Theoretically Supported Predictive Design Approach

Electrocatalytic hydrogen generation requires a multifunctional electrocatalyst with abundant active sites to drive multielectron transfer reactions. High entropy alloys (HEA) are five or more-elements with high configurational entropy are considered unique materials for next-generation electrocatalysts. Here, in this work, based on new screening guidelines for catalyst selections that combine density-functional theory calculated Gibbs formation-enthalpy with bond length and electronegativity variance, a novel HEA electrocatalyst consisting of five elements, namely, Pt, Pd, Ni, Co, and Mn has been designed. By simple room temperature electrodeposition, the designed catalyst is prepared and its hydrogen evolution reaction (HER) is explored and validated through experimental and theoretical approaches. The HEA demonstrated a superior HER activity with an overpotential of 22.6 mV at -10 mA cm -2 which outperforms Pt/C commercial catalyst. No evident degradation of the material is detected even after 100 hours of continuous operation under high current density. Moreover, the HEA has shown exceptional performance in harsh electrolyte conditions such as in simulated seawater and actual seawater. Remarkably, the density-functional theory calculated Gibbs formation-enthalpy is small (≈0 eV) compared to Pt/C placing the new HEA near the apex of Trasatti's model of Volcano plot, which is also suggestive of superior HER activity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Oxygen Effects and Selective Oxidation of Group IV Alloying Additions in Group V-Based Refractory Multi-principal Element Alloys

Refractory multi-principal element alloys (RMPEAs) hold significant potential for advancing ultra-high-temperature technologies due to their remarkable strength retention under these conditions. However, the beneficial effects of alloying on microstructural evolution and mechanical properties are often obscured by the presence of interstitial alloying elements. The intricate interactions between substitutional alloying elements of Groups IV, V, and VI and interstitial content, whether intentional or incidental, remain poorly understood. In this study, we investigate the impact of dissolved oxygen on the microstructural evolution and stability of RMPEAs primarily composed of Group V elements, Nb and V, along with Group IV elements Ti, Zr, and Hf. We show that the strong affinity of oxygen for Group IV elements Zr and Hf leads to the internal precipitation of oxides during heat treatment, which competes with the homogenization of the as-cast dendritic microstructure. Here, we demonstrate that careful control and design of oxygen content and Group IV alloying additions are essential to minimize micro-segregation and prevent the detrimental precipitation of internal oxides. To address these challenges, we propose employing non-equilibrium solidification calculations to predict and optimize as-cast solidification structures, thereby reducing the reliance on homogenization processes.

Alloy design↗
DOE OSTI2025

Bayesian optimization of entropy-stabilized metal fluoride conversion cathodes and their synthesis

Fluoride-based conversion cathodes are promising for next-generation Li ion batteries because of their high voltage and energy densities. High entropy earth abundant fluoride cathodes are attractive for sustainable battery because of the potentially higher cycling stability. While Ni and Co containing equimolar alloys stabilized by high entropy were considered previously, Ni and Co free non-equimolar metal alloy compositions might offer new opportunities to increase materials stability and average voltage. This opportunity was pursued using Bayesian optimization of average voltage for the computational prediction of (Fe x1 Cu x2 Zn x3 Mn x4 Mg x5 )F 2 cathode chemistries. Theoretical voltage, room temperature free energy, and electronic structure of potentially high voltage compositions were computed using density functional theory calculations. Here, the experimental realization of non-equimolar quinary Co and Ni free fluorides with stable rutile single phase and improved conversion reaction voltage by up to 28 % compared to the equimolar alloy demonstrated the power of Bayesian optimization methods for the computationally guided experimental synthesis of fluoride cathodes. Finally, non-equimolar cathode chemistries were found with cycling stability superior to known multi-element fluorides.

25 ENERGY STORAGE↗
DOE OSTI2025

Larger than uncorrelated vacancy diffusion contributions in chemically disordered crystalline materials

Arising from a variational approach to compute diffusion coefficients, we introduce “superkinetic kinosons”, which are contributions to the diffusion flux of mobile defects and atomic species by single jump mechanisms that can exceed their uncorrelated values. In vacancy-mediated diffusion in crystalline random and high entropy materials, these contributions primarily arise from intermittent jumps of slow moving atoms that remove the vacancy out of correlation traps and enable a quantification of such effects on the diffusion coefficients. They can be significant contributors to diffusion, even when faster moving atoms have infinite percolation networks. Furthermore, their existence and importance provide fundamental insights about underlying aspects of vacancy diffusion such as formation of localized correlation traps and deviation of vacancy diffusion from percolation behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗
DOE OSTI2025

Shear strength of a refractory high entropy alloy MoNbTaVW under high pressure

Radial X-ray diffraction (R-XRD) was performed in situ using a Panoramic Diamond Anvil Cell on the refractory high entropy alloy MoNbTaVW. The lattice parameters were determined through a Le Bail fit using a body centered cubic (BCC) lattice of symmetry $Im$$\overline{3}$$m$ (international space group number 229). Upper and lower bounds to the shear strength were determined up to 80 GPa nonhydrostatically using copper as a pressure standard. The equation of state was derived at the magic angle ψ = 54.7° and yielded a bulk modulus of K 0 = 220.8 ± 1.65 GPa. The experimental lattice parameters and bulk modulus match closely with corresponding density functional theory (DFT) calculations. The BCC phase remains stable up to the highest pressure of 80 GPa studied and is shown to be elastically anisotropic. The shear strength was found to saturate around 70 GPa with a value of τ = 1.75 GPa, and the shear moduli are presented in different limits of iso-strain and iso-stress.

36 MATERIALS SCIENCE↗