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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mechanical and Thermal Properties for Uranium and U–6Nb Alloy from First-Principles Theory

Elasticity, lattice dynamics, and thermal expansion for uranium and U–6Nb alloy (elastic moduli) are calculated from density functional theory that is extended to include orbital polarization (DFT+OP). Introducing 12.5 at.% of niobium, substitutionally, in uranium softens all the cii elastic moduli, resulting in a significantly softer shear modulus (G). Combined with a nearly invariant bulk modulus (B), the quotient B/G increases dramatically for U–6Nb, suggesting a more ductile material. Lattice dynamics from a harmonic model coupled with a DFT+OP electronic structure is applied for α uranium, and the obtained phonon density of states compares well with inelastic neutron-scattering measurements. The Debye temperature associated with the lattice dynamics falls within the range of experimentally observed Debye temperatures and it also validates our quasi-harmonic (QH) phonon model. The QH Debye–Grüneisen phonon method is combined with a DFT+OP electronic structure and used to explore the anisotropic thermal expansion in α uranium. The anomalous negative thermal expansion (contraction) of the b lattice parameter of the α-phase orthorhombic cell is relatively well reproduced from a free-energy model consisting of QH-phonon and DFT+OP electronic structure contributions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Defect control strategies for Al 1- x Gd x N alloys

Tetrahedrally bonded III-N and related alloys are useful for a wide range of applications from optoelectronics to dielectric electromechanics. Heterostructural AlN-based alloys offer unique properties for piezoelectrics, ferroelectrics, and other emerging applications. Atomic-scale point defects and impurities can strongly affect the functional properties of materials, and therefore, it is crucial to understand the nature of these defects and the mechanisms through which their concentrations may be controlled in AlN-based alloys. In this study, we employ density functional theory with alloy modeling and point defect calculations to investigate native point defects and unintentional impurities in Al 1-x Gd x N alloys. Among the native defects that introduce deep midgap states, nitrogen vacancies (V N ⁠) are predicted to be in the highest concentration, especially under N-poor growth conditions. We predict and experimentally demonstrate that V N formation can be suppressed in thin films through growth in N-rich environments. We also find that Al 1-x Gd x N alloys are prone to high levels of unintentional O incorporation, which indirectly leads to even higher concentrations of deep defects. Growth under N-rich/reducing conditions is predicted to minimize and partially alleviate the effects of O incorporation. The results of this study provide valuable insights into the defect behavior in wurtzite nitride-based alloys, which can guide their design and optimization for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theory-guided design of high-entropy alloys with enhanced strength-ductility synergy

Abstract Metallic alloys have played essential roles in human civilization due to their balanced strength and ductility. Metastable phases and twins have been introduced to overcome the strength-ductility tradeoff in face-centered cubic (FCC) high-entropy alloys (HEAs). However, there is still a lack of quantifiable mechanisms to predict good combinations of the two mechanical properties. Here we propose a possible mechanism based on the parameter κ, the ratio of short-ranged interactions between closed-pack planes. It promotes the formation of various nanoscale stacking sequences and enhances the work-hardening ability of the alloys. Guided by the theory, we successfully designed HEAs with enhanced strength and ductility compared with other extensively studied CoCrNi-based systems. Our results not only offer a physical picture of the strengthening effects but can also be used as a practical design principle to enhance the strength-ductility synergy in HEAs.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Evaluation of Primary Dendrite Arm Spacings from Aluminum-7wt% Silicon alloys Directionally Solidified aboard the International Space Station - Comparison with Theory

Aluminum – 7wt% silicon alloys were directionally solidified in the microgravity environment aboard the International Space Station as part of the “MIcrostructure Formation in CASTing of Technical Alloys under Diffusive and Magnetically Controlled Convective Conditions” (MICAST) European led program. Cross-sections of the sample during periods of steady-state growth were metallographically prepared from which the primary dendrite arm spacing (lambda 1) was measured. These spacings were found to be in reasonable agreement with the Hunt-Lu model which assumes a diffusion-controlled, convectionless, environment during controlled solidification. Deviation from the model was found and is attributed to gravity-independent thermocapillary convection where, over short distances, the liquid appears to have separated from the crucible wall.

Angart, Samuel↗
DOE OSTI2021

A percolation theory for designing corrosion-resistant alloys

Iron-chromium and nickel-chromium binary alloys containing sufficient quantities of chromium serve as the prototypical corrosion-resistant metals owing to the presence of a nanometre-thick protective passive oxide film. Should this film be compromised by a scratch or abrasive wear, it reforms with little accompanying metal dissolution, a key criterion for good passive behaviour. This is a principal reason that stainless steels and other chromium-containing alloys are used in critical applications ranging from biomedical implants to nuclear reactor components. Unravelling the compositional dependence of this electrochemical behaviour is a long-standing unanswered question in corrosion science. Herein, we develop a percolation theory of alloy passivation based on two-dimensional to three-dimensional crossover effects that accounts for selective dissolution and the quantity of metal dissolved during the initial stage of passive film formation. We validate this theory both experimentally and by kinetic Monte Carlo simulation. Our results reveal a path forward for the design of corrosion-resistant metallic alloys.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Constitutive relationships for anisotropic high-temperature alloys

A constitutive theory is presented for representing the anisotropic viscoplastic behavior of high temperature alloys that posses directional properties resulting from controlled grain growth or solidification. The theory is an extension of a viscoplastic model that was applied in structural analyses involving isotropic metals. Anisotropy is introduced through the definition of a vector field that identifies a preferential (solidification) direction at each material point. Following the development of a full multiaxial theory, application is made to homogeneously stressed elements in pure shear and to a uniaxially stressed rectangular block in plane stress with the stress direction oriented at an arbitrary angle with the material direction. It is shown that an additional material parameter introduced to characterize the degree of anisotropy can be determined on the basis of simple creep tests.

Robinson, D. N.↗
NASA NTRS1983

Constitutive relationships for anisotropic high-temperature alloys

A constitutive theory is presented for representing the anisotropic viscoplastic behavior of high-temperature alloys that possess directional properties resulting from controlled grain growth or solidification. The theory is an extension of a viscoplastic model that has been applied in structural analyses involving isotropic metals. Anisotropy is introduced through the definition of a vector field that identifies a preferential (solidification) direction at each material point. Following the development of a full multiaxial theory, application is made to homogeneously stressed elements in pure shear and to a uniaxially stressed rectangular block in plane stress with the stress direction oriented at an arbitrary angle with the material direction. It is shown that an additional material parameter introduced to characterize the degree of anisotropy can be determined on the basis of simple creep tests.

Robinson, D. N.↗
DOE OSTI2022

Modeling antiphase boundary energies of Ni 3 Al-based alloys using automated density functional theory and machine learning

Antiphase boundaries (APBs) are planar defects that play a critical role in strengthening Ni-based superalloys, and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design. Here, we report a computational workflow to enable the development of sufficient data to train machine-learning (ML) models to automate the study of the effect of composition on the (111) APB energy in Ni 3 Al-based alloys. We employ ML to leverage this wealth of data and identify several physical properties that are used to build predictive models for the APB energy that achieve a cross-validation error of 0.033 J m –2 . We demonstrate the transferability of these models by predicting APB energies in commercial superalloys. Moreover, our use of physically motivated features such as the ordering energy and stoichiometry-based features opens the way to using existing materials properties databases to guide superalloy design strategies to maximize the APB energy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Directing Energy Transfer in Halide Perovskite–Chromophore Hybrid Assemblies

Directing the flow of energy and the nature of the excited states that are produced in nanocrystal–chromophore hybrid assemblies is crucial for realizing their photocatalytic and optoelectronic applications. Using a combination of steady-state and time-resolved absorption and photoluminescence (PL) experiments, we have probed the excited-state interactions in the CsPbBr 3 –Rhodamine B (RhB) hybrid assembly. PL studies reveal quenching of the CsPbBr 3 emission with a concomitant enhancement of the fluorescence of RhB, indicating a singlet-energy-transfer mechanism. Transient absorption spectroscopy shows that this energy transfer occurs on the ~200 ps time scale. To understand whether the energy transfer occurs through a Förster or Dexter mechanism, we leveraged facile halide-exchange reactions to tune the optical properties of the donor CsPbBr 3 by alloying with chloride. This allowed us to tune the spectral overlap between the donor CsPb(Br 1–x Cl x ) 3 emission and acceptor RhB absorption. For CsPbBr 3 -RhB, the rate constant for energy transfer (k ET ) agrees well with Förster theory, whereas alloying with chloride to produce chloride-rich CsPb(Br 1–x Cl x ) 3 favors a Dexter mechanism. These results highlight the importance of optimizing both the donor and acceptor properties to design light-harvesting assemblies that employ energy transfer. Furthermore, the ease of tuning optical properties through halide exchange of the nanocrystal donor provides a unique platform for studying and tailoring excited-state interactions in perovskite–chromophore assemblies.

14 SOLAR ENERGY↗
DOE OSTI2021

Simultaneous Decomposition and Dewetting of Nanoscale Alloys: A Comparison of Experiment and Theory

In this work, we consider the coupled process of phase separation and dewetting of metal alloys of nanoscale thickness deposited on solid substrates. The experiments involve applying nanosecond laser pulses that melt the Ag40Ni60 alloy films in two setups: either on thin supporting membranes or on bulk substrates. These two setups allow for extracting both temporal and spatial scales on which the considered processes occur. The theoretical model involves a longwave version of the Cahn–Hilliard formulation used to describe spinodal decomposition, coupled with an asymptotically consistent longwave-based description of dewetting that occurs due to destabilizing interactions between the alloy and the substrate, modeled using the disjoining pressure approach. Careful modeling, combined with linear stability analysis and fully nonlinear simulations, leads to results consistent with the experiments. In particular, we find that the two instability mechanisms occur concurrently, with the phase separation occurring faster and on shorter temporal scales. The modeling results show a strong influence of the temperature dependence of relevant material properties, implying that such a dependence is crucial for the understanding of the experimental findings. The agreement between theory and experiment suggests the utility of the proposed theoretical approach in helping to develop further experiments directed toward formation of metallic alloy nanoparticles of desired properties.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Phase diagrams and microscopic structures of (Hg,Cd)Te, (Hg,Zn)Te, and (Cd,Zn)Te alloys

A cluster theory based on the quasi-chemical approximation has been applied to study the local correlation bond-length distribution, and phase diagrams of the II-VI pseudobinary alloys Hg(1 - x)Cd(x)Te, Hg(1 - x)Zn(x)Te, and Cd(1 - x)Zn(x)Te. The cluster energy is calculated by letting it relax in some effective alloy medium and then considering the contributions from the strain and chemical energies. Two different models are presented to simulate the alloy medium. While both models show that all three alloys have nearly random distributions, the signs of the local correlation prove to be sensitive to the alloy medium chosen for the energy calculation. Good agreement is found between experiment and the bond lengths and phase diagrams in both models.

Patrick, R. S.↗
DOE OSTI2025

Bayesian prior construction for uncertainty quantification in first-principles statistical mechanics

First-principles statistical mechanics enables the prediction of thermodynamic and kinetic properties of materials, but is computationally expensive. Many approaches require surrogate models to calculate energies within Monte Carlo or molecular dynamics simulations. Inexpensive surrogates such as cluster expansions enable otherwise intractable calculations by interpolating data from higher accuracy methods, such as Density Functional Theory (DFT). Surrogate models introduce uncertainty into downstream calculations, in addition to any uncertainty inherent to DFT calculations. Bayesian frameworks address this by quantifying uncertainty and incorporating expert knowledge through priors. However, constructing effective priors remains challenging. This work introduces and describes practical strategies for building Bayesian cluster expansions, focusing on basis truncation, hyperparameter selection, and ground state replication. We analyze multiple basis truncation schemes, compare cross-validation to the evidence-approximation for hyperparameter optimization, and provide methods to find and enforce ground-state-preserving models through priors. Additionally, we compare the uncertainties between different approximations to DFT (LDA, PBE, SCAN) against the uncertainty introduced with the use of cluster expansion surrogate models. These approaches are demonstrated on the BCC Li x Mg 1-x and Li x Al 1-x alloys, which are both of interest for solid-state Li batteries. Our results provide guidelines for constructing and utilizing Bayesian cluster expansions, thereby improving the transparency of materials modeling. Furthermore, the approaches and insights developed in this work can be transferred to a wide range of cluster expansion surrogate models, including the atomic cluster expansion and related machine-learned interatomic potential architectures.

Alloy theory↗
DOE OSTI2024

Ubiquitous short-range order in multi-principal element alloys

Recent research in multi-principal element alloys (MPEAs) has increasingly focused on the role of short-range order (SRO) on material performance. However, the mechanisms of SRO formation and its precise control remain elusive, limiting the progress of SRO engineering. Here, leveraging advanced additive manufacturing techniques that produce samples with a wide range of cooling rates (up to 10 7 K s –1 ) and an enhanced semi-quantitative electron microscopy method, we characterize SRO in three CoCrNi-based face-centered-cubic (FCC) MPEAs. Surprisingly, irrespective of the processing and thermal treatment history, all samples exhibit similar levels of SRO. Atomistic simulations reveal that during solidification, prevalent local chemical order arises in the liquid-solid interface (solidification front) even under the extreme cooling rate of 10 11 K s –1 . This phenomenon stems from the swift atomic diffusion in the supercooled liquid, which matches or even surpasses the rate of solidification. Therefore, SRO is an inherent characteristic of most FCC MPEAs, insensitive to variations in cooling rates and even annealing treatments typically available in experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning predictions of irradiation embrittlement in reactor pressure vessel steels

Abstract Irradiation increases the yield stress and embrittles light water reactor (LWR) pressure vessel steels. In this study, we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening extrapolated to low flux, high fluence, extended life conditions. The machine learning training data included the Irradiation Variable for lower flux irradiations up to an intermediate fluence, plus the Belgian Reactor 2 and Advanced Test Reactor 1 for very high flux irradiations, up to very high fluence. Notably, the machine learning model predictions for the high fluence, intermediate flux Advanced Test Reactor 2 irradiations are superior to extrapolations of existing hardening models. The successful extrapolations showed that machine learning models are capable of capturing key intermediate flux effects at high fluence. Similar approaches, applied to expanded databases, could be used to predict hardening in LWRs under life-extension conditions.

36 MATERIALS SCIENCE↗