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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Review of the Serrated-Flow Phenomenon and Its Role in the Deformation Behavior of High-Entropy Alloys

High-entropy alloys (HEAs) are a novel class of alloys that have many desirable properties. The serrated flow that occurs in high-entropy alloys during mechanical deformation is an important phenomenon since it can lead to significant changes in the microstructure of the alloy. In this article, we review the recent findings on the serration behavior in a variety of high-entropy alloys. Relationships among the serrated flow behavior, composition, microstructure, and testing condition are explored. Importantly, the mechanical-testing type (compression/tension), testing temperature, applied strain rate, and serration type for certain high-entropy alloys are summarized. The literature reveals that the serrated flow can be affected by experimental conditions such as the strain rate and test temperature. Furthermore, this type of phenomenon has been successfully modeled and analyzed, using several different types of analytical methods, including the mean-field theory formalism and the complexity-analysis technique. Importantly, the results of the analyses show that the serrated flow in HEAs consists of complex dynamical behavior. It is anticipated that this review will provide some useful and clarifying information regarding the serrated-flow mechanisms in this material system. Finally, suggestions for future research directions in this field are proposed, such as the effects of irradiation, additives (such as C and Al), the presence of nanoparticles, and twinning on the serrated flow behavior in HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Complementing Nanoscale Galvanic Exchange with Redox Manipulation toward Architectural Control of Multimetallic Hollow Nanostructures

Galvanic exchange occurring within the confinement by nanoparticulate templates provides a unique pathway to controllably transform solid metallic nanoparticles into architecturally more sophisticated multimetallic hollow nanostructures under facile reaction conditions. As such, in this Minireview, we elaborately discuss how the nanoparticle-templated galvanic exchange can be deliberately coupled with redox manipulation to synthesize a large library of complex multimetallic hollow nanostructures exhibiting precisely tailored architectures and compositions, with a particular emphasis on important mechanistic insights concerning the dynamic interplay among multiple structure-remodeling processes that synergistically dictate the versatile nanoparticle transforming behaviors during kinetically and regioselectively modulated galvanic exchange reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermal properties of BaCu 2 SnQ 4 (Q = S, Se) quaternary chalcogenides

Quaternary chalcogenides form in different structure types and compositions and are of scientific interest, while their diversity of physical properties exemplifies why they continue to be investigated for potential technological applications. Here, we investigate the thermal properties of BaCu 2 SnQ 4 with trigonal (Q = S) and orthorhombic (Q = Se) crystal structures. BaCu 2 SnS 2 Se 2 was also synthesized and characterized in order to investigate the effect of alloying on the thermal properties of these quaternary chalcogenides. The low thermal conductivity these materials possess originates from complex phonon spectra and local dynamics of distorted CuQ 4 tetrahedra. Our results and analyses are presented in light of the ongoing fundamental interest in these materials as well as their continued interest for energy-related and opto-electronic applications.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Method and apparatus for hydrogen production from water

A method, apparatuses and chemical compositions are provided for producing high purity hydrogen from water. Metals or alloys capable of reacting with water and producing hydrogen in aqueous solutions at ambient conditions are reacted with one or more inorganic hydrides capable of releasing hydrogen in aqueous solutions at ambient conditions, one or more transition metal compounds are used to catalyze the reaction and, optionally, one or more alkali metal-based compounds. The metal or alloy is preferably aluminum. The inorganic hydride is from a family of complex inorganic hydrides; most preferably, NaBH.sub.4. The transition metal catalyst is from the groups VIII and IB; preferably, Cu and Fe. The alkali metal-based compounds are preferably NaOH, KOH, and the like. Hydrogen generated has a purity of at least 99.99 vol. % (dry basis), and is used without further purification in all types of fuel cells, including the polymer electrolyte membrane (PEM) fuel cell.

Muradov, Nazim Z.↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗
NASA NTRS2001

Formation of Y(x)Nd(1-x) Ba2Cu3O(7-delta) (0 = or < x < or = 0.7) Superconductors from an Undercooled Melt Via Aero-Acoustic Levitation

Melt processing of RE123 superconductors has gained importance in recent years. While the first high temperature superconductors (HTSCs) were made using traditional ceramic press and sinter technology, recent fabrication efforts have employed alternate processing techniques including laser ablation and ion beam assisted deposition for thin film fabrication of tapes and wires and melt growth for bulk materials. To optimize these techniques and identify other potential processing strategies, phase relation studies on HTSCs have been conducted on a wide variety of superconducting compounds using numerous processing strategies. This data has enhanced the understanding of these complex systems and allowed more accurate modeling of phase interactions. All of this research has proved useful in identifying processing capabilities for HTSCs but has failed to achieve a breakthrough for wide spread application of these materials. This study examines the role of full to partial substitution of Nd in the Y123 structure under rapid solidification conditions. Aero-acoustic levitation (AAL) was used to levitate and undercool RE123 in pure oxygen binary alloys with RE = Nd an Y along a range of compositions corresponding to Y(x)Nd(1-x) Ba2Cu3O(7-delta) (0 = or < x < or = 0.7) which were melted by a CO2 laser. Higher Y content spheres could not be melted in the AAL and were excluded from this report. Solidification structures were examined using scanning electron microscopy, electron dispersive spectroscopy, and powder x-ray diffraction to characterize microstructures and identify phases.

Gustafson, D. E.↗
DOE OSTI2023

High-Temperature Corrosion of Chromia-Forming Ni-Based Alloys in CO 2 Containing Impurities

Future technologies require structural materials resistant to environmental degradation in high-temperature CO 2 -rich environments. In this work, we exposed several commercially available Ni-based alloys (230, 263, 282, 617, 625, and 740H) to atmospheric pressure gases intended to simulate the compositions expected in future direct-fired supercritical CO 2 power cycles. The alloys were exposed to 95% CO 2 + 4% H 2 O + 1% O 2 and the same gas containing 0.1% SO 2 at temperatures of 600, 650, 700, 750, and 800 °C for 2500 h. With minor exceptions, chromia scales formed on all alloys at all temperatures in the SO 2 -free gas, yielding parabolic growth rates that followed an Arrhenius temperature dependence. Behavior in the SO 2 -containing gas was more complex. Generally, the alloys performed well at temperatures of 650, 750, and 800 °C. While some alloys further performed relatively well across the whole temperature range, several of the alloys experienced chromia failure resulting in non-protective duplex oxide scales and high oxidation rates, at temperatures of 600 and 700 °C. Deviation from protective behavior was associated with internal sulfide formation and, additionally for the case of 600 °C, external sulfate formation. Extensive carburization accompanied growth of the non-protective duplex oxide scales, which made it more difficult for the alloy to recover after initiation of the sulfur-induced accelerated corrosion process. The thermodynamic and kinetic factors influencing the accelerated corrosion in the presence of sulfur are discussed. The results suggest that caution is required when assessing compatibility of Ni-based alloys for CO 2 -based systems when sulfur-based impurities are expected.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Damage Tolerance Assessment of Friction Pull Plug Welds

Friction stir welding is a solid state welding process developed and patented by The Welding Institute in Cambridge, England. Friction stir welding has been implemented in the aerospace industry in the fabrication of longitudinal welds in pressurized cryogenic propellant tanks. As the industry looks to implement friction stir welding in circumferential welds in pressurized cryogenic propellant tanks, techniques to close out the termination hole associated with retracting the pin tool are being evaluated. Friction pull plug welding is under development as a one means of closing out the termination hole. A friction pull plug weld placed in a friction stir weld results in a non-homogenous weld joint where the initial weld, plug weld, their respective heat affected zones and the base metal all interact. The welded joint is a composite, plastically deformed material system with a complex residual stress field. In order to address damage tolerance concerns associated with friction plug welds in safety critical structures, such as propellant tanks, nondestructive inspection and proof testing may be required to screen hardware for mission critical defects. The efficacy of the nondestructive evaluation or the proof test is based on an assessment of the critical flaw size in the test or service environments. Test data relating residual strength capability to flaw size in two aluminum alloy friction plug weld configurations is presented.

McGill, Preston↗
DOE OSTI2026

Beyond the eutectic paradigm: nanolamellar patterns in a rapidly solidified peritectic alloy

Peritectic transformations are central to many structural alloys, yet pattern formation remains poorly understood due to complex growth dynamics and limited three-dimensional data. Here, we report an unusual two-phase microstructure in a Zn–Ag peritectic alloy subjected to rapid solidification by laser surface remelting. Synchrotron X-ray nanotomography reveals a lamellar structure of primary 𝜀-AgZn 3 and peritectic Zn with ∼700 nm spacing. Although resembling a eutectic morphology, this pattern forms without a eutectic reaction through non-steady coupled growth from the liquid. SEM and TEM-EDS confirm interface shapes and phase compositions. These findings expand the design space of peritectics for refined microstructural control.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A machine learning aided interpretable model for rupture strength prediction in Fe-based martensitic and austenitic alloys

Abstract The class of 9–12% Cr ferritic-martensitic alloys (FMA) and austenitic stainless steels have received considerable attention due to their numerous applications in high temperature power generation industries. To design high strength steels with prolonged service life requires a thorough understanding of the long-term properties, e.g., creep rupture strength, rupture life, etc., as a function of the chemical composition and processing parameters that govern the microstructural characteristics. In this article, the creep rupture strength of both 9–12% Cr FMA and austenitic stainless steel has been parameterized using curated experimental datasets with a gradient boosting machine. The trained model has been cross validated against unseen test data and achieved high predictive performance in terms of correlation coefficient ( $$R^{2} > 0.98 $$ R 2 > 0.98 for 9–12% Cr FMA and $$R^{2} > 0.95 $$ R 2 > 0.95 for austenitic stainless steel) thus bypassing the need for additional comprehensive tensile test campaigns or physical theoretical calculations. Furthermore, the feature importance has been computed using the Shapley value analysis to understand the complex interplay of different features.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Microstructural Evaluations of Baseline HSR/EPM Disk Alloys

Six alloys representing two classes of powder metallurgy nickel-based superalloys were examined by transmission electron microscopy (TEM) and phase extraction. Alloys KM4, CH98, IN-100 and 456 are based on a Ni-18Co-12Cr composition while alloys Rene' 88 DT and SR 3 have lower Al and Co and higher Cr contents. The lambda size distributions were determined from quantitative image analysis of the TEM images. The volume fraction of lambda and carbides and the composition of the phases were determined by a combination of phase extraction and TEM. The results showed many similarities in lambda size distributions, grain boundary serrations, and grain boundary carbide frequencies between alloys KM4, CH98, 456, Rene' 88 DT and SR 3 when heat treated to give an approximate grain size of ASTM 6. The density of grain boundary carbides in KM4 was shown to substantially increase as the grain size increased. IN-100 and 456 subjected to a serration cooling heat treatment had much more complex lambda size distributions with very large intergranular and intragranular secondary lambda as well as finer than average cooling and aging lambda. The grain boundary carbides in IN-100 were similar to the other alloys, but 456 given the serration cooling heat treatment had a more variable density of grain boundary carbides. Examination of the phases extracted from the matrix showed that there were significant differences in the phase chemistries and elemental partitioning ratios between the various alloys.

Gabb, Timothy P.↗
DOE OSTI2023

Dislocation Patterning in Deforming Crystals: Theory, Computational Predictions and Validation (Final Technical Report)

This project was awarded for an initial period of three years, followed by a no-cost extension for one year and a funded one-year renewal. During the first four years, the project focused on investigating the role of dislocation reactions and dislocation correlation in dislocation patterning in FCC metals. During the fifth year, the scope of research was expanded to investigate the effects of composition inhomogeneity on the mesoscale plastic response of Body-Centered Cubic (BCC) alloys. In addition to its impact on metal hardening during deformation, dislocation patterning provides the microstructure information required to understand phenomena like fracture and recrystallization in metals. The Continuum Dislocation Dynamics (CDD) framework was the methodology used during the first four years, followed by the use of Discrete Dislocation Dynamics (DDD) during the fifth year. CDD is a density-based formalism of dislocation dynamics in which the plastic deformation of crystals is predicted together with the mesoscale dislocation patterns by tracking the space-time evolution of dislocations as driven by the applied stress, short-range and long-range interactions of dislocations, and cross slip. CDD is a crystal mechanics approach in which the plastic constitutive part is replaced with the equations of dislocation dynamics, which is driven by the internal stress via a mobility laws, while the evolution of the density gives the eigenstrain required to update the internal stress itself. The governing equations are thus those of crystal mechanics cast as an eigenstrain problem and those of dislocation transport and reactions. Our investigations during the first four years were driven by the hypothesis that that dislocation patterning is triggered by spatiotemporal dislocation density and internal stress fluctuations, and that such fluctuations influence the collective dislocation dynamic through their effects on the short-range reaction rates and the collective dislocation mobility. This hypothesis was tested by modeling the influence of the dislocation reactions and dislocation correlations on collective dislocation dynamics. The main research components during the first four years were: 1) Reformulation of the CDD framework to integrate the dislocation correlations and dislocation reactions. 2) Simulation of the dislocation correlations and quantifying their contribution to the long-range stress of complex dislocation systems. 3) Computational implementation of the updated CDD model for FCC single crystals and development of an efficient CDD code. 4) Investigation of dislocation patterning in FCC crystals based on the updated CDD model. Some key findings from these investigations were: 1) The patterning of dislocations is initiated by cross slip and internal stress fluctuations, and the refinement of the pattern results from junction formation. 2) Patterning is more prominent under high stress. 3) The correlation stress was found to be a significant part of the mean field stress in continuum representations of dislocation dynamics. During the last year of the project, we have established a method for performing dislocation dynamics in inhomogeneous alloys and demonstrated the impact of composition inhomogeneity on the characteristics of initial yielding and dislocation character in BCC alloys. We also tested this method using an irradiated ferritic alloy in which the composition and dislocation loops effects are both present. In doing so, we have considered two aspects of the role of inhomogeneity, the creation of internal coherency stress due to the dependence of the lattice parameter on the local composition, and the dependence of the dislocation mobility on the local composition. These two aspects resulted in an unexpected behavior of the dislocation system, and, in turn, the yielding behavior of BCC alloys. Key findings include: 1) The composition inhomogeneity in BCC alloys alters the well-known role of screw dislocations by forcing a level of waviness on the average dislocation character, thus destroying the screw character dominance in the yielding observed in pure or homogeneous BCC metals. 2) In the case of irradiated alloys, while composition inhomogeneity by itself and dislocation loops by themselves result in some hardening, the superposition of the two mechanisms does not result in the sum of the two contributions via any known rule. The latter result contradicts the classical works related hardening via multiple mechanisms, which state that various hardening mechanisms can be added linearly or using some Pythagorean additive rule. We were able to rationalize this unexpected result by a closer loop at the origin of the hardening mechanisms themselves, which both involved long-range elastic interactions with dislocations. We reached the conclusion that the hardening resulting from the total stress associated with these two mechanisms (current work) differs from the sum of the effects of the individual stress fields (classical literature). We have also found a major flaw in the classical theory of spinodal hardening. The latter theory never considered the impact of composition undulation on the solute hardening. We have built a new general theory accounting for the effect of solute friction together with the composition undulations on the dislocation configuration at Critical Resolved Shear Stress (CRSS), which is yielding a new definition of the spinodal hardening and new different results. This work is the first to recognize the lack of the role of solute in spinodal hardening theory of alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning bridges local static structure with multiple properties in metallic glasses

A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Additive Manufacture of Multi-Functional, Large-Scale Components

The poster summarizes the main results for a LDRD focused on developing a arc-based additive manufacturing (AM) system capable of fabricating large components with a composition gradient otherwise known as functionally graded materials (FGMs). FGMs are capable of addressing local extreme conditions in an optimal and cost-effective manner. The AM system (referred to as multi-Wire Arc Additive Manufacturing or m-WAAM) consisted of modifying a standard automated gas tungsten arc welding system to deliver multiple welding wires to the weld pool at controlled rates to deposit desired alloy compositions at critical locations. Numerous shapes and composition gradients were fabricated with the system and the effect of various deposition parameters on the nature of the composition profile were evaluated. Additionally, heat treatment of the FGM was performed to develop graded microstructures which should enhance dynamic impact performance of inexpensive steels. The project highlights the potential of m-WAAM to efficiently fabricate FGMs. However, this project only explored the science behind the technique and additional development work will be required to develop a fully-functional system that can build more complex components.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Vacancy diffusion barrier spectrum and diffusion correlation in multicomponent alloys

Vacancy diffusion serves a crucial role in many important kinetic behaviors and properties of multicomponent alloys. Essential questions, however, persist regarding how chemical complexity affects diffusion and what unique characteristics, if any, set these alloys apart from traditional metals. Using neural network kinetics model, we study vacancy diffusion in NbMoTa alloy across a broad temperature range (2600 to 800 K). Unlike pure metals, the two key diffusion parameters—diffusion correlation factor f and activation energy ΔG m —are not constant in alloys, but instead substantially decrease with decreasing temperature. This temperature dependence arises from a reduced number of active vacancy jump pathways at lower temperatures, leading to more correlated diffusion. Upon examining vacancy diffusion throughout the entire compositional space of the Nb-Mo-Ta system, we discover that the slowest vacancy diffusion surprisingly occurs in the non-equimolar region, rather than the equimolar concentration where the configurational entropy is highest. The diffusion barrier spectrum, characterizing the diffusion energy landscape, is an intrinsic material characteristic, which controls both f and ΔG m and, thereby, the diffusivity. Lastly, we find that the vacancy diffusion rate drops noticeably in the presence of local chemical order in the NbMoTa system, particularly for MoTa alloys with long-range B2 order.

Defects↗
DOE OSTI2023

Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential

Interatomic potential development using machine learning (ML) approaches has attracted a lot of attention in recent years because these potentials can effectively describe the structural and dynamical properties of complex materials at the atomistic level. Here, in this work, we present the development of a neural network (NN) deep ML interatomic potential for Fe-Si alloys, and we demonstrate the effectiveness of the NN-ML potential in predicting the structures and energies of liquid and crystalline phases of Fe-Si alloys in comparison with the results from ab initio molecular dynamics simulations or experimental data. The developed NN-ML potential is also used to perform molecular dynamics simulations to study the structures of Fe-Si alloys with various compositions under rapid solidification conditions. The short-ranged orders in the rapidly solidified Fe-Si alloys are also analyzed by a cluster alignment method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Combinatorial investigation of structural and optical properties of cation-disordered ZnGeN 2

Cation-disordered ZnGeN 2 shows promise for application as a blue-green emitter in light-emitting devices, but more foundational work is necessary to understand structure–property relationships. In this work, we present a combinatorial exploration of the experimental phase space of wurtzite (cation-disordered) ZnGeN 2 using high-throughput co-sputtering. Structure, morphology and optical properties are explored as a function of cation composition and synthesis temperature. ZnGeN 2 is found to crystallize in the wurtzite structure ranging from Zn-rich to Ge-rich compositions. X-ray diffraction refinements reveal a continuous shift in cell volume with off-stoichiometry, indicating alloy-like structural behavior. Furthermore, the optical absorption of all films examined is lower in energy than the value predicted for cation-ordered ZnGeN 2 , suggesting that cation disorder is decreasing the bandgap. Additionally, the absorption threshold shifts continuously to higher energy for Ge-rich samples, consistent with bandgap shifts due to alloy-like structural behavior. Defect formation energy diagrams are calculated to help guide understanding of off-stoichiometry from a defect complex perspective. This work paves the way toward use of ZnGeN 2 as a bandgap-tunable optoelectronic semiconductor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗