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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of coherent-precipitate-hardened high-entropy alloys with hierarchical NiAl/Ni 2 TiAl precipitates in CrMnFeCoNiAl x Ti y alloys

Coherent precipitates hardening is currently emerging strengthening mechanism of the various high entropy alloys (HEAs). Recently, CrMnFeCoNiAl x HEAs have been studied to show a phase transition from face-centered-cubic (FCC) to body-centered-cubic (BCC) and formation of coherent precipitates (B2-NiAl) within the BCC matrix. The coherent precipitates in the CrMnFeCoNiAl x alloys could contribute to increase the strength but lead to considerable reduction of the ductility. The present work systematically investigated a series of CrMnFeCoNiAl 0.5 Ti x alloys to further improve the strength and plasticity, as compared to the previously reported CrMnFeCoNiAl x HEAs. As a result, an increase of Ti addition leads to the phase transition from FCC to BCC and formation of lamellar structure and hierarchical precipitates reinforced by B2-NiAl and L2 1 -Ni 2 TiAl phases. Excellent mechanical properties were achieved from CrMnFeCoNiAl 0.5 Ti 0.1 and CrMnFeCoNiAl 0.5 Ti 0.2 alloys. Herein, the mechanical properties of the CrMnFeCoNiAl 0.5 Ti x alloys were discussed via theoretical strengthening mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic properties of FeCrMnNi, a high entropy alloy

The goal of this paper was to assess the dynamic properties of a new class of materials, High entropy alloys (HEAs). Specifically, gas gun experiments coupled with recovery were performed on a specific HEA, FeCrMnNi, to measure its equation of state (EOS) and its spall strength, which is a measure of the stress required to nucleate voids under shock loading conditions. While there has been a plethora of work performed to assess the mechanical properties of these HEAs under uniaxial stress conditions as a function of strain rate, investigation of its properties in dynamic extremes remains rare. The current work fills this gap in knowledge for this novel class of materials. Our results show that the measured EOS for this material at one velocity was in reasonable agreement with an estimated Hugoniot. Furthermore, while the spall strength for this material was found to be ~1.9 GPa, with some variation based on sample location, the main failure mode was brittle. This brittle failure leading to formation of cracks in the material is different than the ductile failure observed in pure iron and its alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Yield strength prediction of high-entropy alloys using machine learning

Yield strength at high temperature is an important parameter in the design and application of high entropy alloys (HEAs). However, the experimental measurement of yield strength at high temperature is quite costly, complicated, and time-consuming. Therefore, it is essential to identify and apply a robust method for the accurate prediction of yield strength at high temperature from the available experimental and simulation data. In this study, for the first time, a machine learning (ML) method based on the regression technique of random forest (RF) regressor is used to predict the yield strength of HEAs at the desired temperature. Further, the yield strengths of MoNbTaTiW and HfMoNbTaTiZr at 800 °C and 1200 °C, are predicted using the RF regressor model. We find that the results are consistent with the experimental reports, showing that the RF regressor model predicts the yield strength of HEAs at the desired temperatures with high accuracy.

36 MATERIALS SCIENCE↗
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↗
DOE OSTI2025

Surface Nanostructure Control and Thermodynamic Stability Analysis of Femtosecond Laser-Ablated CuCoMn 1.75 NiFe 0.25 Nanoparticles

Surface nanostructure control is the key to functionalizing nanomaterials. This paper presents a characterization with thermodynamic stability analysis of CuCoMn 1.75 NiFe 0.25 high-entropy alloy (HEA) nanoparticles synthesized by femtosecond laser ablation in ethanol and liquid nitrogen (LN2). Using multimodal electron microscopy and spectroscopy, we examine phase, particle size, defect structure, chemical distribution, and surface composition and relate them to HEA stability. Elemental distributions are uniform in both media, but LN2 produces smaller particles with a narrower size distribution and mainly single- or few-domain interiors, whereas ethanol yields larger particles built from 2–4 nm crystallites with domain aggregation. Edge defects appear in both but energy-dispersive X-ray spectroscopy (EDS) is broadly uniform with local fluctuations in ethanol. X-ray photoelectron spectroscopy (XPS), supported by an attenuation model, indicates an ∼1 nm oxide overlayer that suppresses Mn 2p intensity; correcting for it returns Mn toward the bulk value. UV–NIR and photoluminescent spectra independently support a thin oxide shell. Composition-based thermodynamic descriptors place LN2 closer to bulk mixing parameters, while ethanol raises ΔH_mix and lowers Ω. Cooling simulations are consistent (LN2 ∼ 0.1 μs quench, ethanol ∼1 μs). In conclusion, these results connect solvent-controlled kinetics and thermodynamics to crystalline state and surface chemistry, informing surface control of HEA nanoparticles.

Femtosecond Laser Ablation↗
DOE OSTI2021

Revealing High-Temperature Reduction Dynamics of High-Entropy Alloy Nanoparticles via In Situ Transmission Electron Microscopy

Understanding the behavior of high-entropy alloy (HEA) materials under hydrogen (H 2 ) environment is of utmost importance for their promising applications in structural materials, catalysis, and energy-related reactions. Herein, the reduction behavior of oxidized FeCoNiCuPt HEA nanoparticles (NPs) in atmospheric pressure H-2 environment was investigated by in situ gas-cell transmission electron microscopy (TEM). The reduction reaction front was maintained at the external surface of the oxide. During reduction, the oxide layer expanded and transformed into porous structures where oxidized Cu was fully reduced to Cu NPs while Fe, Co, and Ni remained in the oxidized form. In situ chemical analysis showed that the expansion of the oxide layer resulted from the outward diffusion flux of all transition metals (Fe, Co, Ni, Cu). Revealing the H-2 reduction behavior of HEA NPs facilitates the development of advanced multicomponent alloys for applications targeting H 2 formation and storage, catalytic hydrogenation, and corrosion removal.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
DOE OSTI2021

Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature, T break , introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay below T break . We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Emergence of local scaling relations in adsorption energies on high-entropy alloys

Alloying has been proposed to circumvent scaling relations between the adsorption energies thus allowing for the complete optimization of multistep reactions. Herein the fidelity of scaling rules on high-entropy alloy (HEA) surfaces is assessed focusing on hydrogen-containing molecules, *AH x for A = C and N (x = 0, 1, 2, 3), A = S (x = 0, 1, 2) and A = O (x = 0, 1). Using an adsorbate- and site-specific deep learning model to rapidly compute the adsorption energies on CoMoFeNiCu HEA surfaces, the energies of *AH x and *A are shown to be linearly correlated if *A and *AH x have identical adsorption site symmetry. However, a local linear dependence emerges between the configuration-averaged adsorption energies irrespective of the site symmetry. Although these correlations represent a weaker form of the scaling relationships, they are sufficient to prohibit the optimization of multistep reactions. The underpinning of this behavior is twofold (1) the nearsightedness principle and (2) the narrow distribution of the adsorption energies around the mean-field value. While the nearsightedness is general for all electronic systems, the second criterion applies in HEAs with relatively strong reactive elements. The present findings strongly suggest that alloys may not generally enable the breaking of scaling relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2020

Superconductivity in a uranium containing high entropy alloy

Abstract High entropy alloys (HEA) are an unusual class of materials where mixtures of elements are stochastically arrayed on a simple crystalline lattice. These systems exhibit remarkable functionality, often along several distinct axes: e.g., the examples [TaNb] 1-x (TiZrHf) x are high strength and damage resistant refractory metals that also exhibit superconductivity with large upper critical fields. Here we report the discovery of an f -electron containing HEA, [TaNb] 0.31 (TiUHf) 0.69 , which is the first to include an actinide ion. Similar to the Zr-analogue, this material crystallizes in a body-centered cubic lattice with the lattice constant a = 3.41(1) Å and exhibits phonon mediated superconductivity with a transition temperatures T c ≈ 3.2 K and upper critical fields H c2 ≈ 6.4 T. These results expand this class of materials to include actinide elements, shows that superconductivity is robust in this sub-group, and opens the path towards leveraging HEAs as functional waste forms for a variety of radioisotopes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Porosity modeling in a TiNbTaZrMo high-entropy alloy for biomedical applications

High-entropy alloys (HEAs) have attracted great attention for many biomedical applications. However, the nature of interatomic interactions in this class of complex multicomponent alloys is not fully understood. We report, for the first time, the results of theoretical modeling for porosity in a large biocompatible HEA TiNbTaZrMo using an atomistic supercell of 1024 atoms that provides new insights and understanding. Our results demonstrated the deficiency of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with available experimental data to reduce Young's modulus. We utilized the novel concepts of the total bond order density (TBOD) and partial bond order density (PBOD) via ab initio quantum mechanical calculations as an effective theoretical means to chart a road map for the rational design of complex multicomponent HEAs for biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interfaces enhanced plasma irradiation resistance in CrMoTaWV/W multilayer films through blocking He diffusion

The performance of plasma-facing materials (PFMs) is one of the key factors that significantly impact the stability of operation in fusion reactors. Herein, a new CrMoTaWV/W (high entropy alloy (HEA)/W) multilayer structure is designed as PFM to investigate its resistance to He plasma irradiation. It was observed that the introduction of the interfaces effectively absorbed plenty of He atoms, preventing them from diffusing into the material and delaying the formation of fuzz incubation zone, therefore, enhancing the resistance to plasma irradiation. The thickness transformed to fuzz in the HEA/W multilayer films was observed to be about two-thirds of those in the CrMoTaWV (HEA) film. Additionally, the fuzz growth rates in HEA/W multilayer films are lower than the average growth rate of bulk W and HEA films combined. These findings highlight a promising new avenue for the exploration of high-performance PFMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Role of Static Displacements in Stabilizing Body Centered Cubic High Entropy Alloys

The configurational entropy of high entropy alloys (HEAs) plays little role in the stabilization of one particular crystal structure over another. We show that disorder-induced atomic displacements help stabilize body centered cubic (bcc) structure HEAs with average valences <4.7. These disorder-induced atomic displacements mimic the temperature-induced vibrations that stabilize the bcc structure of group IV elemental metals at high temperatures. The static displacements are significantly larger than for face centered cubic HEAs, approaching values associated with the Lindemann criterion for melting. Chemical disorder in high entropy alloys have a previously unidentified, nonentropic energy contribution that stabilizes a particular crystalline ground state.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Design metastability in high-entropy alloys by tailoring unstable fault energies

Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gradient cell–structured high-entropy alloy with exceptional strength and ductility

We report that similar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nanoscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant low-angle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nanoscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Diffusion-mediated chemical concentration variation and void evolution in ion-irradiated NiCoFeCr high-entropy alloy

High-entropy alloys (HEAs) are proposed as potential structural materials for advanced nuclear systems, but little is known about the response of matrix chemistry in HEAs upon irradiation. Here, we reveal a substantial change of matrix chemical concentration as a function of irradiation damage (depth) in equiatomic NiCoFeCr HEA irradiated by 3 MeV Ni ions. After ion irradiation, the matrix contains more Fe/Cr in depth shallower than ~900–1000 nm but more Ni/Co from ~900–1000 nm to the end of the ion-damaged region due to the preferential diffusion of vacancies through Fe/Cr. Preferential diffusion also facilitates migration of vacancies from high radiation damage region to low radiation damage region, leading to no void formation below ~900–1000 nm and void formation around the end of the ion-damaged region at a fluence of 5 × 10 16 cm -2 (~123 dpa, displacements per atom, peak dose under full cascade mode). As voids grow significantly at an increased fluence (8 × 10 16 cm -2 , 196 dpa), the matrix concentration does not change dramatically due to new voids formed below ~900–1000 nm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗