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98 records · Page 6

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DOE OSTI2022

Spark plasma sintered, MoNbTi-based multi-principal element alloys with Cr, V, and Zr

MoNbTi, MoNbTiZr, CrMoNbTiZr, and MoNbTiVZr multi-principal element alloys (MPEAs) were fabricated via spark plasma sintering (SPS) and investigated for use in high-strength applications. The fabrication method by SPS and powder metallurgy differs from those presented in the prior literature, where most MPEAs are fabricated using arc melting (AM) methods. Here cryogenic milling was used to maximize potential defect sinks (grain boundaries) for radiation resistance and to increase ultimate tensile strength through the Hall-Petch effect. SPS was chosen for consolidation in order to maintain a fine-grained structure during densification. Each alloy was characterized using x-ray diffraction and scanning electron microscopy for phase identification and compositional homogeneity. The base ternary alloy MoNbTi presented a predominantly single BCC system with minor cubic phases. The introduction of additional alloying elements—Zr, V, and Cr—heightened the phase complexity and increased the fractions of a secondary BCC phase and an HCP phase from Zr. The addition of Cr induced a larger fraction of the Laves phase to form. The addition of V caused the precipitation of small Mo inclusions. Thermodynamic analysis was performed to understand the separation of phases in each alloy. Discrepancies among the phase predictions generated by thermodynamic models, phases previously presented in the literature, and the characterization results suggest that MPEA fabrication methods, especially solid-state methods, require significant investigation to ensure that alloys can remain stable throughout their anticipated service lifetimes.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Gas nitriding behavior of refractory metals and implications for multi-principal element alloy design

Multi-principal element alloys (MPEAs) comprise a large, flexible compositional space that enables tuning of their chemistry, structure, and properties. Here, to facilitate the development of nitriding-based surface-enhancement strategies that harness a broad compositional space, this study examined the gas nitriding behavior of Hf, Mo, Nb, Ta, Ti, and Zr as a function of time, temperature (750 and 1000 °C), and nitriding potential (i.e. ammonia-to-hydrogen ratio). These metals were selected because they have a strong driving force to form nitrides, and appear in many promising refractory MPEA compositions. The nitriding temperatures were selected based on the phase transformation temperature of Ti and Zr, and the nitriding potentials were chosen such that all elements are expected to form nitrides. Mass gain measurements indicate that all six elements follow parabolic kinetics. The microstructure observations and quantitative microchemical analysis show formation of dense and well-adhered compound layers for Mo, Nb, and Ta. Thick diffusion zones appear in Hf, Ta, Ti, and Zr, and diffusion coefficients were fit to the composition profiles. Partial delamination of the compound layer occurred for Ti and Zr. Peak hardness values above 30 GPa are obtained in the dense compound layers, and the solute hardening of the underlying alloy is correlated with the nitrogen content. The results provide insight into the dynamics of nitride compound formation relative to interstitial dissolution of nitrogen, and are discussed in the context of MPEA composition and processing design.

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 OSTI2022

Distilling physical origins of hardness in multi-principal element alloys directly from ensemble neural network models

Abstract Despite a plethora of data being generated on the mechanical behavior of multi-principal element alloys, a systematic assessment remains inaccessible via Edisonian approaches. We approach this challenge by considering the specific case of alloy hardness, and present a machine-learning framework that captures the essential physical features contributing to hardness and allows high-throughput exploration of multi-dimensional compositional space. The model, tested on diverse datasets, was used to explore and successfully predict hardness in Al x Ti y (CrFeNi) 1- x - y , Hf x Co y (CrFeNi) 1- x - y and Al x (TiZrHf) 1- x systems supported by data from density-functional theory predicted phase stability and ordering behavior. The experimental validation of hardness was done on TiZrHfAl x . The selected systems pose diverse challenges due to the presence of ordering and clustering pairs, as well as vacancy-stabilized novel structures. We also present a detailed model analysis that integrates local partial-dependencies with a compositional-stimulus and model-response study to derive material-specific insights from the decision-making process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Gas-phase oxidation and nanoparticle formation in multi-element laser ablation plumes

The evolution from gas-phase oxidation to nanoparticle and agglomerate formation was studied in nanosecond laser-produced plasmas of a multi-principal element alloy target in air. Here gas-phase oxidation of plasma species was monitored in situ via optical emission spectroscopy, while a custom-built single particle mass spectrometer was used to measure size and compositions of agglomerated nanoparticles formed in laser ablation plumes. Ex situ analysis employing transmission electron microscopy was used to study nanoparticle morphology, crystal structure, and element distribution at the nanoscale. Emission spectra indicate that gas-phase oxidation of elements in the alloy target are formed at varying times during plume evolution, and mass spectrometry results indicate fractal agglomerates contain all principal alloying elements and their oxides. Finally, electron microscopy characterization illustrates that these agglomerates consist of multiple material types: sub-10 nm diameter amorphous, multi-element nanoparticles, ≈10–30 nm diameter Ti-rich crystalline oxide nanoparticles, and ejected base material. Results highlight that the multi-component target composition impacts molecular formation in the gas phase and the morphology, composition, and structure of nanoparticles and agglomerates formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Charge-density based evaluation and prediction of stacking fault energies in Ni alloys from DFT and machine learning

36 MATERIALS SCIENCE↗

DOE OSTI2022

Multi-principal element grain boundaries: Stabilizing nanocrystalline grains with thick amorphous complexions

Amorphous complexions have recently been demonstrated to simultaneously enhance the ductility and stability of certain nanocrystalline alloys. In this study, three quinary alloys (Cu–Zr–Hf–Mo–Nb, Cu–Zr–Hf–Nb–Ti, and Cu–Zr–Hf–Mo–W) are studied to test the hypothesis that increasing the chemical complexity of the grain boundaries will result in thicker amorphous complexions and further stabilize a nanocrystalline microstructure. Significant boundary segregation of Zr, Nb, and Ti is observed in the Cu–Zr–Hf–Nb–Ti alloy, which creates a quaternary interfacial composition that limits average grain size to 63 nm even after 1 week at ~ 97% of the melting temperature. This high level of thermal stability is attributed to the complex grain boundary chemistry and amorphous structure resulting from multi-component segregation. Furthermore, high-resolution transmission electron microscopy reveals that the increased chemical complexity of the grain boundary region in the Cu–Zr–Hf–Nb–Ti alloy results in an average amorphous complexion thickness of 2.44 nm, approximately 44% and 32% thicker than amorphous complexions previously observed in Cu–Zr and Cu–Zr–Hf alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Understanding Twinning and Deformation in High Entropy Alloys

A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE cor- relations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. This model opens a possibility to use charge density as a descriptor for predicting SFE in alloys. Furthermore, a descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. We illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R2 of 6.18 mJ/m2 and 0.87, respectively, validating the accuracy of the proposed approach.

36 MATERIALS SCIENCE↗