Phase Formation Of High-entropy Alloys Research Articles

Nanostructured High Entropy Alloys as Structural and Functional Materials.

Since their introduction in 2004, high entropy alloys (HEAs) have attracted significant attention due to their exceptional mechanical and functional properties. Advances in our understanding of atomic-scale ordering and phase formation in HEAs have facilitated the development of fabrication techniques for synthesizing nanostructured HEAs. These materials hold immense potential for applications in various fields including automobile industries, aerospace engineering, microelectronics, and clean energy, where they serve as either structural or functional materials. In this comprehensive Review, we conduct an in-depth analysis of the mechanical and functional properties of nanostructured HEAs, with a particular emphasis on the roles of different nanostructures in modulating these properties. To begin, we explore the intrinsic and extrinsic factors that influence the formation and stability of nanostructures in HEAs. Subsequently, we delve into an examination of the mechanical and electrocatalytic properties exhibited by bulk or three-dimensional (3D) nanostructured HEAs, as well as nanosized HEAs in the form of zero-dimensional (0D) nanoparticles, one-dimensional (1D) nanowires, or two-dimensional (2D) nanosheets. Finally, we present an outlook on the current research landscape, highlighting the challenges and opportunities associated with nanostructure design and the understanding of structure-property relationships in nanostructured HEAs.

Structure and Properties of Melt-Quenched Al<sub>4</sub>CoCrCuFeNi High-Entropy Alloy

The structure and mechanical properties of a multicomponent high-entropy Al4CoCrCuFeNi alloy in the as-cast and melt-quenched states were investigated. The alloy composition was analyzed based on the literature criteria for predicting the phase formation in high-entropy alloys, which considered the entropy and enthalpy of mixing, valence electron concentration as well as the atomic size difference of the components. The alloy films were synthesized by quenching from the melt using a splat-quenching technique. The cooling rate of the films was estimated to be ~ 106 K/s based on the film thickness. The X-ray diffraction analysis revealed that both as-cast and melt-quenched Al4CoCrCuFeNi alloy samples had an ordered B2 phase in their structure. The microhardness of the as-cast alloy was 6500 MPa, while the microhardness of the melt-quenched film was significantly higher and reached 9400 MPa.

Unraveling phase prediction in high entropy alloys: A synergy of machine learning, deep learning, and ThermoCalc, validation by experimental analysis

The phase formation in high entropy alloys (HEAs) presents a significant challenge due to the complexity of their composition and the intricate interactions between multiple elements. The machine learning (ML) and deep learning (ANN) models play a crucial role in phase prediction for HEAs owing to their capability to handle intricate, multi-dimensional datasets and capture nuanced relationships between composition and phase formation. This article seeks to enhance the understanding of phase prediction in HEAs by utilizing ML, ANN, ThermoCalc, and experimental validation techniques. Parameters such as δ, VEC, and Tm, influential in predicting phases, were discerned using the Pearson correlation method. Various ML models, including kneighbors, bagging, adaboost, decision tree, extra trees, and ANN, were employed for predicting phase formation in HEAs. The ANN model exhibited an impressive accuracy of 90.62 %, while the extra trees model achieved an accuracy of 89.73 %. These ML and ANN models adeptly predicted the observed phases in experimental results, correctly identifying both HEAs Co10Cr19Fe30Mn23Ni9Ti8 and Co7Cr22Fe29Mn24Ni14Ti4 as having a face-centered cubic (FCC) + intermetallic (IM) structure. However, it is noteworthy that ThermoCalc and other ML models almost misclassified these HEAs. Both alloys primarily consist of an intermetallic phase enriched in titanium (Ti) and manganese (Mn) while exhibiting a noticeable depletion of iron (Fe) content. A comparison of these approaches underscores the significance of experimental validation in assessing the accuracy and reliability of phase predictions in HEAs, revealing the strengths and limitations of each method.

Prediction of phase via machine learning in high entropy alloys

High Entropy Alloys (HEAs) are a new group of materials with numerous applications. Phase formation in HEAs is necessary for their qualities, but it is difficult to anticipate them effectively. In this study, we are implementing a support vector machine (SVM) model, we separate the model into stable body centre cubic (BCC), face centre cubic (FCC) and a few HEAs with help of cross-validation. From 381 as-cast data the model was used to predict the same atom HEAs of 81 FCC and 155 BCC, with the remaining being FCC + BCC and intermetallic from the compositional space of elements in 14 metals, with accuracy above 86% in training and testing. With much higher prediction accuracy, machine learning methods have been utilised in this study to categorise and identify the phases in HEAs with comparability-predicted precision. Five Thermodynamic features are estimated based on prior research. Various selection strategies were applied to quantify the feature relevance. Entropy variation is discovered to be the least prominent aspect using feature importance.

A machine learning framework for discovering high entropy alloys phase formation drivers

In the past years, high entropy alloys (HEAs) witnessed great interest because of their superior properties. Phase prediction using machine learning (ML) methods was one of the main research themes in HEAs in the past three years. Although various ML-based phase prediction works exhibited high accuracy, only a few studied the variables that drive the phase formation in HEAs. Those (the previously mentioned work) did that by incorporating domain knowledge in the feature engineering part of the ML framework. In this work, we tackle this problem from a different direction by predicting the phase of HEAs, based only on the concentration of the alloy constituent elements. Then, pruned tree models and linear correlation are used to develop simple primitive prediction rules that are used with self-organizing maps (SOMs) and constructed Euclidean spaces to formulate the problem of discovering the phase formation drivers as an optimization problem. In addition, genetic algorithm (GA) optimization results reveal that the phase formation is affected by the electron affinity, molar volume, and resistivity of the constituent elements. Moreover, one of the primitive prediction rules reveals that the FCC phase formation in the AlCoCrFeNiTiCu family of high entropy alloys can be predicted with 87% accuracy by only knowing the concentration of Al and Cu.

Reactive interdiffusion of an Al film and a CoCrFeNi high-entropy alloy at elevated temperatures

The phase evolution of alloys is closely related to atomic diffusion. The influence of reactive diffusion on phase formation in high-entropy alloys (HEAs) is however still unclear. The present work systematically investigates the phase evolution of a multicomponent CoCrFeNi/Al diffusion couple through isochronous-reactive interdiffusion experiments. This provides a direct way to study the influence of enthalpy and entropy on the phase formation and element diffusion behavior. At temperatures below 1173 K, the enthalpy contribution dominates the total energy, leading to the formation of intermetallic compounds. When the temperature is in the range of 1173–1573 K, the entropy of mixing starts to play a more important role. This causes diffusion of Al towards the HEA without phase transformation, forming a more disordered state on the microscale. Even after the system reaches a disordered state, the enthalpy contribution cannot be totally ignored, which is reflected by the uphill diffusion of Ni towards Al. This demonstrates the combined effects of entropy and enthalpy on the phase formation in HEAs at elevated temperatures. Considering the homologous temperature for different equimolar alloys reveals that a multicomponent configuration does not stabilize the disordered state, while the mixing enthalpies between atomic pairs have a large impact on the transition temperature from ordered to disordered state. Finally, it is shown that surface modification of the HEA can be realized through a combination of film deposition and annealing processes. Compared to the HEA matrix, the formation of intermetallic compounds results in a hard surface layer. After the system becomes disordered, the higher hardness of the film side compared to the matrix can be attributed to the lattice distortion induced by Al.

CURRENT DIRECTIONS OF THEORETICAL DEVELOPMENTS REGARDING THE USE OF IRON-BASED ALLOYS

The article proves that important achievements of theoretical developments regarding the use of iron-based alloys are the scientific works of domestic researchers. Thus, in the dissertation research of Karpets M.V. for the first time, the phase composition, microstructure and physicо-mechanical properties of alloys of the Сr-Ni-Co-Fe-Cu-Al system in the concentration range (0-3 mol) of the content of chemical elements were systematically investigated. It was established that in the studied system, due to the high entropy of mixing, only simple solid substitution solutions based on fcc and bcc structures are formed, which are characterized by a high complex of physical and mechanical properties that are not inherent to any of the constituent components. It is substantiated that the main factor of phase formation in high-entropy alloys is the value of the average electron concentration of the alloy. The interval of values ​​of the average electron concentration, in which bcc or fcc structures exist, depends on the rate of crystallization of the melt and the presence of elements prone to liquation in the alloy. Stabilizing elements of solid solutions based on phases with bcc (Al, Cr) and fcc (Cu, Ni, Co) structures were established. A significant scientific achievement should be considered the first developed high-entropy CrMnFeCoNi2Cu alloy based on a solid solution with an fcc phase structure, capable of being deformed by rolling at room temperature by 98% without the appearance of cracks or tears. Its phase composition, microstructure, and physical and mechanical properties at all stages of deformation were studied. It is shown that, for the first time in Ukraine, during cold rolling in the high-entropy CrMnFeCoNi2Cu alloy, similar to pure metals and alloys with an fcc structure, a rolling texture with the main component appears. The article provides examples of other theoretical developments regarding the use of iron-based alloys.

Method to identify the phase structures of high entropy alloys with modified lattice distortion enthalpy

Severe lattice distortion is one of important characteristics of high entropy alloys (HEAs) and exercises considerable influence over phase structures, and atomic volume V is thought to be the key factor for lattice distortion. In the present work, the calculation of V was modified by taking the stacking density effects into consideration, and the calculation of lattice distortion enthalpy (∆HLD) caused by elastic lattice distortion for HEAs was optimized accordingly. With this method, two phase structure formation rules were proposed: valence electron concentration(VEC)−∆HLD rule for crystal structure of solid solution and chemical enthalpy(∆Hchem)−∆HLD rule for phase composition. The prediction effect of these two rules were verified by analyzing 100 existing HEAs, and the intrinsic effect of lattice elastic distortion on the phase formation of HEAs were discussed. The results of the research would be helpful in the composition design of HEAs.

Machine Learning Based Prediction of Phases in High-Entropy Alloys

Intro: The vastness of high-entropy alloys (HEAs) compositional space and breadth of microstructures makes it possible to tailor properties required by an application. Predicting the phase formation is therefore important in the design of future HEAs. Machine learning based studies on high-entropy alloys are still relatively scarce and non-standardized. Objectives: this paper reports on the implementation of ML-based classifiers techniques compares the performance of Decision Tree (DT) and Random Forest (RF) for the prediction of phase formation in HEAs. Results: A new dataset based on 1460 microstructural observations collected from 418 peer-reviewed studies was curated. It contains 36 metallurgy-specific predictor features and a dependent variable, which referred to the phase formation. Based on recursive feature-elimination algorithm an expansive collection of predictive feature for future studies is proposed in addition to widely employed features such difference in the electro-negativities (Δχ) and atomic size (δ), valence electron concentration (VEC), mixing enthalpy (ΔHm), and configuration entropy (ΔSm). The RF model yields higher discriminative performance compared to the DT classifier as well as other tree-based benchmark models. The RF model should be the first choice for investigators when building classification. All models shows lower classification accuracy when intermetallic compounds. Summary: These results suggest classic machine learning algorithms may be sufficient to develop high quality predictive models of phase formation in HEAs.

The phase selection via machine learning in high entropy alloys

The phase formation of high entropy alloys (HEAs) is diversity due to the breadth of the composition space. Most of the studies about phase formation are based on features of solid solution. However, the establishment of the link between compositions and phase formation plays an important role in accelerating novel HEAs development. To achieve this aim, we employed the support vector machine (SVM) to build phase selection models with both the composition dataset and the thermodynamic parameters dataset. The accuracies of both models are above 85%. A dataset with more than a thousand data has been established, which covers 18 elements and most of the HEAs families. The feature dataset was transferred by calculation of thermodynamic parameters. The similar accuracies of the models with compositions dataset and with thermodynamic parameters proved that the prediction of phase formation in HEAs can be carried out directly from compositions. Our models provide a universal approach of phase formation prediction in HEAs.

Effects of Mutual Interaction between Constituent Elements on Phase Formation of High Entropy Alloys

High entropy alloys (HEAs) are alloys that contains multiple elements, often five or more principal elements in equiatomic or near equiatomic ratio with or without minor elements. As felt from the name, high mixing entropy is the sole parameter to decide the solid solution alloy formation in HEAs but, the mutual interaction between elements are key parameters to predict the phase formation in HEAs as proposed by some researchers.

Big-data analysis of phase-formation rules in high-entropy alloys

Big-data analysis of phase-formation rules of high-entropy alloys (HEAs) was conducted and a phase formation rule from a dynamic view was deduced. It was indicated in literatures that cooling rate has a strong influence on the phase formation of HEAs. Higher cooling rate may promote the generation of amorphous phase, and accordingly suppress the formation of intermetallics. Meanwhile, it was also shown that cooling rate had little impact on the formation of solid-solution phase. To demonstrate this rule, a series of FeCoNi(AlSiB)x HEAs ribbons were fabricated by a melt-spinning technique, and the microstructure, mechanical, and magnetic properties were also investigated. The results show that all ribbons exhibit disordered solid-solution structure. The addition of boron changes the alloy from ductility to brittleness, but without evident change of magnetic properties. The alloy in the nominal composition of FeCoNi(AlSi)0.2 has the best combination of mechanical and magnetic properties. A distinct feature of HEAs in magnetization was noticed and explained.

Amorphous phase formation rules in high-entropy alloys**Project supported by the National Natural Science Foundation of China (Grant No. 51471025).

There have been many interesting studies on high-entropy alloys (HEAs), also known as multi-component (MC) alloys (MCAs), in recent years. MC metallic-glasses (MGs) have shown the potential to express the advantages of MCAs and MGs in tandem. Amorphous phase formation rules are a crucial issue in the HEA and MCA field. For equal or near-equal atomic ratio alloys, mixed-entropy among the elements has a significant effect on the phase formation. This paper focuses on HEA amorphous phase formation rules. In the first two sections, the recent progress in amorphous phase formation in HEAs and MCAs is reviewed, including the effective factors and correlative parameters related to amorphous phase formation. In the third section, novel MCMGs including high-entropy (HE) bulk-metallic-glass (HE-BMG) and MCMG films developed in recent decades are summarized, and the giant-magnetic-impedance (GMI) effect of MC amorphous fibers is discussed.

Design of Light-Weight High-Entropy Alloys

High-entropy alloys (HEAs) are a new class of solid-solution alloys that have attracted worldwide attention for their outstanding properties. Owing to the demand from transportation and defense industries, light-weight HEAs have also garnered widespread interest from scientists for use as potential structural materials. Great efforts have been made to study the phase-formation rules of HEAs to accelerate and refine the discovery process. In this paper, many proposed solid-solution phase-formation rules are assessed, based on a series of known and newly-designed light-weight HEAs. The results indicate that these empirical rules work for most compositions but also fail for several alloys. Light-weight HEAs often involve the additions of Al and/or Ti in great amounts, resulting in large negative enthalpies for forming solid-solution phases and/or intermetallic compounds. Accordingly, these empirical rules need to be modified with the new experimental data. In contrast, CALPHAD (acronym of the calculation of phase diagrams) method is demonstrated to be an effective approach to predict the phase formation in HEAs as a function of composition and temperature. Future perspectives on the design of light-weight HEAs are discussed in light of CALPHAD modeling and physical metallurgy principles.

High-entropy alloy: challenges and prospects

High-entropy alloys (HEAs) are presently of great research interest in materials science and engineering. Unlike conventional alloys, which contain one and rarely two base elements, HEAs comprise multiple principal elements, with the possible number of HEA compositions extending considerably more than conventional alloys. With the advent of HEAs, fundamental issues that challenge the proposed theories, models, and methods for conventional alloys also emerge. Here, we provide a critical review of the recent studies aiming to address the fundamental issues related to phase formation in HEAs. In addition, novel properties of HEAs are also discussed, such as their excellent specific strength, superior mechanical performance at high temperatures, exceptional ductility and fracture toughness at cryogenic temperatures, superparamagnetism, and superconductivity. Due to their considerable structural and functional potential as well as richness of design, HEAs are promising candidates for new applications, which warrants further studies.

Guidelines in predicting phase formation of high-entropy alloys

Abstract

A system for generating process and material selection advice during embodiment design of mechanical components

High-entropy alloys (HEAs) are presently of great research interest in materials science and engineering. Unlike conventional alloys, which contain one and rarely two base elements, HEAs comprise multiple principal elements, with the possible number of HEA compositions extending considerably more than conventional alloys. With the advent of HEAs, fundamental issues that challenge the proposed theories, models, and methods for conventional alloys also emerge. Here, we provide a critical review of the recent studies aiming to address the fundamental issues related to phase formation in HEAs. In addition, novel properties of HEAs are also discussed, such as their excellent specific strength, superior mechanical performance at high temperatures, exceptional ductility and fracture toughness at cryogenic temperatures, superparamagnetism, and superconductivity. Due to their considerable structural and functional potential as well as richness of design, HEAs are promising candidates for new applications, which warrants further studies.