Formation Of High-entropy Alloys Research Articles

Mechanical and tribological characteristics of nickel-rich CoCrCuxFeNi2 high entropy-alloys

This research explores the potential to enhance the copper solubility limit in high-entropy alloys (HEAs) within the CoCrCuFeNi system by increasing the nickel content twofold and applying additional heat treatment. The CoCrCuxFeNi2 HEAs were synthesized through mechanical alloying of elemental powders followed by hot pressing. The study investigated the microstructure and phase composition of CoCrCuxFeNi2 HEAs in relation to varying copper concentrations (x = 0; 0.25; 0.5; 0.75; 1.0). The evaluation of the alloy matrix's chemical composition, which is based on the FCC solid solution, enabled the determination of copper solubility. It was found that doubling the nickel content, relative to the equiatomic ratio, facilitated the formation of HEAs with a homogenous FCC structure for copper concentrations up to x ≤ 0.75. Further heat treatment of these HEAs resulted in an enhanced copper solubility of up to 17.5 at.%. The mechanical and tribological properties of CoCrCuxFeNiy HEAs were also assessed, revealing significant improvements in tensile strength (ranging from 910 to 1045 MPa) and hardness (285–395 HV) for the CoCrCuxFeNi2 alloys. Despite the increased copper solubility limit, the heat treatment process caused a decline in mechanical properties by 35–50 %, attributed to grain size enlargement to 5.5 μm. The CoCrCu0.75FeNi2 and CoCrCuFeNi2 alloys exhibited the lowest wear rates when tested against Al2O3 counterbody, with wear rates of 1,58·10–5 and 1,48·10–5 mm3/(N·m), respectively.

An end-to-end machine learning framework exploring phase formation for high entropy alloys

Exploring the rules of high entropy alloys (HEAs) phase formation has clear guiding significance for the design of new alloys. An end-to-end framework was proposed to select the feature subset and machine learning (ML) model from the feature pool and model pool, respectively. In this framework, each model in the pool is to determine its materials feature subset based on the feature importance. The final model was confirmed through the evaluation of the fitting result of every model and its feature subset. This method extracts important factors affecting the phase formation of HEAs. The results show that the chosen model could classify 430 HEAs into five phases, with test accuracy of 87.8%. And the model analysis suggests that the formation of single-phase solid solution is often inhibited when the atomic size difference is greater than 8.295%.

Comparison on structural andmagnetic properties of FeCoNi medium entropy alloy, FeCoNiAl and FeCoNiAlTi high entropy alloys

In the present study, we investigated the effect of configurational entropy on the phase evolution and magnetic properties of medium and high-entropy alloys. Three different, FeCoNi medium entropy alloys (MEA), FeCoNiAl, and FeCoNiAlTi high entropy alloys (HEAs) were synthesized through the mechanical alloying technique (MA). XRD analysis revealed the formation of the single fcc phase structure for FeCoNi MEA. The mixture of bcc and fcc phase is formed forFeCoNiAl HEA. However, for FeCoNiAlTi HEA the mixture of fcc, and bcc phases, along with a minor fraction of intermetallic R-phase is confirmed through the fitting of XRD data. The magnetic properties of FeCoNi MEA changed drastically by adding Al and Al, Tiwith Fe, Co, Ni as alloying elements for the formation of HEAs. The values of saturation magnetization (Ms) and coercivity (Hc) for FeCoNi MEA are 133.7 emu/g and 26.1 Oe, respectively. For FeCoNiAl HEA, the value of Ms decreased to 85.4 emu/g, and Hc increased to 74.2 Oe. However, for FeCoNiAlTiHEA, the value of Ms is reduced to 52.50 emu/g, and Hc increased to 90.55Oe. The present study clearly shows that the addition of different alloying elements significantly impacts the phase formation and the magnetic behavior of the MEA and HEAs.

OVERVIEW OF THE HIGH-ENTROPY ALLOYS CONCEPT

The article presents a review of the results of research on high-entropy alloys, describing the principles of their formation, the basic concepts and properties of high-entropy alloys. The existing categories of the entropic alloys are listed. The effects resulting from the formation of high-entropy alloys are described: high entropy, lattice distortion, sluggish diffusion and cocktail effects. It is noted that the traditional thermodynamic representations for multicomponent alloys require additions. It is also noted that the application of Hume-Rothery rules to predict the phase composition of high-entropy alloys shows some difficulties, since it is difficult to select a large number of elements having the same type of lattice and valence. The results of the analysis of a number of parameters and conditions which, according to the researchers' opinion, affect the structural state created by high-entropy alloys, taking into account which could allow to correctly predict the formation of structures in high-entropy. Analysis of the literature data has shown that at present there is no universal parameter that could allow the correct prediction of the formation of structures in multicomponent alloys systems. Methods for the preparation of powders of high entropy alloys are presented. The results of frequently used methods of obtaining coatings on the basis of high-entropy alloys, such as laser cladding, magnetron sputtering, electrochemical deposition and thermal spraying are reviewed. Disadvantages of obtaining coatings methods are described.

Influence of Laser Direct Energy Deposition Process Parameters on the Structure and Phase Composition of a High-Entropy Alloy FeCoNiCrMn

High-entropy alloys are a unique class of alloys with high strength and hardness, good enduring quality and corrosion resistance, as well as other attractive mechanical properties for both scientific research and practical applications. Using these unique alloys together with the dynamically developing technology of laser direct energy deposition (L-DED) carries the prospects of obtaining large-sized complex-profile products with specified increased mechanical properties. The study of the influence of L-DED parameters on the formation of high-entropy alloys will expand knowledge about the influence of temperature and cooling rate on the formation of the structure, on the mechanical characteristics of high-entropy alloys and the formation of defects and use them for thermal processes involving high-entropy alloys. Preliminary modeling will predict the phase composition of alloys in conditions of high heating and cooling rates. In the work, optimal parameters were selected for obtaining high-entropy alloys based on FeCoNiCrMn by L-DED technology. It was also shown that FeCoNiCrMn alloys were divided into areas with a high content of elements (Fe, Co, Cr) and (Mn, Ni, Cu).

A molecular dynamics study of atomic diffusion effects on thermomechanical properties applying laser additive alloying process for the Cantor high entropy alloy

High entropy alloys (HEAs) can be manufactured in many conventional ways, but it becomes difficult to fabricate heterogeneous materials and structures. The Selective Laser Melting (SLM) method generally melts pure elemental powders or prefabricated alloy powders without an alloying process. In-situ alloying in SLM, which is also called Laser Additive Alloying (LAA), using pure elemental powders becomes a promising method for creating HEA with heterogeneous structures. However, the effect of the diffusion of elements in the molten pool on the formation of HEA remains unclear. In this paper, the well-discussed Cantor HEA was studied in an in-situ alloying situation, where pure elemental powders (Co, Cr, Mn, Ni, Fe) distributed on a powder bed were irradiated by laser and were subsequently allowed to cool back to room temperature. The diffusion of specific elements, with respect to their original clusters, was tracked via Mean Square Displacement (MSD) as well as the final composition of key locations. Our model was verified by showing a good agreement with the overall average diffusion rates of each element in the Cantor HEA qualitatively in other works from literature. Results initially showed that as the energy density increases, better diffusion was observed through a pixel overlay analysis focusing on the mixing of different elements. The best-case scenario of diffusion from the pixel overlay map indicated a strong presence of 3 to 4 elements after the laser scanning. Given the conditions in the MD simulation, there was no apparent segregation of elements during the alloying process. The solidified powder bed was sectioned into a 5 by 4 grid to analyze the composition of the entire powder bed. In addition, we also conducted a simulation by implementing a 0.03 nm/ps laser scanning in a meander 2-track scan to completely melt the powder bed. After cooling and equilibration, Polyhedral Template Analysis was applied to analyze the crystal structure of the solidified powder bed in the presence of increasing components. When alloying the Cantor alloy all elements experience a complex diffusion behavior, elements like Cr experience fairly rapid diffusion rates compared to other elements, despite this, Cr only diffuses for a short period and diffuses minimally during the process. The analysis of element-specific behavior, such as diffusion, can provide a framework for the LAA production of HEA. This MD study provides a detailed analysis about the effect of diffusion on the formation of HEA system if in-situ alloying is adopted, this study is further extended to analyze the effect of diffusion on the thermomechanical properties of HEAs. Moreover, Young's Modulus, Shear Modulus, and lattice thermal conductivity coefficient were simulated and compared with published experimental works. Lastly, the diffusion coefficients were calculated in 3 near-equimolar alloys and 3 alloys with various Fe atomic percentages to study the effects of entropy on the tracer diffusion rates. The findings in this study in terms of diffusion behavior can assist the design and manufacturing of other novel HEAs for applications in extreme environments.

Predicting single-phase solid solutions in as-sputtered high entropy alloys: High-throughput screening with machine-learning model

Searching for single-phase solid solutions (SPSSs) in high-entropy alloys (HEAs) is a prerequisite for the intentional design and manipulation of microstructures of alloys in vast composition space. However, to date, reported SPSS HEAs are still rare due to the lack of reliable guiding principles for the synthesis of new SPSS HEAs. Here, we demonstrate an ensemble machine-learning method capable of discovering SPSS HEAs by directly predicting quinary phase diagrams based only on atomic composition. A total of 2198 experimental structure data are extracted from as-sputtered quinary HEAs in the literature and used to train a random forest classifier (termed AS-RF) utilizing bagging, achieving a prediction accuracy of 94.6% compared with experimental results. The AS-RF model is then utilized to predict 224 quinary phase diagrams including ∼32,000 SPSS HEAs in Cr-Co-Fe-Ni-Mn-Cu-Al composition space. The extrapolation capability of the AS-RF model is then validated by performing first-principle calculations using density functional theory as a benchmark for the predicted phase transition of newly predicted HEAs. Finally, interpretation of the AS-RF model weighting of the input parameters also sheds light on the driving forces behind HEA formation in sputtered systems with the main contributors being: valance electron concentration, work function, atomic radius difference and elementary symmetries.

AlCo-rich AlCoNiFe and AlCoNiFeCr high entropy alloys: Synthesis and interaction pathway at high heating rates

Novel AlCo-rich AlCoNiFe and AlCoNiFeCr high entropy alloys (HEAs) were prepared from the non-activated and mechanically activated (MA) quaternary Al40Co40Ni10Fe10at% and quinary Al35Co35Ni10Fe10Cr10at% mixtures. The wide temperature range of the formation of a single high entropy alloy of BCC structure in quaternary system and the formation of pure quinary AlCoNiFeCr alloy above 740 °C was predicted by thermodynamic modelling. The underlying interaction mechanism was proposed, and the effective activation energy values were deduced at high heating rates up to 2600 °C·min−1 by thermal analysis method through high-speed temperature scanner. The presence of a single-stage exothermic interaction in the non-activated and mechanically activated quaternary and quinary mixtures was attributed to HEA formation via either solid + liquid or solid + solid mechanism depending on the heating rate and mechanoactivation (MA) duration. The influence of heating rate and MA duration on the self-heating profile and reaction onset temperature was also deduced. Microstructure evolution and phase formation sequence were monitored by the examination of products quenched at characteristic temperatures at synthesis and processing of AlCo-rich AlCoNiFe and AlCoNiFeCr HEAs. The crystallite size (CS), lattice strain (LS) and lattice parameter (LP) of CoFeNiAl and CoFeNiAlCr HEAs were estimated according to MA duration. The thermal stability in argon and air flow conditions at heating rate of 40 °C·min−1 for up to 1200 °C was studied by thermogravimetric analyser complemented with X-ray diffraction analysis.

Phase prediction and effect of intrinsic residual strain on phase stability in high-entropy alloys with machine learning

The phase formation and stability of high-entropy alloys (HEAs) are crucial to their properties, but the efficient prediction of them remains challenging due to the associated vastness of the composition space. In the present work, we study the formation and stability of solid-solution (SS) phases with a dataset consisting of 656 HEAs using machine learning (ML). We demonstrate the independence of nine physical parameters by self-organizing map (SOM) algorithm and rank them by feature importance methods, discovering that the root mean square residual strain (εrmsm s) is the most critical parameter. Based on the theoretical calculations and parallel coordinates plot (PCP) technique, we find that εrms can be used to quantitatively predict the stability of SS phases. Moreover, we apply the support vector machine, gradient boosting decision tree, multi-layer perceptron, and logistic regression algorithms to predict the formation of SS phases with testing accuracy values of 95.22 %, 94.78 %, 90.87%, and 89.57 %, respectively. Our results provide a perspective on the stability of SS phases from the viewpoint of intrinsic residual strain and show the support vector machine could be a better algorithm to predict the phase formation of HEAs.

Os-Free Fe<sub>12</sub>Ir<sub>20</sub>Re<sub>20</sub>Rh<sub>20</sub>Ru<sub>28</sub> High-Entropy Alloy with Single hcp Structure Including Fe from Late Transition Metals

Os-free alloys with compositions of Fe12Ir20Re20Rh20Ru28 and Ir25Re25Rh25Ru25 (at%) from an Ir–Re–Rh–Ru system with and without Fe are prepared via conventional arc-melting and subsequent annealing to examine their formation into a single hexagonal close-packed (hcp) structure as high-entropy alloys (HEAs). These alloys are derived by referring to Yunseko et al., who reported the formation of HEAs with a single hcp structure in a near-equiatomic composition (∼Ir20Os20Re20Rh20Ru20) achieved via a chemical reaction. The aim of the present study is to exclude Os from the prototypical HEA (the quinary exact equiatomic Ir20Os20Re20Rh20Ru20 alloy) to prevent hazardous osmium tetroxide (OsO4) from volatilizing in a bulk sample. Fe12Ir20Re20Rh20Ru28 alloy is set as the target alloy by replacing Os with Fe0.6Ru0.4 in the prototypical HEA. The X-ray diffraction (XRD) profile of the Fe12Ir20Re20Rh20Ru28 alloy annealed at 2273 K for 1 h shows an hcp structure, and further scanning electron microscopy (SEM) observations combined with elemental mapping via energy dispersive X-ray spectroscopy (EDX) confirmed a single hcp structure. The XRD profiles of the other samples (the Fe12Ir20Re20Rh20Ru28 alloy in both as-prepared and annealed at 2000 K for 1 h states, and the Ir25Re25Rh25Ru25 alloy in both as-prepared and annealed at 2273 K for 1 h states) exhibit a combination of hcp structures, based on XRD, SEM, and EDX observations. The Fe12Ir20Re20Rh20Ru28 HEA yielded by the conventional solidification method reflects a significant development, as it is an Os-free alloy and the first single-phase hcp-HEA that includes an element from the 3d late transition metal.

High-pressure preparation of high-hardness CoCrFeNiMo0.4 high-entropy alloy

The CoCrFeNiMo0.4 high-entropy alloys (HEAs) were synthesized by a high-pressure solid-state reaction at 3–5 GPa and held for 3–10 min at 1200 °C. The microstructure and mechanical properties of the sample were influenced by the pressure and holding time, which was confirmed when the Co, Cr, Fe, Ni, and Mo atoms diffused to form HEAs. The increased pressure hindered the diffusion between atoms and thus inhibited the formation of HEAs. Under the influence of the enthalpy of mixing between elements, Fe had the strongest repulsive force on the system and the weakest diffusion effect, but increasing the holding time promoted the diffusion of Fe atoms. Compared with the microhardness reported in other studies, the maximum hardness in our work was 449.1 HV, which represents a maximum increase of approximately 80%. The synergistic effects of the solid-solution strengthening of the system and the serious lattice distortion effect caused by large Mo atoms and high pressure were the dominant mechanisms responsible for the enhanced microhardness of the sintered HEAs under extreme conditions.

Transition from High-Entropy to Conventional Alloys: Which Are Better?

The study of the transition from high-entropy alloys (HEAs) to conventional alloys (CAs) composed of the same alloying components is apparently important, both for understanding the formation of HEAs and for proper evaluation of their potential with respect to that of the corresponding CAs. However, this transition has thus far been studied in only two types of alloy systems: crystalline alloys of iron group metals (such as the Cantor alloy and its derivatives) and both amorphous (a-) and crystalline alloys, TE-TL, of early (TE = Ti, Zr, Nb, Hf) and late (TL = Co, Ni, Cu) transition metals. Here, we briefly overview the main results for the transition from HEAs to CAs in these alloy systems and then present new results for the electronic structure (ES), studied with photoemission spectroscopy and specific heat, atomic structure, thermal, magnetic and mechanical properties of a-TE-TL and Cantor-type alloys. A change in the properties of the alloys studied on crossing from the HEA to the CA concentration range mirrors that in the ES. The compositions of the alloys having the best properties depend on the alloy system and the property selected. This emphasizes the importance of knowing the ES for the design of new compositional complex alloys with the desired properties.

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.

Kinetically Limited Phase Formation of Pt-Ir Based Compositionally Complex Thin Films.

The phase formation of PtIrCuAuX (X = Ag, Pd) compositionally complex thin films is investigated to critically appraise the criteria employed to predict the formation of high entropy alloys. The formation of a single-phase high entropy alloy is predicted if the following requirements are fulfilled: 12 J∙K−1 mol−1 ≤ configurational entropy ≤ 17.5 J∙K−1 mol−1, −10 kJ∙mol−1 ≤ enthalpy of mixing ≤ 5 kJ∙mol−1 and atomic size difference ≤ 5%. Equiatomic PtIrCuAuX (X = Ag, Pd) fulfill all of these requirements. Based on X-ray diffraction and energy-dispersive X-ray spectroscopy data, near-equiatomic Pt22Ir23Cu18Au18Pd19 thin films form a single-phase solid solution while near-equiatomic Pt22Ir23Cu20Au17Ag18 thin films exhibit the formation of two phases. The latter observation is clearly in conflict with the design rules for high entropy alloys. However, the observed phase formation can be rationalized by considering bond strengths and differences in activation energy barriers for surface diffusion. Integrated crystal orbital Hamilton population values per bond imply a decrease in bond strength for all the interactions when Pd is substituted by Ag in PtIrCuAuX which lowers the surface diffusion activation energy barrier by 35% on average for each constituent. This enables the surface diffusion-mediated formation of two phases, one rich in Au and Ag and a second phase enriched in Pt and Cu. Hence, phase formation in these systems appears to be governed by the complex interplay between energetics and kinetic limitations rather than by configurational entropy.

Using machine learning and feature engineering to characterize limited material datasets of high-entropy alloys

The prediction of the phase formation of high entropy alloys (HEAs) has attracted great research interest recent years due to their superior structure and mechanical properties of single phase. However, the identification of these single phase solid solution alloys is still a challenge. Previous studies mainly focus on trial-and-error experiments or thermodynamic criteria, the previous is time consuming while the latter depends on the descriptors quality, both provide unreliable prediction. In this study, we attempted to predict the phase formation based on feature engineering and machine learning (ML) with a small dataset. The descriptor dimensionality is augmented from original small dimension to high dimension by non-linear combinations to characterize HEAs. The results showed that this method could achieve higher accuracy in predicting the phase formation of HEAs than traditional methods. Except the prediction of HEAs, this method also can be applied to other materials with limited dataset.

Transition from high-entropy to Cu-based (TiZrNbNi)1−xCux metallic glasses

A study of a transition from conventional multicomponent alloys to high-entropy alloys (HEAs) is important both for understanding the formation of HEAs and for proper evaluation of their potential with respect to that of conventional alloys. We report the main result of such a study performed on (TiZrNbNi)1−xCux metallic glasses (MG) over a broad concentration range x ≤ 0.52 encompassing both high-entropy-MGs and Cu-based MGs. A comprehensive study of the composition, homogeneity, thermal stability, atomic structure, electronic structure, and magnetic susceptibility of 11 alloys has been performed. Thermal analysis revealed a rather weak variation of thermal parameters and glass forming ability with x. The study of the atomic structure showed a linear variation of average interatomic distances and atomic volumes close to those predicted by Vegard's law. The coordination numbers and atomic packing fractions were constant throughout the explored concentration range. The electronic density of states (DOS) showed a split-band structure with DOS close to the Fermi level dominated with d-states of Ti, Zr, and Nb. Accordingly, magnetic susceptibility decreased linearly with x and extrapolated to that of Cu. Thus, the studied alloys show ideal solution behavior similar to that of binary Cu-Ti, Zr, and Hf MGs. The results are compared with those for (TiZrNbCu)1−xNix MGs and (CrMnFeCo)1−xNix alloys and their impact on understanding the transition from high-entropy-MGs to conventional MGs with the same composition is briefly discussed.

К вопросу о трении высокоэнтропийных сплавов и покрытий

In this paper, the authors propose a new approach to the consideration of the friction phenomenon in HEAs and, in particular, dry friction. An equation is obtained that shows the nonlinear dependence of the friction coefficient on Gibbs energy G0, on temperature T, on the concentration of the number of electrons N and which allows predicting the formation of high entropy alloys and coatings.

A New Method to Characterize Limited Material Datasets of High-Entropy Alloys Based on the Feature Engineering and Machine Learning

This paper proposed a new method for characterizing limited material data of high-entropy alloys (HEAs) based on the feature engineering and machine learning (ML). The descriptor dimensionality is augmented from original small dimension to a high dimension by non-linear combination based on feature engineering to characterize this kind material. To avoid overfitting, we carried out 5-fold cross-validation to evaluate the generalization performance of the model. The results showed that this method could achieve higher accuracy in predicting the phase formation of HEAs. Except the prediction of HEAs, this method also can be applied to other materials with limited data.

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.

Design of high-entropy alloys with a single solid-solution phase: Average properties vs. their variances

The empirical thermo-physical parameters for designing of high-entropy alloys (HEAs) with a single solid-solution phase (SSP) are based on the average properties of constituent elements, significant derivation from which might make them out of work. In the current work, both the important roles of average properties and their variances were studied. After an introduction of the variance of dimensionless enthalpy of mixing to characterize the chemical bond mismatch and a comparative study between two typical collections of HEAs to show the validity of previous designing rules, it was found that all the previous parameters to some extent fail to predict the formation of HEAs with a single SSP whereas the variance of dimensionless enthalpy of mixing is able to separate the regions of HEAs with a single SSP, with multi-phases and with an amorphous phase. Application to three typical HEA systems proved further that the lower value of the variance of dimensionless enthalpy of mixing corresponds to the higher possibility to form HEAs with a single SSP. The current work provides some necessary conditions for designing of HEAs, based on which preparation of potential HEAs with a single SSP could be accelerated.