Properties Of High-entropy Alloys Research Articles

Synergistic Enhancement of Electromagnetic Wave Absorption and Corrosion Resistance Properties of High Entropy Alloy Through Lattice Distortion Engineering

AbstractHigh entropy alloys (HEAs) are promising electromagnetic wave absorption (EMA) materials due to its designable crystal structure, variable electromagnetic properties, and excellent corrosion resistance. However, the impedance mismatch owing to the high electric and dielectric conductivity severely hinders the application of HEAs in the field of EMA. Herein, the lattice distortion of FeCoNiCu HEA is manipulated accurately by doping and annealing strategies to tailor the EMA properties. Significant lattice distortion is observed in the FeCoNiCuC0.37, which leads to a decrease in the electrical conductivity and the creation of abundant dipoles. Owing to the optimal impedance matching and boosted polarization loss, the FeCoNiCuC0.37 delivers a minimal reflection loss of −65.4 dB accompanied by an effective absorption bandwidth (EAB) of 6.81 GHz. After annealing at 200 °C, the EAB of the FeCoNiCuC0.37 is further increased to 7.99 GHz at 1.95 mm, which is better than that of most HEA‐based EMA absorbers reported so far. Moreover, it demonstrates excellent corrosion resistance owing to the more tortuous diffusion path of corrosive medium origin from lattice distortion. Thus, the study provides a new insight into designing high performance HEA‐based EMA materials with superior anti‐corrosion property by lattice distortion engineering.

Fabrication of (TiZrNbSiMo)1-xNx high entropy alloy coatings using a high power impulse magnetron sputtering technique: Effects of nitrogen addition

Due to the outstanding mechanical and physical properties of high entropy alloy (HEA) coatings, the global academic and industrial communities have made significant research efforts in recent years, aiming to expand their industrial applications. In this study, TiZrNbSiMo and (TiZrNbSiMo)1-xNx HEA nitride coatings with different nitrogen contents were fabricated using a high power impulse magnetron sputtering (HiPIMS) system. By varying the nitrogen flow rates, the nitrogen contents of coatings increased from 0 to 48.8 at. %. The deposition rate decreased with increasing nitrogen content due to the target poisoning effect. Very fine and dense microstructure can be seen for each coating. The amorphous structure was obtained as the nitrogen content was lower than 19.1 at.%, whereas a nanocrystalline FCC structure was formed when the nitrogen content reached 34.9 at. %. Furthermore, the corrosion resistance of TiZrNbSiMo and four TiZrNbSiMoN HEA coatings in 0.5 M H2SO4 aqueous solution were superior to uncoated 304 stainless steel. We can conclude that the nanocrystalline TiZrNbSiMoN HEA coatings with a nitrogen content of 34.9 at. % exhibited a high hardness of 15.6 GPa, an electrical resistivity of 766.5 μΩ·cm, and an excellent corrosion polarization resistance of 9.71 × 105 Ω·cm2, 610.7 times higher than 304SS. This study provides valuable insights for future promising applications of (TiZrNbSiMo)1-xNx HEA nitride coatings in severely corrosive environments, such as the protective coatings on stainless steel bipolar plates in proton exchange membrane fuel cells.

Discontinuous coarsening leads to unchanged tensile properties in high-entropy alloys with different recrystallization volume fractions

Heterogeneous microstructure alloys provide a possibility for the combination of strength and ductility. As a typical heterogeneous microstructure, partially recrystallized microstructure is attractive because of the convenient processing route and great potential for industrial applications. However, the mechanical properties of this microstructure vary dramatically with different morphology factors, especially the recrystallization fraction, which restricts the processing window and the property consistency. In this study, we found that the yield strength (∼1.3 GPa) and ductility (∼20 %) of the partially recrystallized Ni2CoCrFeTi0.24Al0.2 do not change when the recrystallization fraction increases from 21 % to 72 %. This novel phenomenon is attributed to an additional hetero-deformation induced (HDI) strain hardening effect produced by heterogeneous precipitates. With the increased recrystallization fraction, this additional HDI stress keeps the ductility unchanged by offsetting the decreased HDI stress arising from the hetero-deformation between recrystallized (RX) and non-recrystallized (NRX) areas. The unchanged yield strength comes from the increased strengthening effects of the lamellar precipitates and grain boundaries. We also confirmed that the discontinuous coarsening contributes to the formation of heterogeneous precipitates. These findings would open a new pathway for enhancing the consistency and processability of hetero-structured alloys and thus promote their broader industrial applications.

Machine Learning-Based Predictions of Porosity during Cold Spray Deposition of High Entropy Alloy Coatings

Porosity poses a challenge to the mechanical properties of cold sprayed coatings, especially when it is open or surface-connected, limiting the coatings’ capabilities to act as a barrier. The porosity formation is dependent on the feedstock powder characteristics and the cold spray process parameters. We present a machine learning-based approach to predict porosity based on the above-mentioned factors. Nine different machine learning models based on linear regression (LR), decision trees, random forests, gradient boosting, support vector machine (SVM), and neural networks were explored. Considering the excellent properties of high entropy alloys, Cantor alloy was taken as the consumable. Our dataset, derived from the literature and experiments, identified SVM with a linear kernel and LR as the top-performing models based on the Pearson correlation coefficient (PCC) and root mean square error, where the PCC values exceeded 0.8. The SHapley Additive exPlanations method helped in identifying that the type of gas and powder are the top two factors in pore formation.

Effect of Ferro-Alloys on the Properties of High Entropy Alloy with FeCoNiMnMoV Composition Produced by Arc-Melting Method

In this study, high entropy FeCoNiMnMoV and FeCoNiMn (Ferro Mo-Ferro-V) alloys were produced by arc melting method. After the arc melting process, the samples were annealed at 1000ᵒC under argon atmosphere for 15 hours physical and thermodynamic calculations were performed to determine the properties of the alloy. In the study, both alloys were characterized. For characterization, XRD, SEM, EDS and Micro hardness were taken from the samples. The aim of my study is to examine the effect of using low-priced starting materials on the microstructure of HEA. For this purpose, ferro-alloys were added to the alloy. As a result, similar properties were obtained for the microstructure of both alloys. However, it has been determined that the hardness of samples containing ferro-alloys decreases more due to their chemical composition, especially after heat treatment.

Optimization of structure and properties of WC-reinforced FeCoNiCr high-entropy alloy composite coating by laser melting

High entropy alloys have the potential to be used as coating materials in many fields due to their excellent mechanical properties, corrosion resistance and high-temperature stability. Based on the application requirements of high-entropy alloys, this study aims to explore how tungsten carbide can optimize the properties of high-entropy alloys. Through theoretical research and experimental validation, the effects of the organizational structure of high-entropy alloy coatings on their properties and the effects of tungsten carbide content on the properties of high-entropy alloy coatings were investigated. The micro hardness of the coatings is relatively high at low power laser melting, while it decreases with the increase of laser power. After laser melting of different materials, the average impact toughness of the studied materials exceeded 70 J/cm2, and the average values of microhardness of the optimized coatings prepared at laser powers of 1400 W and 1600 W were more than 160 HV0.2. In addition, the properties of the high-entropy alloys were significantly improved when the content of tungsten carbide reached a certain percentage. The composite coatings have excellent wear resistance, corrosion resistance and thermal stability. Overall, the optimized tungsten carbide on high entropy alloys in this study has good performance, which is of great theoretical and practical significance for understanding the performance regulation and optimal design of high entropy alloy coatings.

Microstructures and Properties of FeCoNiCr High-Entropy Alloy Coatings Prepared by Electrodeposition

High-entropy alloys (HEAs) have attracted increasing attention owing to their multicomponent characteristics with notable high-entropy effects. However, obtaining HEAs with improved properties is still challenging. The properties of HEAs can be modulated by the fabrication technique. Electrodeposition could achieve the desired performance characteristics of HEA coatings while operating at reduced processing temperatures and energy consumption levels. Herein, novel FeCoNiCr HEA coatings were electrodeposited on copper substrates under various current densities. The microstructure, coating thickness, hardness, wear resistance, and corrosion properties of the FeCoNiCr HEA coatings prepared at different current densities were all examined. X-ray diffraction revealed HEA coatings with a single disordered face-centered cubic solid solution phase. Scanning electron microscopy indicated uniform and dense surfaces of FeCoNiCr HEA coatings fabricated under a current density of 25 A/dm2, with significantly reduced coating cracking and improved structural integrity. The coatings prepared at 25 A/dm2 also exhibited maximum thickness and favorable bonding with the substrate, as well as notably enhanced wear resistance. As the preparation current density increases, the hardness of the coating increases. The hardness of the coating reaches its maximum at 30 A/dm2. FeCoNiCr HEA coatings fabricated under a current density of 25 A/dm2 in a 3.5 wt% NaCl solution simulated seawater conditions demonstrated improved electrochemical resistance to corrosion. By comparing the microstructure, elemental content, and properties of coatings prepared at various current densities, it was found that the FeCoNiCr HEA coating prepared at 25 A/dm2 showed the best performance.

Atomic Radius Mismatch: A Key Parameter for Design and Synthesis of High‐Entropy Physical Vapor Deposition Coatings—Review

High‐entropy metal sublattice coatings (HESCs) prepared by physical vapor deposition (PVD) have received attention due to their diverse range of properties and applications. One of the most critical requirements for their synthesis is the prediction and control of their widespread properties, and several efforts have been undertaken using various thermodynamical parameters. The majority of these predictions concentrate on high‐entropy alloys (HEAs) while high‐entropy ceramics receive little attention. One of the most important parameters to control the structure and properties of HEAs is their atomic radius mismatch (δr), which is applied to crystalline, amorphous, and composite (amorphous matrix, crystalline matrix, and multilayer) HESCs. Based on the relationships between δr and structure, mixing enthalpy (ΔHmix), electronegativity difference (Δχ), ion bonding percentage (IBPHE), mechanical properties (including hardness, H, and Young's modulus, E), and wear performance descriptors (H/E and H3/E2 ratios), a δr‐based map to aid the design and selection of elements for HESCs is provided.

Synergistic Effects of PtRhNiFeCu High Entropy Alloy Nanocatalyst for Hydrogen Evolution and Oxygen Reduction Reactions.

The unique properties of high entropy alloy (HEA) catalysts, particularly their severe lattice distortion and the synergistic effect of multiple components, endow them with exceptional multifunctional catalytic performance. Herein, it is revealed for the first time, that the ultrasmall PtRhNiFeCu HEA nanoparticles catalyst shows outstanding catalytic activity for both hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). The catalyst exhibits an impressively low overpotential of 13mV at 10mAcm-2 , a Tafel slope of 29.6mVdec-1, and high mass activity of 7.6AmgPt -1 at -50mV in alkaline media, and long-term stability of at least 20h. Moreover, the catalyst also demonstrates effective catalytic activity for acidic ORR with a commendable performance of 1.23AmgPt -1 , much exceeding the commercial Pt/C catalyst. Density functional theory (DFT) calculations unveil that the efficient electrocatalytic performance for HER and ORR can be primarily attributed to the synergistic effect between components tailors and optimizes the electronic structure of PtRhNiFeCu/C HEA, which not only enhances the HER activity through increasing water capture capability, decreasing energetic barrier for water dissociation, and optimizing hydrogen absorption but also initiates non-platinum active sites with high ORR activity, achieving the improved ORR performance.

Phase stability and microstructural properties of high entropy alloy reinforced aluminium matrix composites consolidated via spark plasma sintering

Spark plasma sintering (SPS) technique was employed in the consolidation of Cr20Mn20Ni20Cu20Nb10Co10 high entropy alloy (HEA) reinforced aluminium matrix composites. Phase stability and prediction expressions were used in the determination of the powder combination for the HEA. The microstructural analysis showed that an interdiffusion layer was formed between the aluminium matrix and the HEA particles in the sintered composites. Further investigation of the composites by X-ray diffraction (XRD) showed that in addition to the Al matrix phase present, other new phases (BCC, FCC and other intermetallics) were formed as a result of the reaction between the Al matrix and the atoms precipitated from the added HEA during sintering. The density of the HEA-reinforced Al matrix composites decreases with an increase in the wt.% of HEA from 98.6 % for pure aluminium to 98.1 % for the reinforced alloy with 10 % HEA, while the microhardness increases with an increase in the wt.% of the HEA from 35 HV for pure aluminium to 96.0 HV for the alloy reinforced with 10 % HEA.

Controllable synthesis of high-entropy alloys.

High-entropy alloys (HEAs) involving more than four elements, as emerging alloys, have brought about a paradigm shift in material design. The unprecedented compositional diversities and structural complexities of HEAs endow multidimensional exploration space and great potential for practical benefits, as well as a formidable challenge for synthesis. To further optimize performance and promote advanced applications, it is essential to synthesize HEAs with desired characteristics to satisfy the requirements in the application scenarios. The properties of HEAs are highly related to their chemical compositions, microstructure, and morphology. In this review, a comprehensive overview of the controllable synthesis of HEAs is provided, ranging from composition design to morphology control, structure construction, and surface/interface engineering. The fundamental parameters and advanced characterization related to HEAs are introduced. We also propose several critical directions for future development. This review can provide insight and an in-depth understanding of HEAs, accelerating the synthesis of the desired HEAs.

Enhanced wear resistance of AlCoCrFeMo high entropy coatings (HECs) through various thermal spray techniques

The remarkable mechanical and wear properties of high entropy alloys (HEAs) have opened up exciting possibilities for their use in aerospace applications. This study explores the potential of AlCoCrFeMo high entropy coatings (HECs) fabricated using three thermal spray techniques, namely low-pressure cold spray (LPCS), flame spray (FS), and high-velocity oxy fuel spray (HVOF) as wear resistant surfaces. The coatings were investigated in terms of their microstructures, phases, mechanical properties, and sliding wear characteristics from room temperature up to 350 °C. Ex-situ characterization was performed using XRD for phase analysis and SEM-EDS for cross-sectional microscopy and phase compositions of the coatings. All three coatings exhibited a typical lamellar structure with the formation of BCC solid solution phase and variations in porosity and oxide content. The HVOF sprayed coatings showed higher hardness values compared to the FS and LPCS coatings, which can be attributed to their fine splats microstructure, lower porosity, and oxide inclusions compared to the other two coatings. In terms of tribological performance, the LPCS coatings exhibited overall lower frictional coefficient than the FS and HVOF coatings at both tested temperatures. However, the HVOF coatings exhibited relatively lower wear rates, correlating well with observations from ex-situ analysis, highlighting lower material transfer and decreased formation of debris particles compared to LPCS and FS coatings. These findings suggest that the HEA materials have great potential as next-generation tribological interfaces under high-temperature wear conditions, emphasizing the importance of designing materials with improved microstructural features.

Research progress of high entropy alloy: Surface treatment improves friction and wear properties

High entropy alloy (HEA) has high hardness, strength and excellent friction and wear properties, which also has broad application prospects in wear-resistant and high temperature coating, aerospace and military fields. However, one third of the world's total energy is consumed by various forms of friction or wear and tear, causing untold economic losses each year. The important way to reduce the wear is to increase the hardness of materials. The surface modification of high entropy alloy is an effective way to improve the friction and wear properties. In this paper, the research progress of high entropy alloys at home and abroad in recent years is reviewed, especially the surface treatment technology which can improve the friction and wear properties of high entropy alloys is introduced, and the influence of surface strengthening treatment on the friction and wear properties and mechanism of high entropy alloys is discussed. Surface treatment mainly includes surface mechanical strengthening, surface heat treatment strengthening, chemical heat treatment strengthening, surface laser cladding treatment, surface plasma treatment, surface electron beam treatment, vapor deposition technology. The purpose of this work is to provide a reference for the research on the friction and wear property of high entropy alloy, to provide corresponding ideas for the possible industrial demand in the future, and to provide the key research direction for future application.

Mechanical Properties of High Entropy Alloys Based on Rare Earth Elements with Yttrium and Scandium

Mechanical Properties of High Entropy Alloys Based on Rare Earth Elements with Yttrium and Scandium

Mechanical Properties of High Entropy Alloys Based on Rare Earth Elements with Yttrium and Scandium

Abstract—The high-entropy alloys GdTbDyHoSc and GdTbDyHoY having equiatomic composition are considered as promising materials for magnetic cold generators. The results of the alloys structure and chemical composition investigation are presented in this paper. The solidus and liquidus temperatures of the alloys under investigation were determined by the method of differential scanning calorimetry. Based on these data, an experimental mode of thermocyclic treatment was selected. There were no signs of alloys destruction after five cycles testing for heat resistance in the following regime: 15 min exposition at 1073 K (~0.6 of the melting temperature) and subsequent quenching in room temperature water. It was found that the applied heat treatment led to an increase in the hardness of the alloys by 2–3 times and a decrease in wear resistance by 4–40 times, depending on the composition of the alloys and the number of heat treatment cycles. A significant change in the properties of alloys is associated with the formation of oxides of the REM2O3 type not only on the surface of the alloys, but also in their volume, which is due to the high chemical activity of rare earth metals (REM). The presented data will be useful for the development of modes of thermal and thermomechanical processing of various alloys.

Superior strength-ductility balance of an extremely low stacking fault energy (SFE) high-entropy alloy (HEA) processed by novel hybrid-rolling

An extremely low SFE Co20Cr26Fe20Mn20Ni14 FCC HEA was processed by warm-rolling (WR) and a novel hybrid-rolling (HR) (cryo-rolling followed by warm-rolling). The HR material showed finer nanostructure and a larger fraction of Cr-rich precipitates due to the finer microstructure and greater driving force resulting from the prior cryo-rolling step. Annealing resulted in finer recrystallized FCC grain size (GS) and a significantly higher fraction of in-grain precipitate in the HR material. The finer GS and higher in-grain precipitate fraction in the annealed HR material resulted in remarkably high strength (∼1125 MPa) and elongation (∼20%). The results highlighted the significant potential of this novel processing route for tailoring microstructure and properties of HEAs.

High-throughput machine learning - Kinetic Monte Carlo framework for diffusion studies in Equiatomic and Non-equiatomic FeNiCrCoCu high-entropy alloys

Sluggish diffusion is postulated as an underlying mechanism for many unique properties in high-entropy alloys (HEAs). However, its existence remains a subject of debate. Due to the challenges of exploring the vast composition space, to date most experimental and computational diffusion studies have been limited to equiatomic HEA compositions. To develop a high-throughput approach to study sluggish diffusion in a wide range of non-equiatomic compositions, this work presents an innovative artificial neural network (ANN) based machine learning model that can predict the vacancy migration barriers for arbitrary local atomic configurations in a model FeNiCrCoCu HEA system. Remarkably, the model utilizes the training data exclusively from the equiatomic HEA while it can accurately predict barriers in non-equiatomic HEAs as well as in the quaternary, ternary, and binary sub-systems. The ANN model is implemented as an on-the-fly barrier calculator for kinetic Monte Carlo (KMC) simulations, achieving diffusivities nearly identical to the independent molecular dynamics (MD) simulations but with far higher efficiency. The high-throughput ANN-KMC method is then used to study the diffusion behavior in 1,500 non-equiatomic HEA compositions. It is found that although the sluggish diffusion is not evident in the equiatomic HEA, it does exist in many non-equiatomic compositions. The compositions, complex potential energy landscapes (PEL), and percolation effect of the fastest diffuser (Cu) in these sluggish compositions are analyzed, which could provide valuable insights for the experimental HEA designs.

Investigation on the evolution mechanism of dislocation in nano-cutting of FeCoNiCrAlx high entropy alloy

The element content has a very important influence on the overall properties of high-entropy alloys, which leads to different nano-cutting mechanisms. In order to explore the influence of Cr and Al contents on dislocation evolution mechanism in nano-cutting of FeCoNiCrAlx high-entropy alloy, nano-cutting of FeCoNiCrAlx high entropy alloy with different Cr and Al contents was simulated at 100 K by molecular dynamics simulation method, and It focuses on the comparison of Von mises, Shear strain, cutting force, cutting temperature, dislocation and phase transformation with different element contents. The results show that, at the same cutting speed, the chip thickness with Fe20Co20Ni20Cr24Al16 is less than that of Fe20Co20Ni20Cr30Al10, and the shear strain with Al content of 16% is higher than that with Al content of 10% at the same cutting depth. There is no uniform rule that the cutting force in [100], [010] and [001] directions is influenced by cutting speed and depth under different element contents，At different cutting speeds, the minimum cutting forces in the [100] direction of Fe20Co20Ni20Cr24Al16 and Fe20Co20Ni20Cr30Al10 are 92 Nn and 83 Nn, respectively, and the minimum cutting forces in the [001] direction of Fe20Co20Ni20Cr24Al16 and Fe20Co20Ni20Cr30Al10 are 82 Nn and 74 Nn, respectively. With the increase of cutting speed and cutting depth, the cutting temperature increases obviously, and the maximum increase amplitude of cutting temperature at different cutting depths is about 1.25 times that at different cutting speeds. The dislocation density of 1/6 < 112 > (Shockley) is the largest and the number of atoms in FCC structure is the largest under any cutting parameters. At different cutting speeds, the maximum dislocation density of 1/2 < 110 > (Perfect) of Fe20Co20Ni20Cr30Al10 is about 1.9 times that of Fe20Co20Ni20Cr24Al16, and the maximum dislocation density of 1/6 < 112 > of Fe20Co20Ni20Cr30Al10 is about 1.45 times that of Fe20Co20Ni20Cr24Al16.

Tailoring the microstructure and mechanical properties of (CrMnFeCoNi)100-xCx high-entropy alloys: Machine learning, experimental validation, and mathematical modeling

As a common thermomechanical treatment route, “cold rolling and annealing” is widely used for the processing and grain refinement of interstitial-containing high-entropy alloys (HEAs). The interrelationship between the parameters of this process, the content of interstitial elements, and their interactions are outstanding challenges and areas of open discussion. Accordingly, the data-driven machine learning approach is a favorable choice for tuning the microstructure and mechanical properties, which needs to be systematically investigated. In the present work, these subjects were addressed in terms of correlating the thermomechanical processing parameters and chemical composition with the recrystallization and grain growth behaviors, grain size, carbide precipitation, and the resulting tensile yield stress for the model (CrMnFeCoNi)100-xCx HEAs. For this purpose, machine learning models based on adaptive neuro-fuzzy inference system (ANFIS), backpropagation artificial neural network (BP-ANN), and support network machine (SVM), as well as mathematical relationships and equations for the contribution of each strengthening mechanism were proposed and verified by extensive experimental work, which shed light on the design and prediction of the microstructure and properties of HEAs.

Machine learning prediction of hardness in solid solution high entropy alloys

The mechanical properties of high entropy alloys (HEAs) are enhanced by solid solution strengthening (SSS) mechanism, which is of great importance for the design of HEAs. The compositional design space of HEAs is extensive, enabling the attainment of varying levels of hardness by combining different SSS elements and phases. Consequently, the selection of appropriate alloy compositions and their proportions to achieve the desired hardness has emerged as a present research challenge in the field. Against this backdrop, achieving accurate predictions of the hardness of HEAs has become a focal point of scholarly investigations. Machine learning (ML) adeptly captures the nonlinear relationships between alloy hardness and various characteristic features, and is widely regarded as a pivotal approach in the realm of hardness prediction for contemporary HEAs. A complete ML-based workflow for hardness prediction of HEAs is presented in this paper. Five ML models were trained using the selected feature descriptors. Eventually, a Random Forest model was obtained, which demonstrated a predictive correlation coefficient of 0.91 on the independent test dataset. Furthermore, the Shapley Additive exPlanations (SHAP) theory is employed to elucidate the influence of empirical parameters on the hardness of HEAs.