High-entropy alloys (HEAs) represent a distinctive class of multicomponent materials with promising properties, yet the mechanisms linking solidification to microstructural evolution and performance remain incompletely understood. This review establishes a mechanistic framework connecting thermal gradient, growth rate and cooling rate with phase selection, grain morphology, dendritic evolution, elemental segregation and defect formation. It highlights that the four core effects of HEAs, particularly lattice distortion and sluggish diffusion, are composition- and process-dependent phenomena influenced by non-equilibrium solidification, multicomponent diffusion and chemical short-range order (CSRO). A comparative assessment of FCC-based HEAs, refractory HEAs and eutectic HEAs reveals distinct thermodynamic and kinetic pathways that govern phase stability, microstructural heterogeneity and defect susceptibility. The effects of conventional casting, directional and assisted solidification, and additive manufacturing are examined in relation to microstructural refinement, phase selection and defect control. The review further evaluates the complementary capabilities and limitations of CALPHAD, phase-field modelling and molecular dynamics in predicting solidification behaviour, emphasizing database uncertainty, computational demands and restricted simulation scales. Despite advances in processing and modelling, accurately predicting the coupled effects of segregation, CSRO, lattice distortion and multicomponent transport remains challenging. An integrated process–structure–property framework is therefore proposed to guide mechanism-driven alloy design, microstructure control and the development of HEAs with tailored mechanical and functional performance.
High-entropy materials (HEMs), encompassing alloys, ceramics, and compounds with extreme compositional complexity, have opened unprecedented opportunities for property tailoring through entropy engineering. However, the vast compositional space and strong local chemical and structural heterogeneities render traditional experimental trial-and-error approaches inefficient. Consequently, computational methods have become indispensable for understanding and predicting structure–property correlations in HEMs. This review presents a comprehensive and pedagogical overview of computational approaches employed for HEM design, organised within a hierarchical framework spanning empirical, phenomenological, and mechanistic models. Empirical descriptors and database-driven machine learning techniques are discussed as rapid screening tools, while phenomenological approaches, including CALPHAD, semi-empirical thermodynamic models, strengthening theories, and generative artificial intelligence, are reviewed for their balance between physical insight and computational efficiency. Mechanistic models based on first-principles calculations, atomistic simulations, machine-learned interatomic potentials, and continuum approaches are critically examined for their ability to capture local chemical environments, defects, and microstructural evolution. Emphasis is placed on the role of chemical short-range order, disorder, and multiscale coupling in governing emergent properties. Finally, key challenges and future directions for inverse design, data-efficient modelling, and integrated multiscale frameworks are outlined, highlighting pathways to accelerate the rational discovery and optimisation of high-entropy materials.
Sustainable development of our society demands recycling of metallic scraps and wastes which in general contain a wide variety of metallic impurities. Therefore, it is desirable to try to develop a ‘universal’ material structure, such as a multicomponent amorphous alloy tolerating high concentrations of multiple-component metallic pollutants. We here report the results of ab initio molecular dynamics (AIMD) simulations for manufacturing a novel multicomponent high entropy amorphous alloy of twenty elements (20e-HEAA). Analysis reveals both topological and chemical compositional short-range ordering in the obtained 20e-HEAA and formation of pair clusters for light elements. Electronic structure calculations reveal the metallic nature of the amorphous alloy with its Fermi level falling in a valley in the electron density of states. Moreover, the (semi)core-like Zn 3d and Cd 4d electrons exhibit a localized nature and thus, should be excluded from the valence electron concentration (VEC) analysis in the study of multicomponent high-entropy alloys. The information obtained here is helpful to get insight into multicomponent high entropy materials, especially multicomponent high-entropy amorphous alloys as potential circular metals.
In this study, the tensile deformation behavior of nano-scaled single crystal and polycrystalline (5, 10, and 15-grains) CoCrFeMnNi high entropy alloys is investigated using molecular dynamics simulations. All models are subjected to uniaxial tension along the x-direction at two different temperatures, 300 K and 1200 K, to examine the influence of temperature on mechanical properties, phase transformations, and dislocation evolution. The results show that increasing temperature significantly reduces the yield strength and ultimate tensile strength. Moreover, the deformation process involves distinct phase transitions and notable variations in dislocation types and densities, which depend strongly on both temperature and grain structure.
Refractory multi-principal element alloys (RMPEAs) combine a chemically disordered lattice with a structurally ordered, single‐phase body‐centered cubic (bcc) crystal structure. Chemical fluctuations in these alloys give rise to significant energy barriers that impede dislocation motion. In this study, we use phase field dislocation dynamics to examine how spatial temperature fluctuations compete with randomness in energy barriers to affect the motion of long screw dislocations in three equi-atomic MoNbTa‐based RMPEAs: MoNbTa, MoNbTaW, and MoNbTaVW. Over a wide range of homologous temperatures (Th ≈ 0–0.6), we determined a screw dislocation ‘flow stress’ as the minimum applied stress to sustain continuous motion over a long excursion distance within a fixed timeframe. All three RMPEAs exhibit temperature dependent flow stress with three characteristic glide regimes: at low homologous temperatures, flow stress drops sharply, and screw glide remains planar and rectilinear; at intermediate homologous temperatures, the flow stress levels off as glide becomes planar but wavy; and at high homologous temperatures, flow stress plateaus as screws exhibit nonplanar, three‐dimensional motion. Glide kinetics and transition temperatures are controlled by the chemically induced fluctuations in the energy landscape. The rectilinear to wavy transition temperature is controlled by statistically weakest local barriers in the glide plane, whereas the wavy to 3D transition temperature is governed by statistically strongest local barriers. At low and intermediate homologous temperatures, the relative spread in energy barriers governs glide behavior by controlling the local kinetics of kink pair formation and kink pinning. At high homologous temperatures, the average barrier height governs the glide behavior by controlling the number of out-of-plane excursions during 3D glide. These findings reveal how random chemical fluctuations determine screw‐driven plasticity in RMPEAs, providing critical insight for the design of high temperature structural alloys.
