High-entropy alloys (HEAs) break through the design concepts of traditional alloys. Since they were first reported in 2004, their remarkable properties—such as high strength, excellent wear resistance, superior corrosion resistance, and good low-temperature toughness—have rapidly made them a research hotspot and frontier in materials science and condensed matter physics. They are widely regarded as one of the most promising "future materials."
Our research group focuses on the strengthening and toughening mechanisms as well as performance regulation of HEAs. We have established a deeply integrated multi-scale research system combining "experimental characterization, theoretical modeling, and simulation."
At the macro-scale, we systematically investigate the deformation, damage, and fracture behaviors of HEAs under different loading conditions through mechanical testing and in-situ observation. At the micro-scale, we utilize advanced electron microscopy and diffraction techniques to analyze their complex phase composition, dislocation structures, twinning behavior, and phase transformation processes.
In terms of simulation and theory, the group has developed
crystal plasticity finite element models tailored to the multi-principal-element and multi-phase characteristics of HEAs. These models quantitatively reveal the synergistic contributions of various strengthening mechanisms—such as solid solution strengthening, dislocation strengthening, and transformation-induced plasticity—during deformation. Concurrently,
molecular dynamics simulations are employed to explore atomic-scale elemental distribution, short-range order structures, and their effects on dislocation nucleation and motion. We have further advanced
discrete dislocation dynamics simulation methods to investigate, the hindering mechanisms and evolution of chemical short-range order, phase boundaries, and nano-precipitates on dislocation motion, thereby elucidating the unique work-hardening and damage behaviors of HEAs. In recent years, we have also actively explored the application of machine learning in HEA composition design, performance prediction, and constitutive parameter inversion to accelerate the development of new materials.
The core scientific goal of this research direction is to establish physically-based constitutive models that accurately describe the complex deformation mechanisms of HEAs through multi-scale correlation analysis. This will enable the quantification of the contribution of each strengthening mechanism to the mechanical response, thereby providing theoretical guidance and design principles for developing novel HEAs with tailored properties—such as ultra-high strength and toughness, irradiation resistance, and high-temperature resistance. Relevant research holds significant value for promoting the application of HEAs in fields such as aerospace, energy equipment, and components for extreme environments.
