Zhihua Dong

Dendrite spatial orientation dominates the geometry of liquid channels and interlocking states of dendritic skeletons, yet quantitative correlations between crystallographic orientation and mushy zone seepage performance remain insufficiently clarified. In this study, a phase-field lattice-Boltzmann method is applied to numerically simulate dendrite growth of Mg-6 wt. % Gd alloy under varying dendrite orientations. Three hierarchical simulation frameworks (single dendrite, dual interacting dendrites, and a multi-dendrite network) are constructed to decouple and quantify the independent and synergistic effects of dendrite orientation and solidification conditions (undercooling and flow intensity) on dendritic morphology, solid fraction, fractal dimension, and interdendritic permeability. Results demonstrate that the solid fraction acts as the primary controlling factor of permeability, while the dendrite orientation functions as a secondary critical regulator by modifying channel tortuosity and intergranular interlocking modes. For the dual-dendrite systems, identical orientation induces severe face-to-face dendrite interlocking and yields 15%–20% lower permeability than symmetric staggered orientation; a universal permeability minimum occurs at orientation angles of 25°–35° due to maximized channel tortuosity. In the multi-dendrite networks, uniformly aligned dendrites form dense narrow flow channels with the lowest permeability, while a dispersed orientation distribution optimizes inter-channel connectivity and improves overall seepage capacity. This study clarifies the regulatory role of dendrite orientation on the seepage capacity of the mushy zone and provides a microscopic explanation for the differences in liquid feeding capacity under different grain orientation conditions.

Casting defects exert severe impacts on the local property distribution of as-cast magnesium alloy automotive components fabricated via high-pressure die casting. This study focuses on high-pressure die-cast (HPDC) AM50 magnesium alloy, addressing the critical issue of large ductility fluctuations constrained by porosity defects. The effects of fast shot speed (3-6 m/s) and intensification pressure (0-28 MPa) on microstructural evolution, three-dimensional pore characteristics, and mechanical properties were systematically investigated. Micro-computed tomography (Micro-CT) was employed to reconstruct defects in three dimensions, revealing the underlying mechanisms by which process parameters suppress the formation of central defect bands. The results show that with increasing fast shot speed and intensification pressure, the number of pores decreases significantly, while the pore morphology transitions from irregular shrinkage networks to dispersed gas pores, accompanied by a notable reduction in the width of the central defect band. Combined with three-parameter Weibull statistical analysis, it is found that local porosity is the key factor governing ductility. Based on this, a linear predictive model was established, enabling the estimation of the mechanical performance of magnesium alloy castings prior to tensile testing. This work provides important theoretical support for optimizing HPDC processing parameters and quality evaluation of large and complex magnesium alloy castings.

This study focuses on high-pressure die-cast (HPDC) AM50 magnesium alloy, addressing the critical issue of large ductility fluctuations constrained by porosity defects. The effects of fast shot speed (3-6 m/s) and intensification pressure (0-28 MPa) on microstructural evolution, three-dimensional pore characteristics, and mechanical properties were systematically investigated. Micro-computed tomography (Micro-CT) was employed to reconstruct defects in three dimensions, revealing the underlying mechanisms by which process parameters suppress the formation of central defect bands. The results show that with increasing fast shot speed and intensification pressure, the number of pores decreases significantly, while the pore morphology transitions from irregular shrinkage networks to dispersed gas pores, accompanied by a notable reduction in the width of the central defect band. Combined with three-parameter Weibull statistical analysis, it is found that local porosity is the key factor governing ductility. Based on this, a linear predictive model was established, enabling the estimation of the mechanical performance of magnesium alloy castings prior to tensile testing. This work provides important theoretical support for optimizing HPDC processing parameters and quality evaluation of large and complex magnesium alloy castings.

An inverse design framework, RF-NSGA-II, is developed using machine learning (ML) methods and a multi-objective co-optimization strategy. It enables intelligent design of chemical compositions and processing parameters for thermo-mechanical treatments based on desired mechanical properties of Mg alloys. Using a database of extruded Mg-Gd and Mg-Y-based alloys, RF-NSGA-II integrates an optimized forward model with a non-dominated sorting genetic algorithm II (NSGA-II). The forward model is constructed by evaluating the performance of different ML algorithms, with the random forest (RF) algorithm experimentally validated to accurately describe the relationship between chemical composition and mechanical properties. RF-NSGA-II simultaneously optimizes multiple mechanical properties, and validation through experimental measurements demonstrates its effectiveness. Using target mechanical properties as inputs, chemical compositions and processing parameters for solid-solution treatment and extrusion are efficiently determined for a high-strength Mg-11.5Gd-6.0Y-1.0Zn-0.2Mn (wt.%) alloy and a high-ductility Mg-2.5Gd-1.0Zn (wt.%) alloy, achieving tensile strength/elongation values of 417 MPa/3.2% and 223 MPa/34%, respectively. These results provide a transparent and effective route for the inverse design of advanced Mg alloys based on desired mechanical properties.

The addition of AlN particles effectively refined the α-Mg grain size of Mg-4Al-2Nd-0.3Mn (AE42) alloy, as well as the size of acicular Al11Nd3 and blocky Al2Nd phases, while promoting the precipitation of the Al8Mn5 phase. The 2.0 wt.% AlN/AE42 composite exhibited optimal room- and high-temperature mechanical properties. At room temperature, the ultimate tensile strength (UTS), yield strength (YS), and fracture strain (ε) of AE42 alloy and 2.0 wt.% AlN/AE42 composite were 191 MPa, 86 MPa, 12.1% and 219 MPa, 107 MPa, and 13.8%, respectively. At 150 °C, 200 °C, and 250 °C, the UTS values of the 2.0 wt.% AlN/AE42 composite were 178 MPa, 152 MPa, and 139 MPa, respectively. At high temperatures, AlN particles synergistically enhanced the strength and plasticity of the composite by suppressing grain boundary sliding and promoting twinning.

Low thermal expansion alloys are typically developed by incorporating negative thermal expansion materials into metal matrices. However, the mismatches of lattice structure and opposite thermal expansion behavior between constituent phases frequently induce defects that interact with lattice vibrations, thereby complicating the expected thermal response. Here, we demonstrate that the mismatch induced defects can fundamentally overturn conventional predictions based on phase mixing rules. By incorporating LaFe9.8Co1.1Al2.1 particles into a magnesium matrix, we observe an anomalous thermal expansion behavior: low particle concentrations lead to an increase in the coefficient of thermal expansion, while higher concentrations result in a significant reduction in it. This inversion is driven by dislocation generation and immobilization at particle–matrix interfaces, as revealed by multiscale microstructural analyses. Our findings demonstrate that thermal volumetric behavior in composites can be actively tuned through defect engineering, providing a viable strategy for designing dimensionally stable structural materials under thermal loading.

In this study, the origin of spin-gapless semiconducting behavior in Ti2CoSi was theoretically revealed. It was discovered that Ti2CoSi is stable in Cu2MnAl-type structure at the ground state. However, the Hg2CuTi-type structure is thermodynamically preferred in Ti2CoSi at high temperatures, which is responsible for the experimentally observed spin-gapless semiconducting behavior. Comparative analysis of data revealed that the kinetic arrest of atomic diffusion, caused by the rapid-cooling method, led to the formation of a Ti2CoSi phase with a structure similar to the Hg2CuTi-type in thin film samples. This study proposed that the physical properties and applications of Heusler compounds in devices are closely dependent on their structure, which can be adjusted by carefully controlling the thermodynamic states and kinetic process during sample fabrication. The calculation results indicate that the style and strength of interatomic chemical bonds are the inherent factors that aid in determining the phase stability in solids. These results not only suggest that thermodynamic states and kinetic processes during the sample preparation determine the spin-gapless semiconductor characteristic in Ti2CoSi but also are helpful in designing and exploring magnetic functional materials for technological applications.