Acta Metallurgica Sinica-English Letters最新文献

Composition design is one of the significant methods to break the trade-off relation between strength and ductility of medium-/high-entropy alloys (M/HEAs). Herein, we introduced three fundamental principles for the composition design: high elastic modulus, low stacking-fault energy (SFE), and appropriate phase stability. Subsequently, based on the three principles of component design and the first-principles calculation results, we designed and investigated a non-equiatomic Ni28 MEA with a single-phase and uniform microstructure. The Ni28 MEA has great mechanical properties with yield strength of 329.5 MPa, tensile strength of 829.4 MPa, and uniform elongation of 56.9% at ambient temperature, respectively. The high ductility of Ni28 MEA may be attributed to the dynamically refined microstructure composed of hexagonal close-packed (HCP) lamellas and stacking faults (SFs), which provide extremely high work-hardening ability. This work demonstrates the feasibility of the three principles for composition design and can be extended to more M/HEAs in the future.

Micro-arc oxidation (MAO) film can only provide common mechanical protection for magnesium (Mg)–lithium (Li) alloys. These alloys are susceptible to severe localized corrosion, if the MAO film is disrupted. This work reports the successful hydrothermal preparation of a MgLiAlCe-LDHs@GO film on a MAO-coated Mg–Li alloy following Ce confinement. The graphene oxide (GO) sheet increased the diffusion path of the corrosive media, and the addition of rare-earth cerium ions (Ce³⁺) endowed the film with a certain self-healing ability, which significantly improved the corrosion resistance of the film, and the corrosion current density (i_corr) reached 3.27 × 10⁻⁸ A cm⁻². The synergistic action of GO and Ce³⁺ can achieve long-term corrosion protection for the substrate. The corrosion resistance mechanism of MgLiAlCe-LDHs@GO film was discussed by the scanning vibration electrode technique (SVET).

Developing cost-effective and high-performance magnesium alloys is a key focus in lightweight materials applications. In this work, a Mg extrusion alloy with a remarkable cost-performance advantage was prepared by microalloying with cost-effective zirconium and adjusting the deformation temperature. Investigations revealed that both the degree of dynamic recrystallization (DRX) and the average grain size increased with increasing extrusion temperature, developing a more homogeneous microstructure. Although all samples exhibited a typical basal texture, a progressive spreading of crystallographic orientations along the < 10–10 > – < 11–20 > arc became increasingly pronounced with elevated extrusion temperatures. At a low extrusion temperature of 200 °C, the heterogeneous microstructure and strong basal texture favored texture and grain boundary strengthening, resulting in the largest yield strength of ~ 244 MPa. However, the potential difference between coarse and fine grains aggravated localized corrosion with a higher corrosion rate of ~ 14.56 mm/y. Conversely, at a high extrusion temperature of 320 °C, the coarse grains and weak basal texture enhanced dislocation storage and the activation of multiple slip systems during axial tension, providing better strain hardening ability and the largest ductility of ~ 13.6%. Nevertheless, grain coarsening and texture weakening were detrimental to mechanical strength (~ 162 MPa). Interestingly, extrusion at 250 °C developed a good combination of grain size, microstructure homogeneity, and texture intensity, achieving synergistic enhancement in grain boundary strengthening, dislocation storage, and uniform corrosion. Thus, a balanced yield strength of ~ 185 MPa, ductility of ~ 12.9%, and corrosion rate of ~ 4.31 mm/y were obtained in this sample.

Selective laser melting, a predominant additive manufacturing technology for fabricating geometrically complex components, faces significant challenges when processing high-performance Ni-based superalloys containing elevated Al and Ti concentrations (typically > 6 wt%), particularly regarding micro-cracking susceptibility. In this study, we demonstrate the successful fabrication of a novel crack-free Ni-based superalloy with 6.4 wt% (Al + Ti) content via optimized energy density, systematically investigating its microstructure, defects, and mechanical properties. Process parameter analysis revealed that insufficient energy densities led to unmolten pores, while excessively high energy densities caused keyhole formation. With an optimal energy density of 51.1 J/mm³, the crack-free superalloy exhibited exceptional mechanical properties: room temperature tensile strength of 1130 MPa with 36% elongation and elevated-temperature strength reaching 1198 MPa at 750 °C. This strength enhancement correlates with the precipitation of nanoscale γ′ phases (mean size: 31.56 nm) during high temperature. Furthermore, the mechanism of crack suppression is explained from multiple aspects, including energy density, grain structure, grain boundary characteristics, and the distribution of secondary phases. The absence of low-melting-point eutectic phases and brittle phases during the printing process is also explained from the perspective of alloy composition. These findings provide a comprehensive framework for alloy design and process optimization in additive manufacturing of defect-resistant Ni-based superalloys.

Only a few studies have reported the effects of electrochemical hydrogenation on the tensile mechanical properties of additively manufactured Ti–6Al–4V alloy, in all of them the alloy was processed by laser powder-bed fusion. Furthermore, the effects of either hot isostatic pressing (HIP) or heat treatment (HT) post-treatments on the mechanical properties were not reported. Here, the Young’s modulus, ultimate tensile stress, and uniform (homogeneous) strain of as-built electron beam melted (EBM) Ti–6Al–4V alloys were studied using small tensile specimens before and after electrochemical hydrogenation, as well as before and after secondary processes of HIP at 920 °C and HT at 1000 °C. The tensile properties of all hydrogenated alloys were significantly degraded compared to their non-hydrogenated counterparts. The yield stress could not be determined for all hydrogenated alloys, as failure occurred at a strain below 0.2% offset. The uniform strain of the hydrogenated alloys was less than 1%, compared to 1%–5% for the non-hydrogenated alloys. The fracture mode of the hydrogenated alloys after HIP and HT revealed cleavage fracture, indicating increased brittleness. In the as-built hydrogenated alloy, the fracture mode varied with location: brittle fracture occurred near the surface due to the formation of a hydride layer, while a more ductile fracture with dimples was observed below this layer.

Machine learning (ML) methods have been extensively applied to optimize additive manufacturing (AM) process parameters. However, existing studies predominantly focus on the relationship between processing parameters and properties for specific alloys, thus limiting their applicability to a broader range of materials. To address this issue, dimensionless parameters, which can be easily calculated from simple analytical expressions, were used as inputs to construct an ML model for classifying the relative density in laser-powder bed fusion. The model was trained using data from four widely used alloys collected from literature. The accuracy and generalizability of the trained model were validated using two laser-powder bed fusion (L-PBF) high-entropy alloys that were not included in the training process. The results demonstrate that the accuracy scores for both cases exceed 0.8. Moreover, the simple dimensionless inputs in the present model can be calculated conveniently without numerical simulations, thereby facilitating the recommendation of process parameters.

High-entropy alloys (HEAs) have attracted considerable attention because of their excellent properties and broad compositional design space. However, traditional trial-and-error methods for screening HEAs are costly and inefficient, thereby limiting the development of new materials. Although density functional theory (DFT), molecular dynamics (MD), and thermodynamic modeling have improved the design efficiency, their indirect connection to properties has led to limitations in calculation and prediction. With the awarding of the Nobel Prize in Physics and Chemistry to artificial intelligence (AI) related researchers, there has been a renewed enthusiasm for the application of machine learning (ML) in the field of alloy materials. In this study, common and advanced ML models and strategies in HEA design were introduced, and the mechanism by which ML can play a role in composition optimization and performance prediction was investigated through case studies. The general workflow of ML application in material design was also introduced from the programmer’s point of view, including data preprocessing, feature engineering, model training, evaluation, optimization, and interpretability. Furthermore, data scarcity, multi-model coupling, and other challenges and opportunities at the current stage were analyzed, and an outlook on future research directions was provided.

Casting technology is a fundamental and irreplaceable method in advanced manufacturing. The design and optimization of casting processes are crucial for producing high-performance, complex metal components. Transitioning from traditional process design based on "experience + experiment" to an integrated, intelligent approach is essential for achieving precise control over microstructure and properties. This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time. First, it explores process design methods based on casting simulation and integrated computational materials engineering (ICME). It then examines the application of machine learning (ML) in process design, highlighting its efficiency and existing challenges, along with the development of integrated intelligent design platforms. Finally, future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.

An ultra-strong steel with enhanced ductility and ultrafine lamellar structure was produced by heavy warm rolling (HWR) of metastable austenite and subsequent quenching. The HWR steel exhibited an ultrahigh yield strength of 1.09 GPa and an ultimate tensile strength of 2.6 GPa, with a total elongation of 6.7% at room temperature. The high yield strength was primarily attributed to the synergistic strengthening of high-density dislocations, nanotwins, and ultrafine martensite grains with an average effective grain size of 1.02 μm. The enhanced ductility is attributed to the parallel lamellar structure, which increased the work-hardening capacity and resulted in delamination toughening. Compared to the heavy multistage rolling (HMR) process, which starts rolling at higher temperatures, the HWR method employed in this study demonstrates significant enhancements in both strength and ductility. Following a 150 °C low-temperature tempering for 1 h, the yield strength of HWR steel was further increased to 2.2 GPa, and the total elongation improved to 10.1%.

The effects of various heat treatments on the microstructures and mechanical properties of as-built selective laser melted Inconel 718 alloy were investigated through conventional and quasi-in-situ tensile tests. The corresponding heat treatment processes include direct aging (DA), solution + aging (SA), and homogenization + aging (HA). The DA and SA samples preserve the melt pool configuration and grain size stability, while the precipitated phase characteristics reveal the refinement of the long-strip Laves phase and the appearance of the δ phase, respectively. The HA process induces recrystallization and grain coarsening. The specimens exhibit enhanced strength concomitant with diminished elongation, which is likely attributed to the reduction of the geometrically necessary dislocation density and the intensified precipitation of the γ′′ phase after heat treatment. Tensile plastic deformation displays notable strain concentration along grain boundaries. The dimensional alterations in precipitated phases were measured to quantitatively determine the impact of grain boundary, dislocation and precipitation strengthening on the yield strength after heat treatment. Precipitation strengthening encompasses coherent, order, and Orowan strengthening. A remarkable agreement is revealed between theoretical predictions and experimental results. Insights are offered for optimizing heat treatment processes to comprehend microstructural evolution effect on the mechanical properties of additive-manufactured metals.