High-entropy alloys (HEAs) have transcended the conventional solute-solvent alloy design paradigm and emerged as a promising materials platform to overcome the long-standing strength-ductility tradeoff in metallic materials. However, current studies on the strengthening and toughening of HEAs primarily focus on specific microstructural features or individual strengthening mechanisms, lacking a unified theoretical framework integrating alloy composition design, microstructural regulation, and deformation mechanisms. Based on a series of recent studies conducted by the authors and their collaborators, this study proposes and systematically develops the theory of entropy-enthalpy synergistic strengthening and toughening. This theory postulates that the superior mechanical performance of HEAs originates from their multiscale microstructures and cooperative deformation mechanisms, jointly governed by configurational entropy and chemical enthalpy. Building on this concept, a unified framework linking alloy composition design, microstructure development, deformation response, and strengthening-toughening performance is established. From the perspectives of atomic-scale local chemical ordering, nanoscale coherent precipitation, microscale metastability-induced phase transformation, and multiscale microstructural synergy, the strengthening and toughening mechanisms of HEAs are systematically summarized. Representative examples are further discussed to elucidate the similarities and distinctions between the strengthening-toughening mechanisms of HEAs and conventional alloys, thereby establishing a generalized design model for HEA strengthening and toughening.

The development of high-strength self-healing materials with heat and radiation resistance is crucial for improving the safety and reliability of advanced nuclear energy systems. However, conventional self-healing materials—including polymers and their composites—suffer from low strength, poor thermal stability, and insufficient irradiation resistance, severely limiting their practical applications in harsh nuclear environments. Self-healing of metallic or ceramic materials at high temperatures can be achieved through oxidation, atomic diffusion, or phase changes; however, this is impractical for in-service components. MAX phases are a family of nanolayered ternary carbides and nitrides with the general formula M_{n+ 1}AX_n. Their unique combination of metallic and ceramic properties—including high-temperature stability and radiation and damage tolerance—makes them promising candidates for nuclear applications. Nevertheless, the nanoscale self-healing behavior of MAX phases, particularly the underlying mechanisms and quantitative healing efficiency, remains largely unexplored. Moreover, the mechanical properties of single-crystalline Nb₄AlC₃MAX phase nanowires, particularly their fracture behaviors and postfracture self-healing capability, have not yet been systematically investigated. In this work, monocrystalline [0001]-oriented Nb₄AlC₃MAX phase nanowires were fabricated using focused ion beam-based nanofabrication. The mechanical behavior and fracture surface self-healing were quantitatively investigated by in situ tensile testing within TEM, elucidating the mechanical properties and fracture mechanisms under uniaxial tension along the c-axis and revealing the atomistic mechanisms governing room-temperature spontaneous self-healing of fractured surfaces. An electron beam irradiation strategy is also proposed to enhance healing efficiency and elucidate its underlying physical mechanisms. The results show that the nanowires exhibit brittle fracture under tensile stress (fracture strength: 6.98 GPa, super-elongation: 11.5%), attributed to the size effect and absence of defects at the nanoscale. The fractured surfaces spontaneously self-healed at room temperature, recovering 30.2% of the original fracture strength. Atomic-scale HRTEM characterization reveals that atomic rebonding across the fracture surfaces and atomic migration dominate self-healing. Furthermore, electron beam irradiation can cause lattice expansion along the c-axis and promote atomic migration, enabling more atoms to participate in rebonding and thereby further enhancing the healing efficiency (up to 56.3% recovery).

In metallic material processing, the microstructural and textural characteristics developed during each manufacturing stage establish the structural foundation for subsequent processing operations, creating substantial hereditary effects throughout the multistage manufacturing chain. This progressive, cross-process accumulation of microstructural and textural evolution makes precise tracing and effective control of microstructural inheritance pathways particularly complex during full-scale manufacturing from the initial ingot to the final TA18 tube blank. Microstructural inheritance forms the basis for structural design and property optimization in TA18 alloys. This investigation employed a 700-mm diameter TA18 alloy ingot as the starting material. The thermomechanical processing route comprised three stages: initial multipass forging in the β-phase field (1150-950 ^oC) followed by forging in the α + β phase field at 900 ^oC to produce a 170-mm diameter rough-forged bar; subsequent processing of the rough-forged bar in the two-phase region at 850 ^oC to obtain a 125-mm diameter finish-forged bar; finally, peeling, drilling, and canned hot extrusion of the finish-forged bar to fabricate tube blanks with inner and outer diameters of 28 and 42 mm, respectively. This study systematically investigates the hereditary evolution of microstructure and texture throughout the processing route from ingot to tube blank in the TA18 alloy and evaluates its impact on mechanical properties to guide the integrated control of multiscale microstructure and performance. The results demonstrate that microstructural hereditary characteristics can be categorized into three primary types. (1) Once established during rough forging, the micron-scale grain size and equiaxed α-phase morphology remain stably inherited in subsequent processing stages. Grain refinement serves as the fundamental basis for increasing axial tensile strength from 400 MPa to 550 MPa and improving elongation. (2) The inheritance of low angle grain boundary (LAGB) fraction exhibits dynamic evolution. The high fraction inherited during the rough- and finish-forging stages contributes to work hardening but negatively affects plasticity; in contrast, the low fraction inherited after extrusion, achieved via dynamic recrystallization, results in plasticity recovery. (3) The inheritance of crystallographic texture is governed by multiple competing mechanisms. The {0001}//axial direction (AD) basal texture and the <\mathrm{10}\overline{\mathrm{1}}\mathrm{0}>//AD texture originating from the central region of the ingot are strongly inherited during subsequent processing, with the intensity of the <\mathrm{10}\overline{\mathrm{1}}\mathrm{0}>//AD texture continuously increasing. The c-axis orientation of the α-phase undergoes controlled evolution during processing: it is randomly distributed after rough forging, transforms into a radial texture after finish forging, and finally develops into a circumferential texture after extrusion. The TA18 alloy controls the inheritance and evolution of crystallographic orientation through the competition and synergy of various mechanisms, including initial crystallographic orientation, deformation, and dynamic recrystallization. The integrated design of TA18 alloy tube blanks, possessing high strength and good plasticity can be achieved by reinforcing beneficial hereditary features (such as fine grains and favorable texture) and interrupting harmful features (such as high LAGB fraction and unfavorable texture).

To enhance the poor mechanical properties of 3003 aluminum alloys, their solidification behavior as well as the effect of the homogenization temperature on their microstructure and mechanical properties were systematically investigated based on thermodynamic simulations, SEM, EBSD, and TEM. The results showed that during the solidification of 3003 aluminum alloys, the formation and growth of eutectic α-AlMnFeSi are mainly governed by the Mn content in the melt. Furthermore, during the homogenization process, the precipitate size and distribution as well as the average width of the precipitate-free zones at the grain boundaries are strongly affected by the homogenization temperature, which impacts the mechanical properties of the alloys. Homogenization at (555 ± 5) °C resulted in a higher precipitate volume fraction and smaller precipitate size, considerably enhancing the yield strength of the annealed and work-hardened 3003 aluminum alloys. In particular, the yield strength of the 3003 aluminum alloys homogenized at (555 ± 5) °C was 16-21 MPa higher than those of the alloys homogenized at (600 ± 5) °C.

Laser surface remelting (LSR) technology significantly enhances the mechanical properties of the TC4 titanium alloy. A comprehensive investigation into the microstructural evolution of TC4 alloy during LSR and its effects on subsequent tensile deformation mechanism is essential for optimizing LSR. In this study, LSR treatment was applied to both the front and back of full martensitic TC4 specimens, followed by tensile testing. TEM and EBSD were used to analyze the microstructural evolution during tensile deformation, focusing on the formation and distribution characteristics of \{\mathrm{10}\overline{\mathrm{1}}\mathrm{2}\}twins. The results show that rapid cooling during LSR induces significant residual stress. This in turn not only promotes the preferential formation of specific martensite variants but also lowers the critical shear stress required for twinning. In addition, the evaporation of aluminum during laser treatment decreases the c / a ratio of the TC4 alloy, weakens the anisotropy of the crystal lattice, and further promotes the formation of\{\mathrm{10}\overline{\mathrm{1}}\mathrm{2}\}twins. These twins are primarily concentrated in several martensite variants with specific orientations, exhibiting a clear tendency for preferential formation under rapid cooling conditions.

During the secondary welding process of titanium-steel hybrid structures for ships, repeated thermal cycles inevitably change the interfacial microstructure and mechanical properties of explosive-welded transit joints. These changes directly affect the bonding strength of hybrid structures and navigational safety of ships. Herein, simulated transient heat treatment (STHT) was adopted to study the relationship among temperature, interfacial microstructure, and bonding properties of a titanium-steel hybrid structures during the secondary welding process. Results showed that when the STHT temperature was <600 ^oC, the interfacial microstructure remained stable. Meanwhile, at ≥ 700 ^oC, recrystallization occurred, causing grains near the interface to become coarse. Furthermore, the thickness of the intermetallic compound layer comprising FeTi and TiC increased rapidly. Unlike aluminum-steel hybrid structures, in which the interfacial bonding strength monotonically decreases with increasing temperature, the bonding and shear strengths of the titanium-steel hybrid structures initially increased and then decreased, with peaks appearing at 500 and 600 ^oC. The thermal effect at medium and low temperatures promoted atomic diffusion and stress release, thereby improving the interfacial bonding strength. At high temperatures, grain coarsening and intermetallic compound growth decreased the bonding strength of the transit joint. Overall, the critical threshold temperature at the interface of the titanium-steel hybrid structures is 600 ^oC.

Bainitic rail steels have been extensively studied as a solution to the considerable fatigue and wear issues experienced with conventional pearlitic rails. With railway constructions in high-cold regions, the effect of low temperatures on the fatigue performance of railways has garnered considerable attention. Despite several studies on the room-temperature fatigue performance of high-strength steels, the effect of the microstructure, particularly retained austenite (RA), on the low-temperature fatigue crack growth behavior in bainitic rail steels remains unclear. This study examined the low-temperature fatigue crack propagation behavior of U20Mn2SiCrNiMo (U20Mn) bainitic rail steel subjected to hot rolling and air cooling. The microstructure of the bainitic rail steel was characterized employing SEM, TEM, EBSD, and XRD. The conventional mechanical properties and fatigue crack propagation rate (da / dN; where a is the crack length and N is the number of stress cycles) were determined at room temperature (20-25 ^oC) and -40 ^oC. The results demonstrated that the U20Mn bainitic rail steel was primarily composed of a granular bainite/martensite multiphase structure, with approximately 10% (volume fraction) RA. A decrease in the experimental temperature increased the tensile and yield strengths of the U20Mn rail steel; however, its impact toughness decreased. The da / dNvs stress intensity factor (ΔK) curves for U20Mn rail steel at room temperature and -40 ^oC indicated that the fatigue crack propagation rate reduced at low temperatures within the ΔK range of 8.0-18.0 MPa·m^1/2. However, an examination of the fatigue fracture surface revealed a transition from ductile to brittle fractures at -40 ^oC. This indicates that the combined effects of the increased strength, decreased toughness, and changes in the stability of RA at low temperatures are the underlying factors responsible for the variation in the low-temperature fatigue crack propagation rate of bainitic rail steel.

High-strength steels are essential materials in various sectors, such as engineering machinery, marine engineering, and hydropower. Welding is a crucial thermal processing technique for fabricating structural components made of high-strength steels. The weld metal, as a vital component of the welded joint, plays a pivotal role in determining the applicability and service life of weldments through its microstructural characteristics and properties. At present, steel manufacturers globally have developed 1000 MPa grade high-strength steels. However, the welding consumables associated with these steels exhibit inadequate strength-toughness matching, which significantly hinders their widespread adoption. In this study, weld metals of 1000 MPa grade high-strength steels with three different Mo contents were produced via the gas metal arc welding process. A comprehensive investigation of the microstructure and mechanical properties of weld metals of 1000 MPa grade high-strength steels were conducted using SEM, EBSD, TEM, tensile testing, and Charpy impact testing. The influence mechanism of Mo content on the microstructural evolution was elucidated. The microstructural characterization revealed that the weld metals predominantly comprised lath bainite (LB) and coalesced bainite (CB). As the Mo content was increased, the proportion of high angle grain boundaries initially decreased and then increased. The morphology of LB transitioned from an interwoven structure to a more parallel arrangement, which was accompanied by an increase in the CB content. Mechanical testing revealed that a higher Mo content enhanced the metal hardenability, resulting in increased yield strength, tensile strength, and hardness. In contrast, the impact toughness initially decreased and then slightly increased. Analysis of the crack propagation paths on the cross-sections beneath the impact fracture surfaces demonstrated that the cracks readily propagated through the CB regions. The presence of CB considerably impaired the impact toughness of the weld metals. The optimal balance between strength and toughness in the weld metals was achieved at 0.71% Mo, resulting in a yield strength of (939 ± 10) MPa, a tensile strength of (1181 ± 2) MPa, and a room-temperature impact energy of (60 ± 3) J.

To understand the relations between the corrosion behaviors of nanocrystalline and conventional polycrystalline 304 stainless steels and their microstructures and microhardness, the microhardness of nanocrystalline 304 stainless steel plate (NSSP-304) produced using severe rolling technology and its counterpart of a conventional polycrystalline 304 stainless steel (CPSS-304) were investigated on the three planes perpendicular to each other. The microstructures of NSSP-304 and CPSS-304 were characterized using XRD, TEM, and EBSD. The microhardnesses on the three planes of NSSP-304 were higher than those of CPSS-304, which was unrelated to the martensite phase. The microhardness distributions on the three planes of NSSP-304 were more uniform than those of CPSS-304. The microhardness of NSSP-304 on the rolling plane was approximately 40 HV higher than on the other two planes, attributed to its weak texture ({110}<211>). Despite the weak texture, the corrosion rates of NSSP-304 varied with corrosion time within the narrower ranges than those of CPSS-304 during potentiostatic polarization in 0.5 mol/L HCl solution at room temperature and in 6%FeCl₃ solution (35 ^oC). NSSP-304 exhibited lower corrosion rates compared to CPSS-304, while the pitting corrosion resistance of the former was higher than those of the latter in both kinds of aqueous solutions. These results demonstrated that the texture, the high microhardness, the twins, and high-density dislocations of NSSSP-304 did not degrade its uniform and pitting corrosion resistances despite undergoing severe deformation during production (total deformation > 70%). Compared to CPSS-304, the higher microhardness, improved uniformity, and pitting corrosion resistances of NSSP-304 were attributed to its distinct configurations of valence electrons (i.e., their higher binding energies, higher weight values at higher energy levels, lower weight values at lower levels, and larger work function) derived from its grain refinement, dislocation accumulation, deformation twins, and larger fraction of low angle grain boundaries.

Natural bamboo fiber possesses excellent mechanical properties due to its unique microstructure, providing valuable inspiration for the configurational design of reinforcement in metal matrix composites. To address the typical high-strength but low-ductility characteristics of discontinuously reinforced titanium matrix composites, TiB/Ti composites with a bamboo-fiber-inspired architecture were successfully fabricated in this work. Comparative analysis of the mechanical properties of the fiber-like structure with those of their uniform counterpart revealed that the fiber-like arrangement of TiB whiskers was important in mechanical behaviors and fracture mechanisms of the composites. At the same TiB volume fraction, the fiber-like structured TiB/Ti composite maintained the tensile strength comparable to that of the composite with uniformly distributed TiB whiskers, while achieving a fracture elongation of 19.1%. The high strength was mainly attributed to the high load-bearing efficiency of the fiber-like distributed TiB whiskers and the grain-refinement strengthening induced by the reinforcements. Meanwhile, the continuous Ti matrix region synergistically enhanced the strain-hardening rate and improved the plastic deformation capability of the composites. During the coordinated deformation of the continuous Ti matrix and the fiber-like structure, these matrix regions effectively blunted and deflected cracks, thereby further improving the toughness of the composite.

The microstructure evolution and stress-coupling failure of copper alloys are the primary factors contributing to their accelerated degradation in deep-sea environments, particularly under seawater pressure. In this study, high-manganese aluminum bronze (MAB), a material commonly used in ship propellers, is selected as the research subject. The atomic structure model of MAB alloy with aluminum atomic surface segregation and the strain-coupling model under varying seawater pressures are established through a combination of simulation and experimentation. The failure mechanism under different pressures is further examined, and the corrosion rate is predicted. As seawater pressure increases from 0.1 MPa to 10.0 MPa, the alloy's dislocation density and strain level progressively rise. When the pressure exceeds 6.0 MPa, these increases become more pronounced. The dislocation density of the alloy's (111) crystal surface increases by 6.08 × 10^-3 nm^-2, while the elastic micro-strain level rises by 0.79%. Experimental results indicate that the mass loss rate of copper alloys escalates with increasing pressure. Additionally, the morphology of the corrosion products transitions from a spot-like to a lamellar structure. Density functional theory calculations reveal that seawater pressure significantly affects the stability of the alloy structure. When seawater pressure surpasses the critical threshold of 6.0 MPa, the copper vacancy formation energy and migration-dissolution activation barrier decrease substantially, leading to a notable increase in the dissolution rate. The molecular dynamics method is employed to investigate the adsorption behavior of Cl^- on the alloy surface under deep-sea pressure and its influence on corrosion. The results demonstrate that increasing pressure enhances the chemical adsorption of Cl^-. However, at 10.0 MPa, the saturated adsorption of Cl^- on the surface does not significantly affect the dissolution rate.

Data-driven methods based on machine learning have been employed to predict fatigue crack propagation. However, existing studies have largely overlooked the multi-scale nature of this process. Relying solely on macroscopic data for long-crack prediction often fails to capture the complete crack growth process, potentially resulting in non-conservative predictions. Moreover, purely data-driven models often lack interpretability, exhibit limited generalization capabilities, and struggle to adhere to physical laws. The challenge of integrating modeling with reasonable interpretations, driven by both data and mechanisms, remains a significant issue for researchers. In this study, we selected 304 austenitic stainless steel as the research object. To identify the algorithm with the best predictive performance, firstly, the fatigue crack propagation prediction capabilities of three algorithms were compared: K-nearest neighbor (KNN), support vector machine regression (SVR), and random forest (RF). The most effective algorithm and implemented data augmentation strategies based on three fatigue crack propagation models were selected, namely, long cracks, short cracks, and multi-scale cracks, to enhance prediction accuracy. Finally, using a dual-drive model framework that incorporated the data augmentation strategy, predictions of multi-scale fatigue crack propagation under different loads were conducted. Compared to the SVR and KNN algorithms, the results indicated that the RF algorithm had a lower root mean square error (RMSE) value and higher coefficient of determination (R²), making it more suitable for predicting fatigue crack propagation. Under a load of 370 MPa, the prediction accuracy for the training set ranked in the order of RF > KNN > SVR. By contrast, the accuracy for the test set was in the order of RF > SVR > KNN. The multi-scale fatigue crack propagation model effectively captured the entire process of crack growth, whereas the long- and short-crack models accurately represented only parts of it. Data enhancement based on the multi-scale crack model demonstrated significantly better results than the other two models, with increases in accuracy of 25.76% and 71.74% for the training and test sets, respectively. The dual-drive model based on the RF algorithm and data enhancement strategy exhibited strong generalization capabilities. Under a load of 350 MPa, the RMSE values for the training and test sets were 0.046 and 0.111, respectively, and R² reached 0.995 and 0.961. Under a load of 330 MPa, the RMSE values for the training and test sets were 0.171 and 0.081, respectively, and the R² reached 0.911 and 0.721. Finally, compared with the pure data-driven model based on the RF algorithm, the predictions from the dual-drive model were found to be significantly more accurate.

Recent studies indicate that zinc alloys are preferred in biodegradable metal materials owing to their unique biodegradability and biocompatibility. However, their mechanical properties are relatively insufficient; thus, it is crucial to design zinc alloys that meet the mechanical performance implantation standards required for application in biomedicine. The traditional alloy design method depends on experience and trial and error resulting in low efficiency and high cost. In recent years, the rapid development of artificial intelligence has provided new tools and methods for material science. Machine learning (ML), a subset of artificial intelligence, offers new ideas for material design and prediction. This study obtained the mechanical property data of the Zn-Mg-Mn alloy through experimental investigation and literature review. A performance-oriented ML model was used to predict the compressive yield strength (CYS) and hardness of the Zn-Mg-Mn alloy, considering various element types and contents and different alloy preparation processes. Furthermore, the influence of the element types and contents on the microstructure and macroscopic mechanical properties of the material was explored. Based on the existing dataset, a comparative evaluation of seven machine learning algorithms was conducted, and the k-nearest neighbors (KNN) algorithm exhibited the highest predictive performance. To further validate the accuracy of the model prediction, a random method was used to select data beyond the dataset for comparative analysis with the model results. Simultaneously, the Shapley additive explanation method was applied to quantitatively examine the correlation between the two alloying elements, the preparation process, the CYS, and the hardness in the Zn-Mg-Mn alloy. The Mg element was determined to significantly impact the alloy's CYS and hardness. Finally, the influence of individual elements on the mechanical properties of the materials was analyzed through microstructure characterization. The results showed that the formation of new phases (Mg₂Zn₁₁ and MgZn₁₃) due to adding alloy elements significantly affected the mechanical properties. Based on the research results, this study proposed a composition ratio range for the Zn-Mg-Mn alloy to satisfy the mechanical performance standards required for medical implant materials. When Mg content is between 2.25% and 2.50% (mass fraction, the same below) and Mn content is between 2.50% and 3.50%, the CYS and hardness of the alloy comply with the implant standards.