This study investigated high-temperature mechanical performance of 2196 Al-Cu-Li extrusions with different heat treatments. At 100 degrees C, extrusions' performance is close to that at room temperature. At 200 degrees C, the strength decreases by 10%, and at 300 degrees C, it decreases by more than 30%, which is attributed primarily to the coarsening of T1, widening of no precipitation zone (PFZ) at grain boundaries and reduction of dislocation density caused by dynamic recovery (DRV). The prestretching with low-temperature preaging thermomechanical treatment (CPT5%-IA) promoted the uniform precipitation of T1 and suppressed its coarsening; therefore, the CPT-5%-IA finegrained matrix specimen exhibited favorable high-temperature performance, and possessed a yield strength of over 350 MPa at 300 degrees C. However, CPT-5%-IA has limited effectiveness in improving the high-temperature performance of coarse-grained welding areas after abnormal grain growth (AGG). The precipitates in the AGG area exhibit low thermal stability, and the substantial precipitation of sigma phases in the AGG area depleted strengthening elements and weakened aging response, thereby resulting in coarsening and low density of T1 phases, and the precipitation of T2 and eta phases at the grain boundaries. Finally, welding area exhibits brittle intergranular fracture even at high temperatures.

High magnetic permeability and low power loss are critical requirements for amorphous soft magnetic composites in high-frequency electronics. They are also typically mutually exclusive; low power loss requires insulating interfaces between magnetic particles, but conventional insulating interfaces cause magnetic dilution and decoupling, reducing permeability. Here, we introduce an interfacial spin-order engineering strategy that departs from traditional ferromagnetic interface solutions. By exploiting a thermally-electrically activated oxygen migration process, we construct a gradient oxygen-deficient functional layer between heterogeneous interfaces, enabling atomic-scale control of interfacial spin configurations. This engineered interface leads to a 150% increase in magnetic permeability and a 76% reduction in power loss, outperforming state-of-the-art counterparts. Neutron dark-field imaging provides direct, bulk-sensitive evidence that oxygen-defect-mediated spin ordering induces enlarged magnetic domains with intergranular magnetic connectivity. Mechanistically, defect-mediated super-exchange interactions reverse the spin orientation of Ce and Fe atoms at the heterointerface, transforming disordered or antiferromagnetic alignment into ferromagnetic coupling and thereby eliminating magnetic coupling barriers across particles. Our work demonstrates interfacial spin-ordering as a generalizable design principle, mitigating the long-standing permeability-loss trade-off. In soft magnetic materials, suppressing eddy currents is usually achieved by forming insulating layers between magnetic grains, degrading the magnetic permeability. Here, to overcome this trade-off, Ding, Wang, Chen, and co-authors present an approach to engineer an oxygen deficiency gradient, allowing for control of the interfacial spin-configurations.

Longitudinal welds in 2196 Al-Cu-Li extrusions exhibit heterogeneous microstructures that strongly affect corrosion behavior. In this study, corrosion behavior and microstructural evolution of the coarse-grain longitudinal weld zone and fine-grain matrix zone were systematically investigated after different heat treatment processes. T1 (Al2CuLi) and δ′ (Al3Li) were identified as the primary strengthening phases after long-term aging at 170°C, their large potential difference from matrix promoted micro-galvanic corrosion, and led to severe pitting corrosion and poor corrosion resistance of T6 and T85 samples. After three-stage aging, the strengthening precipitates transformed into θ′ (Al2Cu) and δ′ and formed a multilayer core-shell structure (δ′/θ'/δ′). This structure enhanced the stability of the precipitate/matrix interface, reduced the potential difference with matrix and effectively suppressed micro-galvanic corrosion, which resulted in the best corrosion resistance among all heat treatment conditions. The re-solution aging (RST) treatment simultaneously provided superior corrosion resistance and satisfactory mechanical properties. Compared with the fine-grain matrix zone, the longitudinal weld zone exhibited coarser precipitates and continuous grain-boundary precipitates (GBPs), which accelerated corrosion through enhanced micro-galvanic corrosion, whereas the finer precipitates in the matrix zone resulted in a smaller potential difference and better corrosion resistance. These findings reveal the relationship between precipitation evolution, weld microstructural heterogeneity, and corrosion behavior, which can provide guidance for optimizing the heat treatment of 2196 Al-Cu-Li extrusions with longitudinal welds.

This study focuses on the of key engineering parameters for the repair of shipboard carbon fiber reinforced polymer composite structures using a scarf patch repair configuration. A three-dimensional finite element model was developed to systematically analyze the effects of repair location (center-symmetric, diagonal-asymmetric, and edge-unidirectional) and cut-out depth (2.0 mm, 3.0 mm, and 4.0 mm) on the mechanical response of the repair structure. The results indicate that although the local stress level of the center-symmetric repair is slightly higher, it provides a continuous load transfer path with more balanced stress distribution, demonstrating the best overall mechanical performance. When the cut-out depth is 3.0 mm, the repair structure achieves an optimal balance between stress uniformity and displacement coordination, effectively reducing the risk of early adhesive layer failure and local buckling. This study identifies the optimal parameter combination for scarf patch repairs, providing important theoretical foundations and references for the design of repair processes and the standardization of engineering practices in shipboard composite structures.

High-entropy bulk metallic glasses (HE-BMGs) exhibit exceptionally high strength and elasticity but often suffer from limited ductility at room temperature. To improve their plasticity, elastostatic compression (ESC) was utilized to tailor the room-temperature compressive plasticity of a Ti20Zr20Hf20Be20Cu20 (at%) high-entropy bulk metallic glass (HE-BMG) in this study. Experimental results indicate that the ESC treated HE-BMG preserves fully amorphous structure without any crystallization. However, the applied elastostatic stress promotes structural rejuvenation, and the rejuvenation extent increases progressively with increasing the loading stress. Correspondingly, the relaxation enthalpy rises from 3.66 J g-1 for the as-cast sample to 8.73 J g-1 for the ESC70 specimen, while the room-temperature plastic strain is significantly improved from 0.73% to 5.18%. With increasing the loading stress, the yield strength slightly decreases, yet it remains high at approximately 1900 MPa. Similarly, both the nanoindentation hardness and modulus show a moderate decrease. These findings demonstrate that ESC can effectively promote the increase of free-volume content and the activation of more shear transformation zones, offering a pathway to enhance the plasticity of HE-BMGs. Furthermore, the highentropy effect on the rejuvenation induced mechanical softening and enhancement of compressive plasticity of the HE-BMG is discussed.

Al/Cu laminated metal composites (LMCs) demonstrate promising application prospects across multiple fields due to their functional integration advantages. However, challenges remain in controlling interlayer deformation compatibility and interfacial bonding quality during severe plastic forming. In this study, Al/Cu LMC thin-walled conical parts (TWCPs) with different thinning ratios (TRs) were fabricated via shear spinning, followed by a systematic analysis of macroscopic morphology, microstructure, and mechanical properties. The results indicate that interlayer deformation compatibility improves with increasing TR, driven by the work hardening of the Al layer and the reduction of stress gradients. The TWCPs achieve peak yield and ultimate tensile strengths at 50% TR, and a superior balance of shear strength and ductility at 65% TR. Microstructural analysis reveals that grain refinement in both Al and Cu layers intensifies with increasing TR; the former is governed by dynamic recovery and recrystallization, whereas the latter is dominated by dislocation accumulation and grain fragmentation. Furthermore, the interface evolves through the fracture of brittle intermetallic compounds (IMCs), the extrusion and contact of fresh metal matrices, and the subsequent formation and thickening of new IMCs layers as the TR increases. Molecular dynamics simulations demonstrate that higher TRs induce significant localized shear deformation and temperature rises, while accumulated dislocation densities and vacancy concentrations of Cu layer facilitate interdiffusion. This study elucidates the thermo-mechano-diffusion coupling mechanism in Al/Cu LMCs during shear spinning, providing a theoretical basis for optimizing the trade-off between strength and ductility in composite forming.

Thermomechanically processed metallic alloys usually exhibit complex anisotropic yield behavior induced by crystallographic texture. Owing to their fixed mathematical form, conventional yield criteria possess limited accuracy and flexibility in capturing such anisotropy, and they require costly parameter recalibration when applied to different materials or crystallographic textures. This paper introduces the generalized convex yield network (GCYN), a feedforward neural network with partial input convexity constraints to predict the yield onset. The proposed architecture decomposes the yield function into a convex stress-dependent branch that guarantees global convexity of the yield surface, and a non-convex branch integrates tailored material descriptors, such as generalized spherical harmonics (GSH) coefficients and typical yield onsets, to explicitly capture anisotropic yield behavior across distinct textures and materials. This bifurcated design enables the GCYN to learn texture/material-specific corrections to the yield surface. The generalizability of GCYN across textures was demonstrated by training on yield datasets for different textured TA1 titanium generated via crystal plasticity (CP) simulations. The well-tuned criteria accurately predicts the yield onsets when applying to the untrained textures, achieving an average prediction error of 0.903% in the 6D stress space. In addition, GCYN accurately predicted the yield onsets of some experimental titanium textures with different characteristics. To demonstrate the potential applicability of GCYN to different materials at a conceptual level, the model was trained on datasets generated from the Lode-dependent anisotropic-asymmetric (LAA) Hill48 criterion. The trained model accurately emulates a parameterized family of analytical yield loci, achieving an average prediction error below 0.2% in plane. Moreover, The yield loci predicted by the GCYN strictly satisfy global convexity while preserving the essential characteristics of the original yield surface. This work provides a fully convex and material/texture-sensitive yield criterion.

In this study, the corrosion behavior of CuXCoCrMoNi (x = 0.3, 0.6, 0.9) high-entropy alloys (HEAs) in 3.5% NaCl solution is systematically investigated. The alloy samples show a strong link between copper content and corrosion resistance. It is noteworthy that an increase in copper content promotes element segregation, resulting in an increase in corrosion current density from 2.138 × 10-7 μA/cm2 to 1.8989 × 10-6 μA/cm2 and a decrease in charge transfer resistance from 182.6 Ω·cm2 to 42.34 Ω·cm2. In addition, electrochemical experiments demonstrate that lowering the copper content in the alloys reduces the spread and depth of corrosion. All alloys exhibit n-type semiconductor behavior, with donor density increasing from 4.792 × 1023 cm-3 to 5.581 × 1023 cm-3 with increasing copper content. Notably, the passive film is characterized by the presence of Cr2O3 and Cu2O as its main constituents. As the copper content in the HEA increases, higher levels of copper oxides in the passive film inhibit the formation of chromium oxides. This degrades the passive film quality, thereby diminishing the overall corrosion resistance.

Ultrasonic vibration (UV)-assisted forming has been widely applied to enhance the plastic deformation of metals, yet its effects on the forming quality and strengthening behavior of the microstructure of the rolled surface remain insufficiently understood. In this study, UV-assisted rolling was employed to fabricate U-shaped and rectangular microchannels with a width of 0.5 mm on 1060 aluminum strips, using a self-developed device with UV amplitudes ranging from 0 to 10 μm. The forming quality, near-surface microstructure, and microhardness of the rolled microchannels were systematically characterized, and the underlying dislocation mechanisms were probed by molecular dynamics simulations. The results show that UV improves the geometric filling and depth-to-width ratio of the microchannels by approximately 26.7% and 44.2%, respectively, while reducing surface roughness. UV enhances the gradient microstructure and the microhardness at the bottom of the microchannel. Notably, despite the high stacking-fault energy of aluminum, UV promotes extensive stacking faults and Lomer-Cottrell locks in the near-surface region. MD simulations reveal that UV reduces the resolved shear stress and slows the slip of the Shockley partials, so that fewer partials are absorbed or annihilated at boundaries and more stacking faults are retained. By quantitatively decoupling the Hall-Petch and Taylor strengthening contributions, dislocation strengthening is shown to contribute approximately twice as much as grain refinement to the UV-induced microhardness increment, identifying dislocation multiplication as the dominant strengthening pathway in UV-assisted rolling.

Hot extrusion is a critical manufacturing technology for tailoring microstructure and eliminating metallurgical defects of powder metallurgy (P/M) superalloys in industrial applications. However, the complex coupling between severe plastic deformation and adiabatic heating challenges the prediction and precise control of microstructures. To address this challenge, this study proposed a synergistic end-to-end framework integrating a continuous strain-gradient high-throughput extrusion technique with physics-constrained interpretable machine learning. The established paradigm enables the rapid acquisition of microstructural evolution data under a wide strain range of 0-2, facilitating the determination of grain refinement limit of 3.63 & micro;m at the strain of approximately 1.0. By leveraging the explicit kinetic formulas mined by symbolic regression, we quantitatively decoupled the competing contributions of dynamic recrystallization (DRX) and thermally activated grain growth. The kinetic analysis demonstrates that the grain refinement during the initial stage is primarily governed by the concurrent activation of multiple DRX nucleation ways and dynamic precipitation of primary gamma' precipitates at grain boundaries. Then, the adiabatic deformation heat-driven gamma' redissolution and subsequent grain growth dominated the later stage after the saturation of DRX. These findings challenge the conventional 'larger strain, finer grain size' consensus during extrusion, providing a generalizable optimization strategy for metal extrusion processing that extends beyond the specific case of superalloys.

This study investigates the high-temperature oxidation behavior of Zr55Cu30Al10Ni5 metallic glass (MG) powders using thermogravimetric analysis combined with multiscale characterization. The powders follow diffusion-controlled parabolic kinetics but oxidize up to four orders of magnitude faster than bulk alloys, owing to curvature-enhanced transport and nanogranular oxide structures that promote short-circuit diffusion. Oxidation produces a stratified scale with an outer Cu-rich layer and inner ZrO2-dominated sublayers. Interfacial porosity indicates diffusion-flux imbalance associated with selective Cu outward migration. Unlike bulk metallic glasses, prolonged oxidation causes spontaneous particle fragmentation driven by growth-induced tangential stress. A fracture criterion shows that the critical oxide thickness scales with the square of the particle radius, leading to a size-dependent instability condition. Based on this scaling, a practical model for critical oxidation time is derived to guide safe thermal exposure in laser powder bed fusion. Particle size thus governs oxidation kinetics, scale integrity, and powder reusability.

ABSTRACT Phase separation offers a promising avenue to mitigate the inherent brittleness of metallic glasses. However, traditional approaches relying on mixing enthalpy face significant challenges, primarily due to the detrimental impact on glass‐forming ability. In this study, we present a novel stress‐driven phase separation strategy that harnesses internal stresses generated through cryogenic cycling to catalyze the formation of new nano‐amorphous phases. By employing preformed ordered clusters as nucleation sites, internal stresses facilitate ultra‐nano scale phase separation by promoting demixing between elements with distinct diffusion capacities. These preexisting nuclei effectively lower the energy barrier, enabling the preferential precipitation and growth of more diffusible elements. Using this approach, we synthesized ultra‐nano Cu‐rich phase‐separated Zr‐based metallic glasses, which demonstrate a fourfold increase in uniform plastic strain (from ∼1.9% to ∼8%) and enhanced nano‐creep resistance. This work addresses the long‐standing trade‐off between glass formation and phase separation, establishing a kinetically modulated pathway to ultra‐nano phase‐separated metallic glasses.

This study investigates the divergent effects of deep cryogenic treatment (DCT) on the structure and soft magnetic properties of two Fe-based metallic glasses (MGs), FeSiB and FeSiBCCr. Results show that DCT induces non-monotonic structural relaxation in both alloys, but their magnetic responses differ significantly. For FeSiB, coercivity (Hc) decreases by 7.3% while permeability (μ) and saturation magnetization (Ms) remain largely unchanged. In contrast, FeSiBCCr exhibits substantial improvements in both permeability (up 25% at 1 kHz) and saturation magnetization (up 9%, 164→178 emu/g), achieving synergistic property enhancement. Correlation analysis identifies average electronegativity as the key parameter governing changes in saturation magnetization, while mixing entropy and average atomic size difference primarily influence coercivity reduction. Mössbauer spectroscopy suggests that DCT is associated with the evolution of weakly magnetic local environments toward more magnetically ordered atomic configurations, which may contribute to the release of the initially suppressed magnetic moments. These findings elucidate the atomic-scale order modulation mechanism of DCT and provide preliminary indications for designing high-performance soft magnetic MGs through tailored compositions and post-processing.

Oxidation behaviors and mechanisms of the CoCrFeNiCu high-entropy alloy prepared via spark plasma sintering (SPS-HEA) are markedly under-explored, which deteriorates its reliability at high-temperature applications and impedes the development of anti-oxidation strategies. This study investigated the high-temperature oxidation behavior of CoCrFeNiCu high-entropy alloys prepared via spark plasma sintering (SPS-HEA) and compared it with their as-cast counterparts (Cast-HEA). Results indicated that while both alloys exhibited an approximate diffusion-controlled parabolic oxide-scale growth trend based on semi-quantitative cross-sectional measurements at 700 degrees C and 800 degrees C, their oxide layer structures and internal oxidation behaviors differed significantly, with the SPS-HEA demonstrating superior oxidation resistance over Cast-HEA. The novelty of this work lies in demonstrating that SPS processing enhances oxidation resistance not simply by densification, but by refining and discontinuously distributing Cu-rich phases to suppress continuous CuO-rich scale growth and promote protective Cr-containing oxides. Cast-HEA developed multiple surface oxides influenced by Cu-rich phase barriers, with internal oxidation proceeding along the phase boundaries. In terms of SPS-HEA, internal pores promoted pronounced internal oxidation, and a continuous Cr-rich oxide layer formed under thermodynamic control. The mechanisms that accounted for the oxide spallation at 900 degrees C differed between the Cast-HEA and SPS-HEA, which were internal oxidation-induced interface weakening and Cu segregation-driven outer layer detachment, respectively.

Controlling the microstructure of electroless nickel coatings is crucial for optimizing the interfacial properties of carbon fibers. However, a systematic understanding of how dispersants can effectively leverage the refining effect of nanoparticles in composite plating systems remains lacking. This paper proposes the use of a composite dispersant, comprising polyethylene glycol (PEG) and sodium methylene bis-naphthalene sulfonate (NNO) at a 1:1 mass ratio, for nano-Al2O3 to achieve microstructure refinement of nickel coatings on carbon fiber surfaces. The results demonstrate that the composite dispersant modifies the surface state and dispersion stability of Al2O3 particles through synergistic adsorption, thereby regulating the nucleation and growth behavior of the Ni-P alloy. At an optimal composite dispersant concentration of 3 g/L, the coating exhibits the most compact structure, with Ni-P particle size refined to approximately 181 nm. The coating consists of two phases: crystalline Ni3P and amorphous Ni-P. The dual adsorption effect of the dispersant—inhibiting Al2O3 agglomeration while improving the surface wettability of carbon fibers—is key to enhancing the refinement efficiency. Conversely, excessive dispersant addition leads to deteriorated coating quality. This study provides experimental evidence for understanding the multiphase interfacial interaction mechanism involving organic additives, nanoparticles, and metal deposition, and offers a novel strategy for controlling the surface functionalization of carbon fibers.

Cu/Ti composite joints are widely used in high-end equipment, and improving their interfacial bonding performance is of great practical significance. This work adopts a self-developed ultrasonic-assisted solid-phase consolidation method to bond Cu/Ti joints at 1023 K with different ultrasonic amplitudes. Experimental results show that ultrasonic vibration effectively improves joint shear strength: the maximum value reaches 139.33 MPa, much higher than 54.67 MPa obtained via conventional thermal diffusion bonding. The increased diffusion layer thickness dominates the strength enhancement, which counteracts the adverse impact of brittle CuTi2 intermetallic compounds. Excessive amplitude generates interfacial defects and reduces mechanical performance. Molecular dynamics simulations further verified the atomic diffusion behavior and interfacial stability evolution under ultrasonic vibration, revealing the intrinsic bonding mechanism.

To accurately characterize the warm deformation behavior and workability of the 5A06 aluminum alloy, this study presents an innovative workflow that develops and systematically validates machine learning-assisted Johnson-Cook (ML-JC) frameworks based on artificial neural network (ANN) surrogate models. Two predictive frameworks-the parallel-decoupled PD-ANN-JC and the multi-objective integrated MOI-ANN-JC-were constructed. Quantitatively, both developed ML-JC frameworks achieve significantly higher stress prediction accuracy and superior generalization capability compared with the conventional JC model. Specifically, on the testing set, the MOI-ANN-JC framework yields an average absolute relative error (AARE) of 1.424% and an R2 of 0.997, outperforming the PD-ANN-JC framework (AARE of 3.246%, R2 of 0.988). On the validation set, the MOI-ANN-JC framework also demonstrates exceptional generalization, with an AARE of 3.302% and an R2 of 0.987. Scientifically, the superior performance of the MOI-ANN-JC framework stems from its ANN-mnδ surrogate model, which simultaneously predicts the strain hardening exponent n, thermal softening exponent m, and relative error δ directly from deformation parameters. This mutual coupling establishes an intrinsic correlation between m and n, successfully aligning with the physical reality wherein strain hardening and thermal softening are inherently linked during deformation. Qualitatively and practically, by integrating the MOI-ANN-JC framework into finite element (FE) simulation software, dynamic tracking and visualization of the thermal softening exponent m during warm deformation were achieved. Combined with FE simulations, Vickers hardness testing and EBSD observations, this study successfully establishes a direct qualitative spatial correspondence between low-m regions and macroscopic defects, which was further verified through the warm forging of a thin-walled dual-cavity component. Crucially, this approach for evaluating deformation stability bridges the gap caused by the inapplicability of conventional processing maps within this temperature regime, offering a robust and broadly applicable workflow for complex forming optimization.

This paper investigated the high-temperature oxidation behavior of gas-atomized CoCrFeNiCu high-entropy alloy (HEA) powders at 800-1000 degrees C via techniques including SEM, XRD, and TEM. The results indicated that the oxidation kinetics of HEA powders is highly sensitive to temperature and the oxidation kinetics undergo a tripartite evolution through distinct phases: initially following a power function law, transitioning to a logarithmic law, and culminating in a linear law with temperature rising. The oxide growth patterns shift from external oxidation to internal oxidation. Reducing the powder particle size accelerates the oxidation rate and promotes more thorough oxidation. Multilayered oxides form on powder surfaces and interpenetrate to form continuous oxide scales between adjacent particles.