This study examined the impact of tempering temperature on the microstructure and properties of vanadium (V)-microalloyed medium-carbon bainitic steel. A series of heat treatments were performed on the steel, and the microstructural evolution and mechanical properties were systematically investigated through X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and mechanical testing systems (MTS). The findings revealed that tempering temperature has a significant influence on microstructural changes. Specifically, at 350–450 °C, retained austenite begins to decompose and carbides start to precipitate. At 550–600 °C, bainitic ferrite laths undergo coarsening. Regarding mechanical properties, both tensile strength and yield strength initially increase with tempering temperature before decreasing as the temperature continues to rise. The diffusion and redistribution of carbon atoms during tempering enhance the elongation of all tempered samples compared to their untempered counterparts. Optimal comprehensive mechanical properties are achieved at 450 °C, where precipitation strengthening from vanadium, enhanced stability of retained austenite, and synergistic strengthening effects of decomposition products are most pronounced. This research provides a theoretical foundation for optimizing the heat treatment process of such steels and offers insights into the synergistic effects of V-microalloying and tempering.

A multiphase high-strength steel austempered at 260 °C for 24 h was investigated by quasi-in-situ tensile characterization and EBSD-based crystal plasticity finite element modeling. The experimental observations reveal that local plastic deformation is strongly heterogeneous: von Mises strain concentrates preferentially near bainitic-ferrite packets, phase boundaries, and retained-austenite/martensite–austenite regions, whereas blocky retained austenite contributes to strain accommodation at the early deformation stage. To quantify the underlying stress–strain partitioning, a quasi-two-dimensional representative volume element was reconstructed from EBSD data and implemented in ABAQUS through a user-defined material subroutine. The model contained the real grain morphology, phase distribution, and crystal orientation information of the 24 h austempered specimen. A rate-dependent crystal plasticity constitutive framework with BCC matrix, FCC retained austenite, and transformed martensite branches was calibrated against the macroscopic tensile curve. The simulated tensile response agrees well with the experimental curve before macroscopic instability, and the predicted local fields are consistent with the quasi-in-situ strain maps. The results show that local plastic strain first accumulates in M/A-related regions and phase-boundary-neighboring zones, while high Mises stress migrates dynamically with slip activity and stress-induced martensitic transformation. Retained-austenite transformation increases the local load-bearing capacity, modifies interphase load transfer, and delays the direct linkage of strain-localization bands. The present work clarifies the coupling among retained-austenite stability, TRIP-assisted load redistribution, and microstructural strain partitioning in multiphase high-strength steel, providing a mesoscale basis for microstructure-guided strength–ductility optimization.

Achieving high strength, high toughness, and high plasticity in bainitic steel to meet the needs of economic and industrial development is the direction and driving force for researchers. The reinforcement technology of bainitic steel has become very well developed, with research conducted on microstructure, dislocation density, and alloying elements. While improving strength, some plasticity and toughness are inevitably sacrificed. Therefore, achieving high strength, high plasticity, and high toughness in bainitic steel has always been a research focus. Existing research has shown that pre-transformation before the bainitic transformation can help increase the bainitic transformation rate and thereby regulate the microstructure. This paper will conduct a detailed analysis of the influence of pre-phase transformation microstructure on the strength, toughness and plasticity of bainitic steel.

Against the backdrop of China’s dual-carbon goals—peaking carbon emissions by 2030 and achieving carbon neutrality by 2060—capacity optimization in the steel industry can no longer rely solely on aggregate output reduction. Instead, governance must shift toward a multidimensional approach that combines scale control, structural adjustment, and coordinated regional allocation. This study develops a quantifiable and interpretable assessment model for capacity-adjustment pressure. Monthly provincial crude steel output is used as a high-frequency proxy for capacity utilization and production adjustment. Additive time-series decomposition is applied to extract three components from monthly output—trend, residual, and volatility—which respectively represent structural evolution, short-term deviations, and exposure to shocks. The model further incorporates multidimensional variables, including downstream steel demand, resource and transport constraints, scrap steel ratio, and policy constraints. On this basis, a two-stage hybrid assessment framework is developed. In the first stage, extreme gradient boosting (XGBoost) is used to learn nonlinear relationships and derive data-driven feature importance. In the second stage, a composite pressure index is constructed and transformed into a standardized 0–100 score through a robust rank-based mapping mechanism. Dual thresholds are then used to generate three policy recommendations: maintaining current capacity, structural optimization, and capacity reduction. The results show that production trends and volatility intensity are the primary drivers of capacity-adjustment pressure, while pronounced spatial heterogeneity requires highly localized strategies. The classification assigns 25 provinces to maintaining current capacity, 3 to structural optimization, and 3 to targeted capacity reduction. Finally, integrating SHapley Additive exPlanations (SHAP) enhances model interpretability and provides a quantitative basis for shifting from indiscriminate capacity suppression toward differentiated, region-specific capacity governance, thereby supporting the sustainable low-carbon development of the global steel industry.