Invar alloys, known for their extremely lowlinear expansion coefficient and excellent soft magnetic properties, have been extensively applied in precision optics, microelectronics, magnetic shielding and aerospace industries. Ultra-thin Invar alloy strip products are focused, as they are regarded as essential for high-end applications such as fine metal masks and precision electro-mechanical components. The state-of-the-art fabrication techniques, including electroforming, precision cold rolling and subsequent surface-quality enhancement processes, are systematically summarized with a comparative discussion of their manufacturing mechanisms, technical advantages and existing limitations. Moreover, key performance optimization strategies such as texture tailoring, annealing parameter control, pulsed-current-assisted treatment and hydrogen-based annealing are comprehensively reviewed to elucidate the underlying strengthening and soft-magnetic enhancement mechanisms of Invar alloy strip.Researchers are paying increasing attention to the critical role of high-purity alloys in ensuring surface defect-free and dimensional stability in ultra-thin products, which has now become a key bottleneck.Overall, the findings reveal that precise control of process parameters, high-cleanliness smelting, and multi-performance synergistic optimization is the key to enabling superior ultra-thin Invar alloys.

In the KR hot metal pretreatment process, the vortex distribution formed by the rotation of the stirring paddle exerts a significant influence on desulfurization efficiency. To enhance the dispersion degree of desulfurizer and thus improve desulfurization efficiency, a three-dimensional numerical model is established to systematically investigate the three-dimensional distribution characteristics of the vortex at the top of the hot metal ladle and the multiphase flow field distribution rules inside the hot metal ladle under different stirring parameters. The accuracy of the established three-dimensional numerical model is verified by the measurement results of the water model. Results indicate that whether the bottom of the vortex reaches the top of the stirring paddle is a key factor affecting the flow pattern inside the hot metal ladle and the dispersion degree of desulfurizer. The fluid velocity inside the hot metal ladle increases with the rise in stirring paddle rotation speed, but the proportion of the dead zone at the bottom of the stirring paddle cannot be completely eliminated merely by increasing the rotation speed. The turbulent kinetic energy dissipation rate of hot metal is proportional to the square of the rotation speed. When the rotation speed is higher than 90 r/min, the turbulent kinetic energy dissipation rate is proportional to the immersion depth of the stirring paddle; when the rotation speed is lower than 90 r/min, the turbulent kinetic energy dissipation rate shows no obvious change with the increase in immersion depth. Based on the relational expressions among rotation speed, immersion depth and turbulent kinetic energy dissipation rate, as well as the relational expression between turbulent kinetic energy dissipation rate and vortex depth, a calculation formula for the critical rotation speed at which the bottom of the vortex reaches the stirring paddle under different immersion depthsis derived. This calculation relational expression of critical stirring parameters can provide theoretical guidance for matching reasonable rotation speed and immersion depth of the stirring paddle, thereby realizing the improvement of desulfurization efficiency.

Against the backdrop of the low-carbon transition in the iron and steel industry, double challenges including energy consumption imbalance and slag cost out-of-control are confronted in converter steelmaking with a high scrap ratio. To address the problems of unstable slag addition control and large energy consumption calculation deviation in 120 t converters under high scrap ratio conditions, the thermal-material-oxygen coupling relationship during converter steelmaking is analyzed, and the intrinsic correlation mechanism among molten pool heat demand, slag consumption and thermal compensation under high scrap ratio conditions is clarified. Key production data from 1 200 heats are integrated through data preprocessing, and an integrated prediction and optimization system for the optimal slag addition amount, which combines mechanism models and intelligent algorithms, is established. Eight key characteristic parameters such as molten steel weight and hot metal silicon content are screened out by means of Pearson correlation analysis combined with recursive feature elimination algorithm, and comparative and optimization studies are carried out on BP neural network, PSO-BP and GA-BP models. The results show that the GA-BP model exhibits the optimal performance, with the mean absolute percentage error of 0.13% and the root mean square error of 208.03 for slag addition amount prediction. The model has been successfully applied in the production site with favorable prediction effects, and effective technical support can be provided for the green and efficient production of converter steelmaking with a high scrap ratio.

To address the insufficient prediction accuracy of silicon element yield in electric arc furnace steelmaking and the proneness of the traditional grey wolf optimizer(GWO) to local optima, a chaotic dynamic grey wolf optimizer(CDGWO) is proposed and an integrated prediction model is developed by integrating it with an auto-encoder(AE). Firstly, the AE is employed to reconstruct smelting data features and denoise them. Subsequently, the CDGWO algorithm is designed. Tent chaotic mapping is used for population initialization to enhance global search capability; a nonlinear convergence factor is formulated; a δ-wolf levy flight mechanism is introduced to enable escape from local optima during stagnation phases; and an adaptive leadership election mechanism based on historical performance and recent progress is established. Based on five base models of logistic regression, support vector machine, multi-layer perceptron, random forest and light gradient boosting machine, CDGWO is utilized to optimize the integration weights. Experimental results demonstrate that the CDGWO integrated model achieves a mean absolute percentage error of 11.28% on the test set, which is 1.03% lower than that of the original GWO integrated model. Shapley additive explanation interpretability analysis identifies that temperature, aluminum content, carbon content and manganese content are core influencing factors. Temperature and carbon content exert a negative effect on the yield, while aluminum and manganese contents show a significantly positive effect.

Thermophysical parameters of continuous casting slabs are key factors determining the prediction accuracy of continuous casting solidification processes. At present, the calculation of most thermophysical parameters is performed using the average cooling rate method, which fails to take into account the actual working conditions where cooling rates at different positions of the slab cross-section are different and vary continuously. In view of this, a microsegregation model integrated with dynamic cooling rates is proposed for the accurate calculation of thermophysical parameters. The solute equilibrium distribution coefficient is modified by introducing the Aziz interface kinetic equation, and the MnS/TiN inclusion precipitation model is integrated to realize the dynamic tracking of thermophysical parameters during the non-equilibrium solidification process. The results show that the cooling rate gradient can broaden the δ/γ phase transformation interval by more than 5 ℃, thus significantly regulating the solute redistribution behavior. Meanwhile, the cooling rate gradient can also change the phase fractions at different positions, thereby leading to spatial distribution differences in specific heat capacity, thermal conductivity and density. This model breaks through the limitations of the traditional fixed cooling rate assumption, and provides theoretical support for high-precision continuous casting solidification simulation and defect control.

In view of problems such as large scale differences, complex textures and difficult identification of tiny defects on the surface of strip steel, which lead to low detection accuracy, an improved detection algorithm named DMI-YOLO based on YOLOv8n is proposed, aiming to enhance the multi-scale feature extraction capability and small target detection accuracy. Firstly, a lightweight feature extraction module called C2f-DWRB is constructed. The perception capability for defects of different scales is enhanced through the introduction of multi-scale dilation-wise residual and dilated reparam block structures. Secondly, a modulation fusion module is embedded into the neck network. Local details and global semantic information are fused by means of an adaptive attention mechanism, thus strengthening the feature expression effect under complex backgrounds. Finally, Inner-EIoU is adopted in the prediction stage to improve the original loss function. The positioning robustness for tiny defects is enhanced through the optimization of the aspect ratio strategy. Experimental results show that the mean average precision of the improved algorithm reaches 80.3% on the NEU-DET dataset, which is 3.5% higher than that of the original YOLOv8n network. Meanwhile, the detection speed is maintained at 84.2 frames per second, with both the model size and computational complexity reduced to a certain extent. The proposed DMI-YOLO algorithm has both high accuracy and real-time performance in the task of hot-rolled strip steel surface defect detection and can meet the requirements of practical industrial applications.

In order to study the high-temperature plasticity of low-temperature resistant H-beam steel used in marine engineering under different strain rates, high-temperature tensile tests were conducted on the Gleeble-3800 thermal simulation test machine for the continuous-casting billets of low-temperature resistant H-beam Q420NE steel for marine engineering applications at two strain rates of 0.01 and 1 s^-1. The variation laws of high-temperature strength, hot plasticity and fracture morphology of irregular-shaped continuous-casting billets were obtained in the temperature range of 600-1 300 ℃. The results showed that when the continuous-casting billets were stretched at a higher strain rate of 1 s^-1, the reduction of area of the specimens increased with the increase in tensile temperature, and the reduction of area was always greater than 65%. When high-temperature tensile tests were conducted at a lower strain rate of 0.01 s^-1, the test steel exhibited a significant third brittle zone, with a temperature range from 600 to 850 ℃, where the reduction of area was always less than 65%, indicating poor hot plasticity in this range. Overall, better hot plasticity could be obtained at higher strain rates. In addition, the overall fracture strength of Q420NE continuous-casting billets under deformation at the strain rate of 1 s^-1 was higher than that of 0.01 s^-1, which was consistent with the fracture morphology.

To investigate the influence law ofdefocusing amount on the microstructure and properties of laser welded joints of 2 mm thick Q235 steel sheets, metallographic microscope, scanning electron microscope, tensile testing machine, microhardness tester and electrochemical workstation were used to systematically characterize and analyze the welded joints. The experimental results showed that with the defocusing amount changing from negative to positive values, the width of the weld zone and heat-affected zone gradually increased. The hardness of the welded joint first increased and then decreased, while the self-corrosion current density and self-corrosion potential first decreased and then increased. The average tensile strength also exhibited a trend of first increasing and then decreasing. When the defocusing amount was 0 mm, the average hardness of the weld zone reached the maximum value of 170.03HV, the average tensile strength was the highest at 299.83 MPa, the self-corrosion current density was the smallest at 1.39×10^-5 A/cm², and the capacitive reactance arc radius was the largest, indicating the optimal corrosion resistance.

High-entropy alloys have demonstrated broad application prospects in industrial manufacturing due to their unique thermodynamic properties.Existing reliable binary thermodynamic data were used in conjunction with the molecular interaction volume model (modified M-MIVM) to further optimize model parameters, and to construct and validate algorithms. The key thermodynamic properties of CoCrFeNi, CoCrFeNiAl, CoCrFeNiMn, and CoCrFeNiAlMn high-entropy alloy solid solutions were predicted, and a thermodynamic database was subsequently established. Theoretically, the phase stability and structurally stable compositions formed under different conditions for CoCrFeNi(AlMn) high-entropy alloys were analyzed.The results show that the predicted thermodynamic properties for the CoCrFe, CoFeNi and CrFeNi alloy systems are in close agreement with literature values, confirming the rationality and reliability of the model and algorithms. Theoretical optimization identified alloy compositions with minimized mixing Gibbs free energy andbest solid-solution phase stability as follows, Co_0.22Cr_0.27Fe_0.19Ni_0.32, Co_0.10Cr_0.05Fe_0.16Ni_0.34Al_0.35, Co_0.20Cr_0.16Fe_0.09Ni_0.30Mn_0.25 and Co_0.08Cr_0.05Fe_0.11-Ni_0.30Al_0.35Mn_0.11. The addition of appropriate amounts of Al or Mn to CoCrFeNi alloys, Al to CoCrFeNiMn alloys or Mn to CoCrFeNiAl alloys effectively reduced the mixing Gibbs free energy and enhanced solid-solution phase stability. Moreover, increasing temperature reduced the Gibbs free energy of the studied systems, thereby improving phase stability. The incorporation of Al and Mn was found to increase the temperature sensitivity of the mixing Gibbs free energy.

To reveal the evolution law of microstructural stability and mechanical properties of the Fe-based wrought superalloy GH2132 under long-term high-temperature service conditions, the microstructural stability and mechanical property evolution of GH2132 during long-term aging at 650 and 700 ℃ (500, 1 500 and 3 000 h) were systematically investigated. The results indicate that aging for 3 000 h did not change the grain size (35-40 μm), while the γ′ phase coarsened from 18 to 50 (650 ℃) and 63 nm (700 ℃), and its coarsening behavior was found to conform to the LSW coarsening theory. With increasing aging temperature and duration, grain boundary MC carbides and Laves phases transformed from discontinuous distributions to continuous chain-like distributions. Under long-term aging at 700 ℃, the η phase was preferentially precipitated at grain boundaries and subsequently grew into the grains as lamellae along specific crystallographic orientations. Mechanical testing showed that after aging at 650 ℃ for 3 000 h, the room-temperature yield strength increased from 930 to 1 106 MPa, while elongation decreased to 22%; the high-temperature strength remained almost unchanged, whereas ductility deteriorated. Creep performance exhibited a monotonic degradation.At 650 ℃/250 MPa, the creep life decreased from 2 835 h (after 1 500 h aging) to 2 486 h (after 3 000 h aging). The time-stress parameter was used to extrapolate the 3 000 h creep strength as 246 MPa, which was reduced by approximately 2.3% compared with that after 1 500 h aging. Microstructure-property correlation analysis revealed that moderate coarsening of the γ′ phase synergistically enhanced strength together with grain boundary strengthening, whereas the presence of η phase at grain boundaries and chain-like distributions of carbides and Laves phase led to reductions in creep performance and ductility.

The efficient management of superalloy data for aeroengines is crucial for improving material selection efficiency, optimizing design processes and ensuring product quality. To address issues with domestic superalloy data, such as fragmentation, poor standard compatibility and insufficient traceability, a systematic management scheme was proposed. By constructing a multi-level material system framework of“material category-application-grade-product form-specification” and integrating a full-process data standard system covering material types, forming processes, heat treatment systems and performance testing, the structured and standardized integration of superalloy data is achieved. In terms of data management, a management mode based on data traceability, version control and multi-link quality control is designed through unique coding to associate data sources, preparation processes and test results, ensuring data traceability and reliability. The results demonstrate thatsuperalloy data system system effectively integrates research and production data, supporting material property retrieval, process optimization and quality monitoring, thereby providing precise data support for aeroengine design, manufacturing and maintenance. Future efforts should focus on expanding data coverage, introducing data mining to extract deeper value, optimizing the system architecture for efficiency and fostering cross-domain data sharing to advance aeroengine technology.

Magnesia castables are critical basic materials in the iron and steel smelting process. To improve the comprehensive properties of magnesia castables and address the problems of resource waste and environmental pollution caused by magnesite tailings, medium-calcined magnesia prepared from magnesite tailings is adopted as the raw material, and SiO₂ and CaO are used as additives to prepare medium-calcined magnesia castables. The influence rules of SiO₂ and CaO on the properties of medium-calcined magnesia castables are investigated from the aspects of sintering property, mechanical property, microstructure and thermal shock resistance. It is shown that the introduction of SiO₂ and CaO increases the liquid phase content in the system and thus promotes the sintering process of the material. Sample No. 6 witha CaO mass fraction of 2% added exhibits the densest structure after calcination at 1 400 ℃, with the bulk density reaching 2.59 g/cm³ and the apparent porosity being 24.4%. With the increase in the contents of SiO₂ and CaO, the room-temperatureflexural strength of the test samples after thermal shock treatment reaches a maximum of 3.98 MPa, which is 161.84% higher than that of Sample No. 0. This phenomenon indicates that the massive formation of forsterite phase and monticellite phase significantly enhances the mechanical properties of the material, thereby improving its thermal shock stability.

Substitution of steel slag for limestone, the conventional desulfurizer, can reduce CO₂ emissions, yet the core challenges lie in improving the sulfur fixation rate of steel slag and realizing proper disposal of desulfurization tailings. It has been demonstrated that the cooling method of molten steel slag affects its mineral phase structure, which in turn is correlated with the sulfur fixation performance and the compositional characteristics of desulfurization tailings. Based on the compositional features of desulfurization products, a strategy of preparing denitration catalysts by using steel slag desulfurization tailings is proposed, and the effects of different cooling methods on the desulfurization performance of steel slag and the catalytic performance of catalysts derived from tailings are systematically compared. Results indicate that quenched steel slag (C-SS) and the catalyst prepared from its desulfurization tailings (C-SS-C) exhibit excellent desulfurization and denitration performance. In terms of desulfurization, compared with naturally cooled steel slag (NC-SS) and slowly cooled steel slag (LC-SS), the desulfurization duration of C-SS is prolonged by 70.0% and 88.9%, respectively, while a desulfurization rate of 90% is maintained. In terms of denitration, the NO removal efficiency of C-SS-C reaches 90%, which is 28.5%, 38.5% and 260.0% higher than those of NC-SS-C, LC-SS-C and the single H₂O₂ system, respectively. Mechanism analysis reveals that metal elements in C-SS are mainly hosted in the unstable glassy phase, a characteristic that facilitates their dissolution during the desulfurization process, thereby significantly enhancing the sulfur fixation capacity. Meanwhile, the iron-containing sulfate formed in the desulfurization process is heterotopically attached to the surface of SiO₂, forming a unique structure that effectively promotes the denitration efficiency of the catalyst. It is verified that quenched steel slag can be successfully used as a substitute for limestone in flue gas desulfurization, with the two key challenges of sulfur fixation rate improvement and desulfurization tailings disposal solved simultaneously.