15 December 2025, Volume 60 Issue 12

    

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Technical Reviews
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  Prospects for development and application of intelligent continuous casting technologies

  CHEN Wei, HUO Meijie, YANG Gaiyan, ZHU Liguang

  Iron and Steel. 2025, 60(12): 1-14. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250336

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  Driven by China's "dual carbon" strategy, the metallurgical industry is rapidly advancing toward green and intelligent transformation. As a core process in steel production, the level of intelligence in continuous casting significantly influences the overall efficiency, energy utilization, and product quality of the steel manufacturing chain. Recent advances and innovative applications of artificial intelligence （AI） in the continuous casting process are systematically reviewed. Firstly, regarding breakout prediction, the causes and consequences of breakouts are analyzed, and the effectiveness and limitations of AI-based prediction models in enhancing warning accuracy and reducing false alarms are discussed. Secondly, in the domain of secondary cooling dynamic water control, a hybrid approach is proposed, combining genetic algorithms for parameter optimization with deep neural networks to construct a multi-variable control model. This enables intelligent adjustment of water flow and precise local thermal field regulation, effectively reducing thermal stress and crack formation in the plate. To address challenges in plate surface defect detection, the integration of deep learning and machine vision is explored. Convolutional neural networks （CNN） are used to automate defect recognition, classification, and statistical analysis, significantly improving detection precision and efficiency. Moreover, the latest developments in the deployment of casting operation robots are reviewed, focusing on tasks such as mold replacement, temperature sampling, and automatic slag addition in high-risk, labor-intensive scenarios, demonstrating strong potential for intelligent operation. Despite these advances, key challenges hindering intelligent transformation in continuous casting are identified, including the lack of standardized data acquisition protocols, limited generalization capability of AI models under complex boundary conditions, and poor adaptability to extreme casting environments. Therefore, it is imperative to accelerate the development of large-scale industrial data platforms and multimodal sensing technologies to realize intelligent perception, prediction, and control throughout the continuous casting process. The result of study aims to provide strong technical support for the steel industry in achieving smart manufacturing goals characterized by zero defects, self-adaptation, and ultra-low carbon emissions.
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  Research progress on motion of inclusions in steel during unsteady continuous casting process

  QU Tianpeng, ZHANG Zhixiao, WANG Deyong

  Iron and Steel. 2025, 60(12): 15-28. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250361

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  During steady casting, the flow and temperature field inside the tundish and mold are in dynamic equilibrium. While unsteady processes such as casting start, ladle change, and casting end are unavoidable, disturbances in the flow field can have adverse effects on the removal of inclusions. With the increasing cleanliness requirements for high added value steel, the cleanliness of molten steel and the migration behavior of inclusions in unsteady casting processes have become key factors restricting product quality. The unsteady process causes severe fluctuations in the flow and temperature fields, leading to steel reoxidation, slag entrainment, and obstruction of inclusions floating up, significantly increasing the inclusion content in the first slab, transition slab, and last slab. A large number of unsteady process slab are downgraded or even scrapped, significantly increasing production costs. A systematic review is conducted on the migration behavior of non-metallic inclusion particles in molten steel in typical metallurgical reactors during the unsteady process of continuous casting. The sources and migration behavior of inclusions in the unsteady process are summarized, as well as their impact on the cleanliness of castings. By integrating numerical simulations, physical experiments, and industrial testing data, the three-dimensional distribution pattern of inclusions are systematically revealed and key control technologies are extracted, which provides theoretical support for accurately defining the range of unsteady slab and reducing degradation and scrap rates. The existing control technology can improve the impact of unsteady processes on the cleanliness of molten steel, but there are still problems such as insufficient model accuracy, poor universality of technical solutions, and scarce real-time monitoring and dynamic control capabilities. The combination of multi-physics mechanism and intelligent control technology will be the future trend.
Raw Material and Ironmaking
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  Edge multi-foot coke particle detection based on improved RTDETR

  ZHANG Xuefeng, QIN Jiyang, LONG Hongming, XIA Qin, YU Zhengwei

  Iron and Steel. 2025, 60(12): 29-40. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250388

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  Given the problems of complex image noise, low separation between coke powder and background, and blurred images collected on the spot in the detection of fuel coke powder in metallurgical industry, it is difficult to accurately detect the particle size. A coke powder detection model ESGE-RTDETR （edge-sparse graph-enhanced efficient real-time detection transformer） based on the improved RTDETR algorithm was proposed, which can efficiently and accurately detect the coke powder particle size in coke powder detection scenarios. The MutiScaleEdge multi-scale edge convolution module combined with the ConvEdgeFusion edge feature fusion module was proposed to obtain feature maps with different dimensions of information. Windowed attention and dynamic adaptive sparse attention were used to optimize the calculation complexity. The neck feature was fused through the CSP-MSF（cross stage partial multi-scale fusion） fusion module, and finally the coke powder detection results were obtained by inputting the detection head. In order to improve the training accuracy, combining the characteristics of PowerIoU and FocalerIoU, FocalPowerIoU was proposed to replace the original GIoU, which made the training faster convergent and stable, and improved the accuracy of the model. Enhanced the interpretability of the model detection process by visualizing the feature extraction points and regions focused by the model. In the actual production process, adaptive histogram equalization （contrast limited adaptive histogram equalization,CLAHE） was selected to enhance the image after experimental comparison in the preprocessing stage of detection, highlighting the edge characteristics of coke powder, providing stable input for model detection, and improving the comprehensiveness and accuracy of model reasoning results through CLAHE image enhancement. The experimental results on the coke powder image data set of a steel plant show that the ESGE-RTDETR model has a better effect on improving the recognition accuracy of coke powder multi-scale particle size compared with the mainstream target detection model. Compared with the original RTDETR model, the mean average precision（P_mA50） has increased by 20.6 percentage points, and the recall rate has increased by 14.1 percentage points. Compared with the mainstream detection model YOLOv8, the accuracy rate of P_mA50 has increased by 8.9 percentage points, and the recall rate has increased by 8.5 percentage points. It can provide technical support for on-site production and industrial closed-loop control of coke powder particle size. The actual production verification of a steel plant meets the requirements of production detection accuracy and speed.
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  Hydrogen reduction behavior of internally mated biomass vanadium-titanium magnetite pellets

  WAN Xinyu, HONG Lukuo, CHEN Jiansong, XU Ying, TONG Shuai

  Iron and Steel. 2025, 60(12): 41-48. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250365

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  Aiming at the bottlenecks of traditional vanadium-titanium-magnetite smelting process, such as high carbon emission and low resource utilization, a green metallurgical process was proposed utilizing H₂ reduction of internally mated biomass vanadium-titanium magnetite pellets. A test of H₂ reduction of vanadium-titanium magnetite pellets with internal biomass at 1 100 ℃ was carried out to systematically investigate the effects of H₂ volume fraction （30%,40%,60%） and reduction time （20,30,40,50,60 min） on the reduction effect of the pellets as well as the changes in the microscopic morphology of pellet, and compared with that of the original ore pellets. The results show that the composite pellets containing biomass improve gas diffusion efficiency by altering their pore structure. Under 30% H₂（volume fraction） conditions, they achieve the same reduction effect as the original ore pellets under 40% H₂ volume fraction conditions. When the H₂ volume fraction is increased to 60%, the metallization rate of composite pellets reaches 94.58%, and titanium ore residues are eliminated, confirming that 40%Ar-60%H₂ is the optimized process condition for pellet deep metallization. The internally mated biomass significantly optimizes the reduction kinetics of composite pellets, continuously accelerating the metallization process during the critical reduction period of 20,30,40,50,60 min. By enhancing the reduction atmosphere, reducing activation energy, and improving diffusion pathways, composite pellets achieve the same high metallization rate （approximately 96%） at least 10 min earlier than original ore pellets, significantly shortening the reduction cycle and reducing reduction atmosphere consumption. The composite pellets form a porous honeycomb-like iron matrix, exhibiting 22.68% increase in BET（Brunner-Emmet-Teller）specific surface area compared to the original ore pellets, with rough surface structure expanding the gas-solid contact area. The increased contribution of medium/large pores doubles the average pore size, providing diffusion pathways for the directed migration of iron atoms and promoting the deep reduction and aggregation of titanium iron oxides （disappearance of the FeTiO₃ phase）, synergistically achieving diffusion-reaction kinetic optimization.
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  Optimization of cold-bonded process for zinc extraction tailings carbon-containing pellets via response surface methodology

  LI Junguo, WAN Guohao, ZHEN Changliang

  Iron and Steel. 2025, 60(12): 49-59. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250387

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  The cold strength of carbon-containing pellets plays a critical role in transportation efficiency and smelting process permeability,directly impacting industrial production stability and economic viability. Zinc extraction tailings,which are secondary solid wastes generated after the pyrometallurgical recovery of zinc from zinc-containing dusts,have garnered increasing attention in industrial research due to their potential for resource recovery and utilization. A method was devised to produce carbon-containing pellets by utilizing zinc tailings,iron concentrate powder,and semi-coke,aiming to lower smelting expenses and improve the efficiency of solid waste resource utilization. The compressive strength of green pellets was selected as the response variable,with moisture mass fraction,binder ratio,and forming pressure identified as key process parameters. Response surface methodology（RSM）was employed to optimize the cold consolidation process for zinc tailings-based carbon-containing pellets. The results demonstrate that moisture mass fraction（A）and forming pressure （C）exert statistically significant positive effects on compressive strength. Optimal moisture enhances feedstock plasticity and promotes particle adhesion. Meanwhile,higher forming pressure increases particle contact density,thereby improving structural stability. Although the effect of binder ratio（B）alone did not reach a significant level,its interaction with moisture content exhibited a significant synergistic effect. The experimental analysis results led to the development of a binomial model to predict the compressive strength of carbon-containing pellets. The optimal process parameters for the cold consolidation of these pellets were determined to be a moisture mass fraction of 4.67%,a binder ratio of 5.51%,and a forming pressure of 26.98 MPa. The results confirmed the accuracy and reliability of the model,showing deviations in compressive strength of less than 2% from the predicted values. This systematic optimization offers reliable theoretical basis and guidance of high-performance metallurgical raw materials derived from solid waste resources.
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  Optimization analysis of key constituents and slag properties in titanium slag smelted from vanadium-titanium magnetite

  YANG Shuangping, DONG Zhenyu, WANG Miao, LIU Qihang, DONG Jie, LU Lu, ZHAO Shuanghe

  Iron and Steel. 2025, 60(12): 60-73. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250403

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  Vanadium-titanium magnetite is widely distributed globally with abundant reserves. Vanadium and titanium are key metal elements in aerospace, electronic information, high-end manufacturing, new energy, new materials and other fields, and their development value in metallurgy and material industry is extremely important. However, in the traditional process smelting process based on the blast furnace-converter method, the blast furnace slag is often accompanied by a high content of titanium nitride and titanium carbide. These high melting point compounds not only easily lead to the increase of blast furnace slag viscosity in the furnace, but also lead to bad phenomena such as iron content in the slag and accumulation of the hearth, which affect the normal production. Vanadium-titanium magnetite provided by Heilongjiang Jianlong Company was used as raw material. Firstly, its physical and chemical properties and composition were characterized and analyzed, and relevant experiments were designed to explore the evolution law of melting performance in slag. At the same time, the specific effects of alkalinity and w（MgO）/w（Al₂O₃） on melting performance were further studied. The results show that when the mass fraction of TiO₂ increases from 11% to 14%, the softening temperature, hemispherical temperature and flow temperature of slag reach 1 245, 1 255 and 1 267 ℃, respectively. With the increase of alkalinity from 1.1 to 1.4, the three temperature indexes also show an increasing trend, which are 1 240, 1 247 and 1 259 ℃ respectively when the alkalinity is 1.4. With the increase of w（MgO）/w（Al₂O₃） from 0.5 to 0.9, the slag softening, hemispherical and flow temperatures decrease significantly, with the lowest values of 1 208,1 222 and 1 238 ℃, respectively. In terms of viscosity, the change of TiO₂ content has little effect on it. The increase of alkalinity can effectively reduce the viscosity. The w（MgO）/w（Al₂O₃） is the most sensitive to the viscosity, the viscosity decreases significantly from 0.5 to 0.9, and the downward trend slows down when it continues to rise to 1.1. It provides a theoretical basis for optimizing the vanadium-titanium ore smelting process and inhibiting the adverse effects of TiN and TiC.
Steelmaking
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  Multi-model comparison for converter oxygen consumption based on isolation forest anomaly detection

  WANG Jianhao, FANG Qing, LI Yiming, LU Pengsheng, ZHANG Hua, NI Hongwei

  Iron and Steel. 2025, 60(12): 74-87. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250344

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  Oxygen consumption in basic oxygen furnace （BOF） steelmaking is governed by multiple interrelated factors, including hot metal composition, temperature, alloy additions, and operational fluctuations. Accurate prediction of oxygen consumption is essential for optimizing thermal balance, ensuring final steel quality, and facilitating green and efficient production. Although data-driven models have been widely employed in this context, the presence of outliers in industrial data can degrade model robustness and generalizability. Six representative data-driven models,SVM （support vector machine）, RF （random forest）, RBF （radial basis function network）, CNN（ convolutional neural network）, ELM （extreme learning machine）, and LSTM（long short-term memory） were comparatively evaluated for their performance in predicting BOF oxygen consumption. The LSTM model exhibited superior overall accuracy, with 95.41% of test samples showing absolute prediction errors less than 5%, outperforming the other models. To further improve model stability, an isolation forest algorithm was introduced to identify and remove outliers from both oxygen consumption and relevant process variables. Outlier removal significantly reduced fluctuations in key parameters such as temperature and composition, thereby enhancing the models' ability to learn dominant trends. Post-cleaning analysis indicates that all models achieved improved prediction accuracy, particularly the RBF and ELM models, which are more susceptible to data irregularities. The LSTM model further benefites from reduced extreme deviations and more compact error distribution, reinforcing its predictive stability. The integrated framework combining outlier detection and multi-model evaluation enhances the accuracy and robustness of BOF oxygen consumption prediction. These findings offer practical insights for intelligent process control and low-carbon optimization in BOF steelmaking operations.
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  Characteristics and formation mechanism of 20MnCrS5 gear blank surface bright line defect

  DENG Feng, CHENG Guoguang, LI Yao, PENG Feng

  Iron and Steel. 2025, 60(12): 88-99. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250375

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  After the cutting process of 20MnCrS5 gear steel produced by a steel plant, obvious bright line defects are found on the surfaces of several gear blanks, which are mainly caused by inclusions. SEM （scanning electron microscopy） and EDS （energy-dispersive spectroscopy） were used to identify the basic characteristics of inclusions at the defect sites, such as their morphology and composition. By sampling during the steelmaking process of 20MnCrS5 steel, analyzing the slag composition at different stages and the morphology and composition of inclusions in steel samples, and combining thermodynamic calculations, the evolution of inclusions during steelmaking was analyzed to determine the formation mechanism of defect-causing inclusions. The results show that the defects on gear blanks were primarily large-sized CaO-MgO-Al₂O₃ inclusions, with the maximum size exceeding 200 μm. These inclusions contain no SiO₂, exhibit a uniform distribution of CaO and Al₂O₃, and have locally concentrated MgO, this type of large-sized inclusions is formed by the agglomeration of numerous small-sized CaO-MgO-Al₂O₃ inclusions. The inclusions originate from the reaction of abundant Al₂O₃ inclusions originally present in the molten steel with Mg and Ca during steelmaking. Such inclusions mainly exist in liquid state at high temperatures, making them difficult to float and remove, thus remaining in the molten steel. Small-sized CaO-MgO-Al₂O₃ inclusions, after passing through the nozzle along with the molten steel, gradually precipitate solid phases during the subsequent temperature drop and solidification process. These solid phases adhere to each other due to the effect of cavity bridge force and complete sintering within a short time after contact. Such small-sized inclusions collide and agglomerate in this way, eventually forming large-sized aggregated inclusions. To reduce the formation of such large-sized inclusions, the cleanliness of molten steel needs to be further improved. The slag composition should be adjusted to enhance its ability to absorb Al₂O₃ inclusions in the molten steel,and the feeding quality of calcium wire during Ca treatment should be reasonably controlled to minimize the formation of liquid CaO-MgO-Al₂O₃ inclusions. These research results are of great significance for addressing the surface defect issue of 20MnCrS5 gear blanks and further enhancing the product quality of 20MnCrS5 steel.
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  Effect of Ce on modification of inclusions and refinement of solidification structure in 700L steel

  SHI Chao, WANG Yuhang, LIU Peng, YANG Weiyu, TANG Haiyan, YANG Jichun

  Iron and Steel. 2025, 60(12): 100-110. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250407

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  The 700L high-strength large beam steel, which is a key component for bearing the weight of vehicle body and external loads, must has excellent product performance and requires a high level of cleanliness for molten steel. The hard inclusions such as Al₂O₃, Ca-（Mg）-Al-O present in the steel are difficult to deform during the rolling process and their improper control can cause cracking during stamping and bending of the steel plate. The rare earth element, represented by Ce, has high reactivity and can transform the inclusions in the steel into rare earth inclusions, reducing the harm caused by large-sized spherical inclusions. Moreover, the rare earth inclusions in the steel have a lower degree of misfit and can serve as hetero nucleation cores to refine the solidification structure of casting billet. The results show that when the mass fraction of rare earth Ce in the steel is 0.001 3%, the spherical inclusions are refined, with the number per unit area decreasing from 22 to 11 and the maximum size reducing from 11 μm to 6 μm. The number and size of TiN-like inclusions remain unchanged. The rare earth Ce transforms Al₂O₃, Ca-（Mg）-Al-O inclusions in the steel into Ce-Al-O inclusions, and the degree of transformation depends on the local Ce content. The transformed Ce-Al-O inherits the morphological characteristics of original inclusions in the steel. The morphology of TiN changes, presenting a brittle structure, which is conducive to alleviating stress concentration. Based on FactSage thermodynamic calculations, when no rare earth Ce is added, the steel liquid composition is in the non-ideal phase region （liquid+slag+CaAl₄O₇）, and after adding rare earth Ce, the steel liquid enters the liquid+slag+AlCeO₃ phase region. The rare earth transforms the deoxidation products and calcium-aluminate inclusions into Ce-Al-O inclusions, which is consistent with the SEM（scanning electron microscopy） observation results. The mismatch degree of Ce-Al-O in ferrite steel is less than 8%, which promotes the solidification nucleation of the steel. The equiaxed grain zone of slab is expanded, the dendrite is refined, and the primary dendrite spacing is reduced from 426 μm to 280 μm.
Metal Forming
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  NSGA-III-based hot rolling batch planning with constraint and path optimization

  LI Shaobin, ZHANG Yongjun, XIAO Xiong, SUN Yanguang, GU Jiachen

  Iron and Steel. 2025, 60(12): 111-124. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250475

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  In steel manufacturing, the quality of the hot rolling plan directly impacts production efficiency, costs, and delivery schedules. To address the limitations of existing models, such as incomplete objective coverage and ineffective resolution of multi-objective conflicts, the multi-objective hot rolling batch planning problem was formulated as a prize-collecting vehicle routing problem （PCVRP）. An improved non-dominated sorting genetic algorithm III （NSGA-III）, incorporating constraints and path optimization, was proposed to solve this problem. The model utilized virtual slabs from continuous casting and physical inventory slabs as inputs, considering key factors including attribute changes between adjacent slabs, rolling unit length, total batch plan length, and the proportion of hot slabs and constructs optimization evalution system combing three core evalution values with comprehesive evaluation score. The algorithm initialized the population using a hybrid strategy of constraint satisfaction and a path nearest-neighbor pool to enhance initial solution quality while maintaining diversity. Novel crossover and mutation operators, integrating model constraints with path optimization, were designed to accelerate convergence and avoid local optima. Through the synergistic design of the model and algorithm, an effective balance among conflicting objectives and efficient problem-solving were achieved. Experimental results based on real-world production data from a steel plant demonstrate that the proposed algorithm outperforms MOEA/D（multi-objective evolutionary algorithm based on decomposition）, NSGA-II, and GA（genetic algorithm）, with improvements in the comprehensive evaluation value of 2.3%, 5.1%, and 35.4%, respectively. Furthermore, the comprehensive evaluation value of the initial solution is optimized by 57.5% during the iterative process, confirming that the proposed model and algorithm significantly enhance the efficiency and quality of hot rolling batch planning.
Materials
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  Effect of Si content and heating temperature on oxidation behavior of low-carbon steels

  ZENG Wu, TIAN Junyu, PANG Houjun, ZHENG Wanjie, WANG Yunfeng, XU Guang

  Iron and Steel. 2025, 60(12): 125-137. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250373

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  To improve the surface quality of low-carbon steel and address defects caused by incomplete removal of iron oxide scale, the microstructure and formation mechanism of oxide scales on low-carbon steels with different Si contents during high-temperature oxidation were investigated by using FE-SEM （field emission scanning electron microscopy） and EDS （energy dispersive spectroscopy）. It focused on elucidating the effects of temperature and Si content on oxidation behavior. The results show that the oxide scales mainly consist of Fe₂SiO₃, Fe₃SiO₄, FeO and an internal oxidation layer containing SiO₂2SiO₄ phase. At heating temperature of 1 050 ℃, the phase of Fe₂SiO₄ appears as finely dispersed particles, and the oxide-scale/substrate interface remain relatively flat. However, when the heating temperature is 1 170 ℃, the Fe₂SiO₄ phase transforms into continuous dendritic or network-like structures, significantly deteriorating interface flatness. Moreover, the influence of Si content on oxidation weight gain exhibits temperature dependence. At heating temperature of 1 050 ℃, the steel with high Si content promotes the formation of solid Fe₂SiO₄, which could effectively hinder the diffusion of iron and oxygen ions, thus inhibiting the oxidation process. In contrast, at 1 170 ℃, the formation of Fe₂SiO₄-FeO eutectic liquid phase provides a faster channel for atomic and ionic diffusion in oxidation reaction, thus accelerating the oxidation process. Additionally, the eutectic liquid phase tends to infiltrate into the matrix and FeO, forming anchor and/or grid shape with it, pinning the grain boundary of the matrix, strengthening the bonding between the oxide scale and the matrix, and making the peeling of the iron oxide scale more difficult. Based on this, process and chemical composition optimization are proposed, when the content of Si in steels is relative high, the heating temperature should be controlled below 1 170 ℃ to suppress the formation of Fe₂SiO₄-FeO eutectic liquid phase, thereby improving surface quality and reducing iron loss. The intrinsic relationship among temperature, Si content and oxidation behavior is clarified, providing theoretical foundation and process guidance for surface quality control in hot-rolled low-carbon steel production.
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  Microstructure and fracture toughness analysis of 500 MPa grade high crack resistance toughness wind tower steel

  JIA Xiaohang, CHANG Jiandong, LIU Zhongzhu, GUO Aimin, MA Heng, HE Kang, WANG Zhongxue, WU Huibin

  Iron and Steel. 2025, 60(12): 138-147. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250359

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  As the wind power industry rapidly develops, the installed capacity of wind turbines continues to increase, with individual turbine units becoming progressively larger, placing more stringent demands on the scalability and high performance of wind power equipment. To meet the critical requirements for high strength, low-temperature fracture toughness, and fatigue crack arrest ability of steel used in wind tower structures, a 500 MPa grade high crack resistance toughness wind tower steel was developed through low-carbon microalloying and the application of TMCP （thermo-mechanical controlled processing）. The microstructure of the steel primarily consists of uniformly fine ferrite and granular bainite, with an average grain size of 3.57 μm. The fraction of low-angle grain boundaries （3°-15°） is 43.5%, while the fraction of high-angle grain boundaries （>15°） is 56.5%. The material exhibits excellent mechanical properties, with a yield strength of 580 MPa, a tensile strength of 689 MPa, and an elongation of 19.36%. At -80 ℃, the impact energy reaches 257 J, and at -40 ℃, the CTOD （crack tip opening displacement） value is 0.604 mm, demonstrating outstanding low-temperature toughness and crack arrest performance. Microstructural analysis reveals that the presence of polygonal ferrite significantly enhances the material's low-temperature toughness, while a small amount of granular bainite contributes to the strength. The refined grain size improves the material's strength, and the high fraction of high-angle grain boundaries effectively inhibits crack propagation, further enhancing the low-temperature toughness and crack arrest capabilities of the material. Provide a theoretical basis for the practical application of high-performance steel for wind power.
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  Characteristics of residual ferrite and solidification mode in 12.5% nickel 316L stainless steel continuous casting billet

  XUE Zhixuan, CHEN Chao, MA Hui, LI Yafeng, HOU Dongzhi, CHEN Lei, YANG Kun, MU Wangzhong

  Iron and Steel. 2025, 60(12): 148-159. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250419

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  The residual ferrite in austenitic stainless steel significantly impacts its service performance, with its characteristics primarily influenced by composition, cooling rate, and solidification mode. The distribution characteristics of residual ferrite and precipitated phases along the width direction of a continuous-cast 12.5% nickel 316L austenitic stainless steel billet was investigated. Characterization was performed using metallographic analysis, electron back-scatter diffraction （EBSD）, and electron probe microanalysis （EPMA）. Solidification mode was determined based on residual ferrite morphology, Thermo-Calc thermodynamic calculations, chromium/nickel equivalent empirical formulas, and high-temperature laser scanning confocal microscopy （HT-CLSM） experiments. The results indicate that the ferrite volume fraction along the centerline thickness direction of the billet width exhibits an "A"-shaped distribution. The surface region shows the lowest residual ferrite volume fraction （4.14%）, while the center region has the highest （8.99%）. The calculated cooling rate decreases from 7.60 °C/s at the billet surface to 0.38 °C/s at the center. Regarding morphology, in the surface fine-grained zone （≤20 mm from surface）, granular and parallel short-rod ferrite are formed. In the columnar grain zone （20-60 mm）, ferrite morphology evolves from skeletal→lath-like→vermicular. In the central equiaxed grain zone （>60 mm from the surface）, dense lath-like and clustered vermicular structures are formed. EBSD and EPMA results reveal that partial transformation of δ-ferrite to σ/chi phases occurs at subsurface of the billet. In the billet center region, the δ→σ+γ₂ eutectoid reaction leads to σ-phase precipitation within the austenite grains. Concerning solidification mode, both results of Thermo-Calc thermodynamic calculations and empirical chromium/nickel equivalent formulas predict an AF （austenitic-ferritic） mode. However, in-situ HT-CLSM observation shows skeletal δ-ferrite preferentially precipitating at 1 392.6 ℃, followed by austenite growing interdendritically at 1 386.5 °C. This sequence （L→L+δ→L+δ+γ→δ+γ） aligns with an FA （ferritic-austenitic） solidification mode. Features such as ferrite enveloping austenite in the billet and the δ→σ+γ₂ eutectoid decomposition are characteristic of FA mode. A discrepancy thus exists between the solidification mode predicted by thermodynamic calculations and empirical formulas and the mode observed experimentally. It aims to provide theoretical guidance for the control of ferrite in the production of 12.5% nickel 316L stainless steel continuous casting billet.
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  Influence of heat treatment on microstructure and mechanical properties of GH4151 alloy

  TANG Chao, SONG Guanjun, QU Jinglong, DU Jinhui, ZHANG Ji

  Iron and Steel. 2025, 60(12): 160-169. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250511

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  GH4151 alloy is a difficult-to-deform nickel-based superalloy capable of serving at temperatures up to 800 ℃. This alloy features a high degree of alloying, with the γ′ strengthening phase accounting for 50%-60% of its mass fraction. Not only are its manufacturing processes, such as smelting and cogging, highly challenging, but its properties are also notably sensitive to heat treatment parameters. Current research on GH4151 alloy primarily focuses on smelting process control, cogging forging optimization, and the relationship between hot-working parameters and microstructural homogeneity. In contrast, studies on the heat treatment of GH4151 are relatively scarce, particularly regarding the influence mechanisms of solution and aging treatments on microstructure and properties.It investigated the nickel-based superalloy GH4151, which could operate at temperatures up to 800 ℃. Using double aging heat treatment （850 ℃×6 h+760 ℃×16 h） under both sub-solvus （1 130 ℃） and super-solvus （1 170 ℃） solution conditions, combined with optical microscopy, scanning electron microscopy, and selected area electron diffraction analysis via transmission electron microscopy, the grain size distribution, evolution of primary and secondary γ′ phases, and precipitation behavior of grain boundary phases were systematically examined under different heat treatment parameters. Furthermore, through a series of tensile tests at room and elevated temperatures, the effect of heat treatment on the mechanical properties of GH4151 alloy was thoroughly investigated.The results indicate that the solution temperature significantly influences the dissolution behavior of the primary γ′ phase and the grain size distribution. After sub-solvus treatment, a certain amount of undissolved large-sized primary γ′ phase remains, which pins the grain boundaries and effectively inhibits grain growth, resulting in fine-grained microstructure. In contrast, super-solvus treatment leads to complete dissolution of the primary γ′ phase, resulting in rapid grain growth and coarse-grained structure.The double aging heat treatment promotes further precipitation of the secondary γ′ phase, thereby enhancing the tensile strength of the alloy at room temperature, 650 ℃ and 750 ℃, as well as the room-temperature hardness. However, the size and distribution of the secondary γ′ phase vary with different solution treatments. Moreover, since the aging temperature falls within the precipitation range of grain boundary μ phase and M₂₃C₆ carbides, extensive co-precipitation of these phases occurs along the grain boundaries. In particular, the precipitation of the brittle and hard μ phase leads to a reduction in tensile strength at 800 ℃.
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  Effect of Al on high temperature oxidation behavior of high-Mn high-Al steel

  LIU Zijia, SONG Mingming, LI Zaoyu, YANG Chunhua, LI Jianli, ZHU Hangyu, PENG Hongbing

  Iron and Steel. 2025, 60(12): 170-183. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250390

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  The scale formation characteristics are the basis of descaling process. In order to clarify the difference between descaling process of high-Al low-density steel and TRIP/TWIP steel, the differences of oxidation process between high-Mn high-Al steels with Al mass fraction of 1% and 11% were compared at 850, 1 000 and 1 250 ℃. The results show that all the oxidation process of the two steels at 3 temperatures were under the control of diffusion process, which satisfied the parabolic law, but the oxidation weight gains were quite different. The weight gain of 11%Al steel after 25 h oxidation was much less than that of 1%Al steel. The oxidation activation energy of 1%Al steel was 95.61 kJ/mol within 25 h. The oxidation process of 11%Al steel could be divided into two parabolic stages, the weight gain was significant at [0, 2） h after oxidation, and decreased rapidly at [2, 25] h after oxidation. The activation energies of oxidation for 11%Al steel were 24.11 and 27.44 kJ/mol in [0, 2） h and [2, 25] h respectively. There was a great interface difference between scale and steel matrix for two experimental steels. The interface between scale and matrix of the 1%Al steel was straight, and the scale would remain intact during cooling. While the interface between scale and matrix of 11%Al steel was tortuous, its outer layer and a small amount of intermediate layer would fall off by self-pulverization during cooling. Both the scales of the two experimental steels had a three-layer structure. The scale of the 1%Al steel was manganese-rich oxide, iron-manganese oxide and manganese-iron oxide containing Al₂O₃ in turn from outside to inside. Whereas the outer layer of oxide scale of 11%Al steel was manganese-iron oxide, the middle layer was manganese-aluminum oxide, and the inner layer was aluminum-rich oxide. There was a discontinuous thin Al₂O₃ enrichment layer in the inner layer of the scale of 1%Al steel, which had high flatness but small thickness. While the Al₂O₃ layer in the scale of 11%Al steel was dense and continuous, and it was obviously thicker than that of 1%Al steel, but its flatness was reduced and its interface was curved. The research results are of significant guiding to the formulation of hot rolling descaling process for high-Al low-density steel.
Environmental Protection and Energy
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  Comparison of energy efficiency and carbon emission characteristics of blast furnace and shaft furnace ironmaking

  WANG Zhen, ZHENG Haiyan, ZHANG Yan, CHEN Ruizhang, SHEN Fengman, JIANG Xin, GAO Qiangjian

  Iron and Steel. 2025, 60(12): 184-196. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250347

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  Based on the first and second laws of thermodynamics, classical energy analysis models and grey-box exergy analysis models for the BF（blast furnace） and SF（shaft furnace） smelting processes were established respectively. Employing evaluation indicators such as thermal efficiency and exergy efficiency, it systematically analyzed the differences in energy utilization between BF and SF smelting processes and compared their carbon emissions and gas utilization rates. The results show that, the material input of BF is dominated by iron ore and blast air. The material input of SF is primarily comprised of feed ore and reducing gas. In terms of energy efficiency, the main heat sources for BF ironmaking are carbon combustion before the tuyere and the sensible heat of blast air, with a thermal efficiency of 80.70%. The BF exergy efficiency is 56.57%, and the exergy loss during ironmaking is 4.25 GJ/t, of which external exergy loss accounts for a relatively high proportion （approximately 27.71% of total exergy input） and constitutes 63.80% of the total exergy loss. For SF ironmaking, the main heat source is reducing gas, with a thermal efficiency of 74.55%. The exergy efficiency of the SF smelting process is 41.61%, and the exergy loss during smelting is 5.462 GJ/t, which accounts for 58.39% of the total exergy expenditure. Comparison reveals that both the thermal efficiency and exergy efficiency of the BF are higher than those of the SF, indicating the BF's advantage in thermal energy conversion and quality maintenance. The shaft furnace process uses hydrogen-rich gas as a reducing agent, and its carbon emission per unit product is 322.42 kg/t,52.5% lower than that of the blast furnace （679.69 kg/t）. At the same time,the gas utilization rate （57.87%） and hydrogen utilization rate （59.77%） of the shaft furnace are higher than those of the blast furnace （52.00% and 41.35%, respectively）.
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  Cold bonding and high-temperature bursting of high titanium slag dust

  TANG Xiaojing, LI Jun, TANG Jianzhong, WU Enhui, HOU Jing, XU Zhong, PENG Wenjing, LI Xiang

  Iron and Steel. 2025, 60(12): 197-208. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250303

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  During the electric furnace smelting process of high titanium slag, the excessively fine particle size of fine-grained titanium concentrate leads to significant generation of furnace dust. To enhance the recycling utilization of this high titanium slag smelting dust, experimental investigations were conducted on its cold-bonded briquetting performance and high-temperature bursting characteristics. The orthogonal experimental method was employed to study the influence of cold-bonding parameters,including binder ratio, mass fraction of binder ,water addition（mass fraction） and forming pressure on the drop strength and compressive strength of both green balls and dry balls of furnace dust. The orthogonal test results demonstrated that forming pressure exerted the most significant effect on the tumble strength of green balls, as well as the compressive strength and tumble strength of dry balls. Meanwhile, water addition（mass fraction） shows the most pronounced influence on the compressive strength of green balls. The drying process substantially improves both the tumble strength and compressive strength of the pellets. Considering both cost efficiency and pellet strength, the optimal parameter combination is determined as follows,8% binder ratio, 8% binder mass fraction, 0 water addition, and 6 MPa forming pressure. Under these conditions, the produced pellets exhibit stable performance, the tumble strength and compressive strength of green balls reach 3 times/（0.5 m） and 241.5 N/pellet, respectively, while those of dry balls reach 125 times/（0.5 m） and 477.3 N/pellet. High-temperature bursting tests reveal that the bursting ratio of pellets increases progressively with rising temperature, and the bursting temperature range for cold-bonded pellets make from high titanium slag dust is 700-800 ℃ . The cold-bonded briquetting process enables effective recycling of high titanium slag dust, thereby improving the resource utilization efficiency of fine-grained titanium concentrate in electric furnace slag smelting.
Metallurgical Process Engineering
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  Innovation and application of iron-steel interface technology in Tangsteel New District

  WANG Xindong, LI Yiting, MA Xinguang, WANG Yinghong, LI Xiuping, SHENG Gang, ZHOU Jicheng, LI Jiansheng

  Iron and Steel. 2025, 60(12): 209-216. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250393

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  As a key demonstration project for the transformation and upgrading of Hebei Iron and Steel Group, Tangsteel New District aims to achieve the construction goals of "greening, intelligence and branding", and is committed to building a production network architecture that integrates material flow, energy flow and information flow. The iron-steel interface, as a crucial link in the steel production process, encompasses multiple technological elements such as production organization, scheduling management, and logistics transportation. It plays a pivotal role in connecting the upper and lower levels and is of great significance for enhancing the production efficiency and economic benefits of enterprises. Based on the theory of metallurgical process engineering, Tangsteel New District had carried out a series of innovations and applications of iron-steel interface technology. An intelligent management system for the steel process had been established, a software platform for intelligent processes had been built, and core technologies such as laminar flow operation of processes, interface collaborative optimization, digital simulation of processes, and five-dimensional dynamic Gantt charts had been innovatively developed. Through the innovative application of models such as the blast furnace iron tapping prediction model, the iron water temperature drop prediction model, the full-process covering technology of the iron water ladle, and the optimization technology of the ladle allocation mode, the iron water ladle turnover rate and the iron water ladle accuracy rate in the new area of Tangsteel have been significantly improved, and the iron water temperature drop has been greatly reduced. The application of intelligent technologies such as the Gantt chart of the iron-steel interface, the iron separation decision, the intelligent ladle allocation decision, the tail ladle transfer decision, the molten iron transportation task scheduling, and the KPI（key performance indicator） statistical analysis have achieved real-time dynamic tracking and scheduling of the iron-steel interface, which not only improves the operational efficiency of the iron-steel interface, at the same time, it has also enhanced the ability of refined management. The innovation and application of iron-steel interface technology in Tangsteel New District have enriched the theoretical connotation of metallurgical process engineering and set a model for the practical application of metallurgical process engineering in the steel industry.
Technology Exchange
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  Analysis and application of emulsion lubrication process impact during cold rolling process

  WANG Jianhui, GAO Yuan, SHI Zhourun, LI Xuetong, YI Kesong, BAI Zhenhua

  Iron and Steel. 2025, 60(12): 217-229. https://doi.org/10.13228/j.boyuan.issn0449-749x.20250398

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  The surface quality issues of finished strip steel caused by poor parameter settings of emulsion lubrication process during high-speed rolling was focused on. Firstly, a model of emulsion jet flow field during the rolling process was established. The influence analysis of emulsion jet flow field under different lubrication process parameters was carried out using FLUNT software. Furthermore, the influence laws of work roll speed, emulsion jet pressure, spray angle, and nozzle height on the gas-liquid two-phase velocity field and emulsion distribution between the roll and the strip were obtained. Secondly, based on the laws of emulsion jet flow field, using the orthogonal experimental method, 3 typical test values were selected for various parameters. The nozzle mass flow rate, roll gap emulsion volume fraction, mixed phase density at the roll gap, impact force on roll surface, work roll surface emulsion volume fraction, and strip surface emulsion volume fraction were used as evaluation indicators. By analyzing the range values of the indicators and quantifying the sensitivity of each parameter, the optimal combination of working parameters was determined. And further adjusting the jet angle, compare and verify the correction results to obtain the optimal solution for the emulsion jet flow field. The work roll speed is 150 rad/s, the injection pressure is 0.7 MPa, the nozzle height is 110 mm, and the injection angle is 0°. Finally, the optimized process parameters were applied to a cold rolling production line of certain enterprise. By tracking the on-site data for the first 6 months and the last 6 months of optimization, and using the wiping method to determine the residual oil and iron content on the surface of strip steel. Comparison shows that the surface scratch defect rate has decreased from 0.08% to below 0.05%, the residual oil content on the surface of strip steel has decreased from 150-300 mg/m² to 80-200 mg/m², and the residual iron content has decreased from 25-80 mg/m² to 15-40 mg/m². The surface quality of the strip steel has been effectively improved, and the production efficiency has been enhanced. The engineering applicability of simulation and optimization methods has been verified.