Electrolytic ironmaking from aqueous solution, an emerging hydrometallurgical technology, aims to produce pure iron by electrolytic reduction of iron compounds, offering significant environmental and energy advantages. In recent years, with the continuous advancements in materials science, electrochemical technology, and energy systems, substantial research progress has been made in electrolytic ironmaking processes and techniques. However, certain technical challenges remain. For instance, the gas element content in the electrolytic products is high, necessitating further treatment to achieve higher purity iron. The stability of the electrolyte is poor, and ferrous ions are prone to oxidation and degradation.The state-of-the-art principles, processes, equipment, and control technologies of electrolytic ironmaking both domestically and internationally were reviewed. Corresponding solutions to the technical challenges have been suggested. For example, increasing the electrolysis temperature could reduce the gas element content in the products, thereby shortening the process, and adding stabilizers (such as ascorbic acid and sodium citrate) could inhibit the oxidation of ferrous ions. Finally, recommendations and outlooks for the future advancement of electrolytic iron production are given,including improvements in electrolysis equipment and the shortening of process flows to save energy consumption and intelligent systems implemented for real-time monitoring and other applications.

The iron and steel industry is a crucial foundational sector in China's national economy and a major carbon emitter, producing 1.3 billion tons of CO₂ annually, which accounts for 15% of the nation's total carbon emissions. Annual steel slag generation also reaches 150 million tons. Utilizing the bulk steel slag generated by the industry itself to sequester significant amounts of CO₂ enables“treating waste with waste”, provides an outlet for captured CO₂, and makes deep decarbonization of the steel industry feasible. The major advantages and existing problems of steel slag carbonation technologies are reviewed, which could be categorized them into two main types (direct and indirect carbonation). These can be implemented through three specific approaches: hot slag direct carbonation, cold slag direct carbonation, and cold slag indirect carbonation. It could be pointed out that both hot steel slag direct carbonation technology and cold steel slag indirect carbonation technology are suitable for China's context in achieving its dual-carbon goals. Hot slag direct carbonation seamlessly integrates with existing steel slag treatment processes in steel plants. Cold slag direct carbonation has relatively lower carbonation efficiency and capacity due to its lower reaction temperature, whereas cold slag indirect carbonation achieves higher-value utilization of the slag.

Under the dual context of China′s dual carbon strategy and the EU′s carbon border adjustment mechanism, significant transformation in the structure of steelmaking raw materials is being observed. The future development trend is characterized by both a high scrap ratio in basic oxygen furnaces and the utilization of electric arc furnaces operating with 100% scrap. However, the extensive introduction of scrap steel presents challenges to the cleanliness of molten steel and the subsequent quality of steel products, particularly concerning the impact of nitrogen content and titanium nitride inclusions on steel performance. Based on previous theoretical and industrial experimental research on the“nitrogen content-titanium nitride inclusions-material performance” relationship, progress in studies on the formation and control of titanium nitride in steel is summarized. The precipitation mechanism of titanium nitride in steel is analyzed from a thermodynamic perspective, and microsegregation and coupled precipitation models are reviewed. Key factors influencing titanium nitride precipitation are quantitatively analyzed. Through an analysis of the nitrogen content evolution during the steelmaking process, nitrogen content control methods in molten steel are systematically studied from the perspectives of raw material control, vacuum degassing, and slag-based nitrogen removal. The results of this review provide theoretical guidance for the production of high-quality titanium-containing steel in the context of changing raw material structures in steelmaking.

In the field of modern bridge construction, steel structures are widely employed in key load-bearing and connection components, including main beams, main cables, stiffening girders of suspension bridges, piers, bearings, and composite bridge deck structures. This is attributed to their excellent mechanical properties and constructability. They play an indispensable role in ensuring the stability and safety of bridges. However, the corrosion of steel structures poses a significant threat to both the safe operation and the service life of bridges. Bridges are constantly exposed to complex and dynamic natural corrosion environments, including wind, sunlight, rain erosion, and various chemical substances, all of which can contribute to severe corrosion of steel structures. A comprehensive review of the corrosion status of bridge steel structures is reviewed and the corrosion behavior of these structures in various natural environments is meticulously examined, including marine, inland, and complex environments characterized by alternating dry and wet conditions. The analysis focuses on the corrosion characteristics and severity affecting different components, such as piers, bridge bodies, cables, and bearing systems. In investigating the corrosion mechanism, the differences between chemical and electrochemical corrosion are elucidated, further classifying and analyzing uniform and localized corrosion within the realm of electrochemical corrosion. Specific forms of localized corrosion, including pitting, crevice, and stress corrosion, are examined in detail with respect to their formation mechanisms, influencing factors, and the severity of damage that they inflict on bridge steel structures. Based on the analysis of corrosion conditions, corrosion protection strategies for bridge steel structures are systematically summarized and organized, including material selection, coating systems, cathodic protection, and other advanced technical methods. By applying and optimizing these measures, a solid scientific basis and reliable technical support for corrosion prevention are provided, thereby reducing safety risks associated with steel structure corrosion, promoting technological innovation in bridge engineering, and ensuring the long-term durability and safe operation of bridges.

Micro-grain casting process can strengthen alloys under medium and room temperature by refining grains. However, the increased transverse grain boundaries may deteriorate the stress rupture and creep proprieties under high temperature creep conditions, leading to premature failure of components. In this work, stress rupture tests under 760 ℃/724 MPa were conducted on K447A alloys produced by conventional, fine-grain and micro-grain casting processes. The original and deformed microstructures were characterized by SEM, EDS and ECCI. The effect of micro-grain casting process on the stress rupture property of K447A alloy was studied and discussed. Results show that the stress rupture life of micro-grain casting K447A alloy is increased to 194 h, which is 134% and 69% higher than that of the conventional and fine-grained ones, respectively. The deformation is dominated by dislocation shearing, and cracks initiate on the sample surface and propagate transgranularly. The refined grains and carbides, the increased γ′ volume fraction and the disappeared dendrite structures induced by micro-grain casting process effectively inhibit crack initiation and propagation, significantly improving the stress rupture life of K447A alloy under this condition. Intergranular oxidation cracks along grain boundaries are observed in micro-grain K447A alloy, while their detrimental effect on mechanical property is much weaker than that of strengthening effect induced by grain refinement, thus significantly improving the stress rupture property of K447A alloy.

Sulfur (S) and phosphorus (P), as typical harmful impurities in steel materials, significantly influence the forming quality and service performance of welds in advanced steel materials. In terms of forming, S affects the shape and contour of the weld pool by altering its flow characteristics and surface tension, while P primarily modifies the surface tension of the molten metal, thereby influencing the spreading behavior and wettability of the weld pool on the base material. In terms of performance, S readily forms low-melting-point sulfide inclusions that accumulate at grain boundaries, not only increasing susceptibility to hot cracking but also severely degrading the toughness and plasticity of the weld metal. P, on the other hand, undergoes significant grain boundary segregation during solidification, weakening the bonding strength of grain boundaries. This serves as a source for crack initiation and propagation and significantly reduces the toughness and strength of welded joints. This article reviews the impact of S and P elements on weld formation and performance based on the latest research and summarizes current control strategies for both elements.

With the development of information technology, fully mining, screening and analyzing the big data of steel production is of great significance for achieving intelligent control, energy conservation and efficiency improvement in steel production. Through in-depth analysis of 425 groups of real-time test data of furnace gas composition of a 200 t converter in a steel plant, based on the carbon integral model, it is transformed into carbon composition and temperature time series data, and the data are normalized and preprocessed.A Long Short-Term Memory (LSTM) network model was developed to predict carbon mass fraction and temperature during the steelmaking process, with feeding and flue gas information serving as input variables. By comparing the measured end-point data from 50 production batches with the model′s predicted values, the results show that the hit rate of the end-point prediction error of the carbon mass fraction within ±0.03% is 96%, and the hit rate of the end-point prediction error of the temperature within ±15 ℃ is 92%. The deviation between actual and predicted values from the LSTM model is minimal, and the end-point hit rate within the specified range surpasses that of ELM and BP models. The LSTM model is beneficial to the dynamic prediction and control of smelting process.

The mechanical properties and fatigue performance of injection-production pipelines are vital for ensuring long-term safety and durability of underground gas storage (UGS).Mechanical performance tests and microstructural analysis on L360 pipeline steel base metal (L360-BM) and welds(L360-WM) were conducted. To address the challenge of testing high-cycle fatigue in injection-production pipelines, a high-cycle fatigue simulation model was developed for both base metal and welds based on experimentally measured material properties, and its accuracy was verified through high-load fatigue tests.The fatigue life evolution under varying loading conditions is further explored, comparing the fatigue performance of the base metal to that of the weld specimens. Results indicate that the plasticity of L360-WM is markedly lower than that of L360-BM, with elongation at break is 26.1% for L360-BM and 21.6% for L360-WM, characterized by ductile fracture and quasi-cleavage fracture, respectively. Both L360-BM and L360-WM specimens exhibit a decrease in fatigue life as the average tensile load and load spectrum amplitude increase. For a tensile load of 6.5 kN and an amplitude greater than 0.075, the fatigue life of L360-WM specimens is 44.7% of that of L360-BM specimens. These findings offer valuable data and theoretical insights to support material selection and pipeline failure prevention in UGS.

The granulation of iron ore is indispensable in sintering process, which ensures the quality of sintering production. Under the background of the iron ore resources gradually depleting and the imported iron ore prices fluctuating, to improve and prefect the granulation process is crucial for enhancing the permeability of the material layer, increasing sintering production efficiency, and reducing energy consumption and production costs. The research progress of sintering granulation strengthening technology and process of iron ore is reviewed, including two aspects: conventional granulation strengthening technology and innovative granulation process. The advantage, disadvantage, and application scope of various technologies and processes are analyzed, aiming to provide reliable theoretical basis and practical guidance for iron and steel enterprises to scientifically select the granulation process according to their own raw material conditions and industrial needs, contributing to improved resource utilization and economic efficiency in sintering production.

Carbon content affects the distribution of carbides and element segregation during the solidification process of high-temperature alloys, thereby determining the microstructure and mechanical properties of superalloys. The effects of different carbon contents on the carbide distribution and quantity in GH3536 alloy ingots were investigated, and the elemental segregation behavior of the ingots was further analyzed. The results indicate that carbides in GH3536 are mainly M₆C and M₂₃C₆ types. Thermodynamic equilibrium calculation shows that the melting temperature range of carbides increases with the increasing ofcarbon content. M₂₃C₆ and M₆C can transform into each other. However, the remelting temperatures of carbides are not affected by the carbon content in DSC analysis. The addition of carbon content promoted the formation of two types of carbides, the carbide area increased significantly and morphology changed from block to net-like with the increasing carbon content which affected the ingot thermo-plasticity. The addition of carbon content also reduced the secondary dendrite spacing and inhibited the segregation of Cr, Mo and Ni. The segregation of elements reduced due to the precipitation of carbides occupies which consumed a large number of carbide-forming elements.

With the development of blast furnace ironmaking technology, the rising price of raw materials and fuels, and the proposed goal of“double carbon”, the development and application of metallized charge have become a hot research topic in recent years. The types and source of different metallized charges were introduced, the physicochemical characteristics and compositions of typical metallized charges were compared, and the utilization status of metallized charges in a blast furnace was analyzed. The metallized charges mainly include scrap, direct reduction iron(DRI), ferro-coke, and metallized sinter, etc. Scrap and DRI have higher iron grades than traditional iron ore and have good metallurgical properties. However, the shape of scrap is different, and its composition is complex, limiting its utilization. Thus, it is necessary to establish a unified industry standard to guide the rational utilization of scrap in a blast furnace. The use of DRI in blast furnace smelting has a remarkable effect of increasing production and reducing carbon emission, but it is expensive. New metallized charges, such as ferro-coke and metallized sinter, are mainly in the basic research stage at present and have not been applied in large-scale industrial practice. The physicochemical properties of various metallized charges are quite different. Suitable particle size, regular shape, and good metallurgical properties are usually required when added to the blast furnace. And the harmful element content should be controlled within a reasonable range. A large number of production practices at home and abroad have shown that the use of metallized charges can reduce the reducing agent ratio of blast furnace production, thereby improving production efficiency and reducing CO₂ emissions; with every 10% increase in the addition of metallized charges, the output of hot metal is increased by about 8%, and the CO₂ emissions of ironmaking system are reduced by 6%. To sum up, the metallized charge has a wide application prospect in blast furnace, and is one of the effective measures to achieve the goal of “double carbon” in the steel industry.

The steel metallurgy industry is a crucial component of the basic industries, where the quality stability of sinter is vital to the entire production process. A novel online prediction framework, the Process Feature Serialization and Extraction Prediction model (PFSE) is proposed to predict the FeO content in the sinter accurately. The framework first serialized and differentiated the raw data to enhance its expressiveness. Subsequently, it employed feature extraction techniques such as Grey Relational Analysis (GRA) and Correlation Coefficient (CC) to identify key process characteristics. Then, a prediction model for FeO content was constructed using Recurrent Neural Networks (RNN) and its variants, such as Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRU). Experiments conducted on sintering process data from a steel plant between 2022 and 2023 validated the PFSE framework, demonstrating good stability and accuracy. With an error tolerance of 0.1, the model achieved a high accuracy rate of 85.3%. which confirms the effectiveness and reliability of this method.

Hardenability is a key performance parameter of steel materials, reflecting the ability of steel to achieve uniform hardening during the quenching process, which directly affects the mechanical properties and service life of the steel. Traditional physical models have limited accuracy in predicting hardenability due to their inability to handle complex compositions and process parameters accurately. The application of machine learning models such as Support Vector Machine (SVM), Decision Tree (DT), Neural Network (NN) and deep learning in the prediction of steel hardenability is reviewed, and the prediction accuracy, data requirements and computational efficiency are compared and analyzed. The future research directions are prospected, including key issues such as improving data quality, fusion model and enhancing physical interpretability. With the continued development of machine learning technology, the accuracy and generalizabilityof hardenability prediction are expected to be significantly improved, providing strong scientific support for the intelligent production of steel in the industry.

The mechanical properties of rolled plate will be significantly reduced if the shrinkage holes of continuous casting slab are not completely healed during rolling process. With the samples from slab, intermediate slab, and plate of E355 pipeline steel, the industrial computed tomography (CT), scanning electron microscope (SEM), and optical microscope were applied to analyze the shrinkage holes evolution in the rolling process. The results show that the slab surface layer has a dense solidification structure, where the shrinkage hole appears to be small size and single type. With the distance from the slab surface increasing, the number density of shrinkage holes rises, the size is enlarged, and it becomes the through type holes. The number density of shrinkage holes in the slab center is 5.510 mm^-3, the volume rate increases to 2.191‰, and the average and maximum sizes are 0.140 and 1.493 mm, respectively. After rough rolling process, the shrinkage hole extends along the rolling direction, the size decreases, and the number density increases. In the center of the intermediate slab, the number density is 61.744 mm^-3, the volume ratio is 0.395‰, and the maximum and average diameters are 0.038 and 0.023 mm, respectively. No large-size holes are found in the final plate, and the shrinkage holes are completely welded during finishing rolling, but the small-size holes are still observed near the MnS inclusions.

Controlling the size of slag eye by bottom blowing in steel ladle can improve the quality of steel liquid. Based on the argon bottom blowing process in steel ladle, a three-dimensional unsteady multiphase flow water model is established by coupling the Discrete Phase Model (DPM) and the Multiphase Flow (VOF) model. The slag eye size and slag eye interface velocity obtained from numerical simulation are validated and analyzed using a 1:5 water model. The research investigated the impact of different parameters (bottom blowing flow rate, oil layer thickness, and bottom blowing position) on the distribution of slag eye size and slag eye interface velocity. Finally, the relationship between dimensionless slag eye area and dimensionless flow rate was obtained through data fitting methods. The results indicate that the slag eye area gradually increases with the increase of blowing flow rate and the decrease of oil layer thickness, with a more significant effect for higher bottom blowing flow rates. A greater eccentricity of the nozzle leads to a more noticeable change in slag eye area with respect to blowing flow rate. For eccentric bottom blowing, there is a critical flow rate value, beyond which the slag eye area decreases. For instance, with an oil layer thickness of 25 mm and a blowing flow rate of 2.26 L/min, the slag eye area decreased by 180 cm² compared to that when the blowing flow rate was 1.87 L/min.

The surface adsorption principle of H₂ on two crystal surfaces of Fe₂O₃(0 0 0 1) and Fe₂O₃(1 $\bar{1}$ 0 2) is investigated by a first-principles approach based on Density Functional Theory (DFT). The study focuses on the adsorption mechanism, adsorption energy, and electronic structure analysis of the H₂/Fe₂O₃ system. The results show that the adsorption of H₂ on the crystal surfaces of Fe₂O₃(0 0 0 1) and Fe₂O₃(1 $\bar{1}$ 0 2) are physisorption, with the vertical adsorption at the top of the vacancies being more stable than the other positions, and the adsorption energies of the adsorption are 20.99 and 26.44 kJ/mol, respectively. The interaction between H₂ and the crystal surface is mainly due to the orbital overlap hybridization effect between H and Fe, and the exchange, recombination, and energy conversion of electrons between the two occurs through the Mulliken charge fabrication analysis. The adsorption of H₂ to Fe₂O₃(0 0 0 1) and Fe₂O₃(1 $\bar{1}$ 0 2) produces H₂O, which needs to be dissociated from O atoms of the crystal surface across the energies of 1.999 and 2.496 eV. The dissociation of H₂O from O atoms on the crystal surface requires crossing an energy barrier of 1.999 and 2.496 eV, respectively, and releasing 1.894 and 1.573 eV of energy. The relatively high adsorption energy of H₂ on the crystal surface of Fe₂O₃(1 $\bar{1}$ 0 2) suggests that the adsorption of H₂ on Fe₂O₃(1 $\bar{1}$ 0 2) is more facile and stable. The energy barriers for the dissociation of the H₂O molecule from Fe₂O₃(0 0 0 1) are lower than those for Fe₂O₃(1 $\bar{1}$ 0 2), which implies that the reaction products on the crystal surface of Fe₂O₃(0 0 0 1) are more easily and steadily adsorbed. Fe₂O₃(0 0 0 1), implying that the reaction products dissociate more easily in Fe₂O₃(0 0 0 1).

Steel pipelines are key facilities for oil and gas transportation, and their structural integrity is crucial for securing energy supply. As an important means of failure analysis, fracture analysis techniques are valuable for revealing the causes of pipeline failure and preventing future risks.Four main fracture analysis techniques were systematically introduced, including compositional analysis, structural analysis, morphological analysis and inversion analysis, which reveal the causes of pipeline failure from different perspectives. The application of related fracture analysis techniques in pipeline failure analysis was further discussed, and the applicability of related techniques in pipeline failure analysis were compared. Results show that each technique has a specific scope of application, and its comprehensive use can significantly improve the accuracy of pipeline failure analysis and provide a scientific basis for pipeline design, maintenance and emergency response. Future research should focus on the comprehensive application of these techniques to cope with more complex working conditions and prevent the risk of pipeline failure on this basis.

The 862 MPa high-strength oil well tubing, known for its exceptional strength, toughness, and corrosion resistance, is particularly suitable for severe conditions containing high concentrations of CO₂,H₂S, and elemental sulfur. The effects of the initial microstructure on the properties of 862 MPa high-strength oil well tubing steel prior to the quenching and tempering heat treatment were investigated. The microstructures and properties after same heat treatments were compared for different initial microstructures. The findings reveal that the martensitic initial microstructure with a high density of crystal defects exhibited a significant reduction in martensite lath size by over 50% following quenching and tempering, achieving a simultaneous enhancement in strength and toughness through grain refinement strengthening. The morphology of Cr₂₃C₆ precipitates transitioned from intergranular chain-like structures to intragranular dispersed spherical structures, which increased the sulfide stress cracking critical stress intensity factor (K_ISSC) by approximately 10%. Further research indicates that the H₂S stress corrosion failure process of the material is the result of the synergistic effects of surface pitting and hydrogen-induced cracking.

Spent fuel reprocessing is a key step in the nuclear fuel cycle. Austenitic stainless steel for reprocessing is facing serious nitric acid corrosion problems. In the harsh environment of spent fuel post-processing corrosion,it is difficult for austenitic stainless steel to meet the requirements of equipment. It is of great significance to study the intergranular corrosion of austenitic stainless steel in spent fuel post-processing environment. The research results of the main corrosion mechanisms of austenitic stainless steel anode and cathode in spent fuel reprocessing environment in recent years are summarized. The application of ultra-low carbon austenitic stainless steel, ultra-pure austenitic stainless steel and high silicon austenitic stainless steel in spent fuel reprocessing is introduced. The intergranular corrosion resistance and research status of three austenitic stainless steels are summarized.

The burn-through point (BTP) state directly impacts critical production indicators of sintering processes, including yield, quality, and energy consumption. Addressing the limitations of current BTP prediction methods in terms of temporal span and operational adaptability, a hybrid long-term prediction approach integrating convolutional neural networks (CNN) and long short-term memory (LSTM) networks is proposed. The CNN module extracts localized temporal patterns across features from input data, while the LSTM component models temporal dynamics, collectively capturing long-range dependencies within the dataset to enable early BTP prediction during the material charging and ignition phases. Experimental and practical applications demonstrate that the model achieves a mean absolute error of less than 0.4 wind-box segments within a 45 min prediction window, with 89.2% prediction accuracy within ±0.8 wind-box segments. An effective solution for long-term BTP prediction challenges is provided.

Iron and steel is a pillar industry in China, and the production quality of steel products is key to the performance andprice. In order to solve the problems of poor accuracy, low efficiency and complex model structure in strip surface defect detection, we proposed a lightweight strip surface defect detection algorithm based on YOLOv11 (PSN-YOLO). Firstly, the P-GELAN_CAA feature extraction-fusion module was designed, and PSConv was introduced based on GELAN to process multi-scale information, optimize parameter utilization, and integrate CAA to enhance feature representation. Secondly, the lightweight and efficient SCDown downsampling was selected to expand the receptive field, reduce the information loss, and reduce the complexity of the model. Finally, NWD is used to improve the loss function of the bounding box, focusing on irregular and complex micro-texture features, so as to better measure the distribution similarity between the bounding boxes and improve the detection accuracy. Experimental results on the NEU-DET dataset show that compared with the benchmark model, the mAP of the proposed model is increased by 3.1%, and the number of parameters and computation are reduced by 20.3% and 19.0%, respectively, which better balances the detection accuracy and lightweight requirements. In addition, the model shows good generalization ability on the Severstal dataset, which meets the practical engineering needs and has important application value.

To facilitate the construction of new-type power systems and achieve carbon peaking/carbon neutrality goals, new-generation coal-fired peak-shaving units have been extensively deployed, exposing key high-temperature components to damage mechanisms dominated by creep-fatigue interaction. Based on current design codes and material test data including P91/P92 etc., this study systematically investigates temperature, stress, and load variations in boiler thick-walled components under both steady-state and flexible peak-shaving operations. Comparisons reveal critical discrepancies between laboratory high-stress creep/fatigue testing conditions and actual low-stress service environments with frequent load fluctuations. The mechanisms governing how stress levels, temperature ranges, and load variation parameters such as amplitude, frequency and ramping rate influence creep void evolution, fatigue crack propagation, and coupled creep-fatigue damage are thoroughly elucidated. Results demonstrate that transient thermal stresses and localized plastic strains intensify substantially under peak-shaving conditions, causing a paradigm shift in dominant failure modes from time-dependent creep failure under steady-state operation to complex damage patterns dominated by low-cycle thermal fatigue and creep-fatigue interaction. The proposed countermeasures, informed by engineering failure cases, encompass the adoption of advanced alloys such as G115 and C630R for their superior creep-fatigue resistance, geometric optimization to mitigate stress concentration, and the implementation of online life-assessment systems. Crucially, establishing near-service creep-fatigue interaction test protocols, developing multi-factor coupled damage models, and formulating material selection guidelines tailored for peak-shaving units are identified as essential strategies to ensure long-term operational safety and reliability.

The long-term corrosion behavior of 12Cr13 steelwas investigatedin a static oxygen saturated liquid lead-bismuth alloy at 450 ℃ for 6 000 h. The morphology, composition, and corrosion kinetics of the oxide film during the corrosion process were analyzed. The results indicate that the growth rate of the oxide film on 12Cr13 steel is slow, and the thickness of the oxide film follows a parabolic law. After3 000 h of corrosion, a typical double-layer structure oxide film forms with an inner layer of Fe-Cr spinel and an outer layer of Fe₃O₄. The diffusion of Cr at the micron scale plays a crucial role in forming the surface oxide film and inward steady progression of the inner oxide layer. Additionally, there is an evidence of peeling-off phenomenon in the oxide film after 3 000 h, which may be associated with unevenness on original corroded sample surfaces. Based on these experimental findings, a corrosion model for 12Cr13 steel in liquid lead-bismuth was proposed.

Iron coke as a new type of low-carbon ironmaking raw material, has a good reactivity. The use of appropriate amount of iron coke in blast furnaces (BF) can improve gas utilization efficiency and strengthen energy conservation and carbon emission reduction. Iron coke needs to have high mechanical strength and high reactivity to meet the requirements of production, transportation, and low-carbon blast furnace smelting of iron coke. Carbonization treatment is a key process for the transformation of iron ore-coal mixture into iron coke, which has a significant impact on the metallurgical properties of iron coke, such as mechanical strength and reactivity. The study of pyrolysis behavior and carbonization consolidation mechanism of iron coke is crucial for optimizing the metallurgical properties of iron coke. The research progress of pyrolysis behavior and carbonization consolidation mechanism of composite iron coke was reviewed. The current research results, the contents that need to be further studied and the prospect of theoretical research on iron coke carbonization consolidation were analyzed and summarized. To a certain extent, the key theoretical basis for the pyrolysis behavior and carbonization consolidation mechanism of iron coke has been summarized, which will theoretically clarify the carbonization process of iron ore-coal mixture into iron coke, promote the optimization of carbonization process technology path of iron coke, and advance the technology of iron coke preparation and its use in BF smelting.

Technical means such as SEM, TEM, XRD, and EBSDare usedto systematically study the effects of nickel and cobalt elements on the new NiCrMoV hull steel microstructure, second phase, and properties. The results showed that after quenching and tempering, the steel structure was composed of tempered martensite and a spot of reversed austenite, and during the tempering process, a fine-needle Mo-Cr-V-rich M₂C phase was mainly precipitated. Afterquenching at 850 ℃ and tempering at 580 ℃, theyield strength of new NiCrMoV steel can reach 1 140 MPa, and -84 ℃ low temperature impact effect reaches 76 J. With the increase of Ni content in steel, the grains are refined, the large angle grain boundaries increase, and the reversed austenite increases, which effectively obstructs the propagation of cracks and further improves the low-temperature toughness to 82 J. After adding the Co element in the test steel, the dislocation density is increased, and the precipitated M₂C phase increases and becomes more dispersed, which effectively improves the ultra-high yield strength of the test steel to 1 216 MPa.

The effect of the quenching-partitioning-tempering (Q-P-T) process on the microstructure evolution laws and regulation mechanisms of mechanical and forming properties for cold-rolled Q&P980 steel at 285, 310 and 335 ℃ quenching temperatures has been investigated. The results indicate that increasing quenching temperature promotes the transformation of martensite morphaology from coarse blocky structures to uniformly distributed fine laths. The volume fraction of retained austenite and its carbon content exhibit a trend of first increasing and then decreasing, with the optimal mechanical properties achieved at a quenching temperature of 310 ℃. An increase in quenching temperature leads to a decrease in hole expansion rate,plastic strain ratior-value, and limiting forming curves, while the plastic anisotropy index(Δr-value) shows an upward trend. At a quenching temperature of 285 ℃, strong recrystallized {111} texture and high-angle grain boundaries weaken the planar anisotropy caused by grain orientation differences, resulting in the best forming performance. Quenching at a temperature of 335 ℃ resulted in the deterioration of the material′s formability, which is attributed to the presence of a strong α-fiber texture coupled with a decrease in the intensity of the γ-fiber texture. It is indicated that while there is a certain correlation between forming performance and mechanical properties, more attention should be paid to the influence of texture types and their microstructural distribution on forming performance.

Coke powder, as the primary fuel in sintering production, has a particle size distribution that significantly affects both product quality indicators and energy consumption levels. The current method for measuring coke powder particle size typically involves manual sampling, drying, and vibrating sieving, which is complex, time-consuming, and unsuitable for timely control of crushing and proportioning systems. Although image recognition technologies for online detection of moving material particle sizes are developing rapidly, the fine particle size of coke powder and the harsh conditions in crushing and proportioning processes lead to severe challenges for image acquisition and size recognition. To address these issues, an image acquisition system for complex industrial environments was developed. The system comprises an image acquisition chamber and a multi-stage dust removal pipeline, designed to minimize the effects of lighting, temperature, and dust on image capture. Considering the fine particle characteristics of coke powder, an improved neural network was used for multiple training rounds to optimize the particle size recognition model, enabling the identification of surface particle size distribution on the conveyor belt. A predictive model was then constructed using machine learning algorithms, combining image-recognized surface particle size distribution data with manually sieved results to train a model capable of predicting the overall particle size distribution, thereby enhancing recognition accuracy. This image acquisition and particle size recognition system has been put into application in the coke powder crushing workshop of a domestic iron and steel enterprise. The application results showed that the recognition errors of the system for the particle size distribution ratio of coke powder in four intervals of (0, 0.5), [0.5, 3), [3, 5) and [5, ∞) mm were all less than 3%.

In the context of China′s “dual carbon” policy, the iron and steel industry is confronted with significant challenges in energy conservation and consumption reduction. The recovery of waste heat from blast furnace slag and the efficient utilization of coal are considered crucial for promoting the green development of the iron and steel industry. Thermodynamic and energy utilization studies were conducted on coal gasification reactions driven by blast furnace slag waste heat. A thermodynamic model for the coal gasification reaction was established based on the principle of minimizing Gibbs energy. The effects of the gasification reaction under varying temperatures,n(H₂O(g))/n(C) ratios, and pressure conditions were explored, leading to the identification of optimal operating conditions. At 1 073 K, with an n(H₂O(g))/n(C) ratio of 2.00 and a pressure of 0.10 MPa, the total syngas production was found to be 3.28 kmol, with a carbon conversion rate of 0.93 and a syngas production rate of 1.56. Additionally, a comprehensive analysis method incorporating both energy analysis and exergy analysis was employed to evaluate the energy utilization efficiency of the coal gasification reaction. The results indicated that the energy efficiency of the coal gasification reaction reached 73.22%, with an exergy efficiency of 70.81%.

Because of its special geometric structure, the multi-strand asymmetric tundish is easy to lead to significant differences in the flow characteristics of each flow of molten steel, which in turn affects the consistency of slab quality. Taking the four-strand asymmetric tundish currently used in a Chinese steel plant as the research object, the effects of different diversion walls and diversion holes on the flow field and temperature field of the tundish were studied. Firstly, the flow field characteristic parameters of tundish with different schemes were compared by physical simulation. The deficiency of tundish structure (original scheme P) was pointed out, and the optimization scheme was put forward accordingly. The temperature field distribution and inclusion removal effect of the optimization scheme were further analyzed by numerical simulation. The physical simulation results show that after using the optimized A4 scheme, the average residence time of the tundish is 53 s longer than that of the original scheme, and the proportion of dead zone is reduced from 37% to 28%. Among them, the stagnation time of No.1 nozzle is extended from 9 to 33 s, the short-circuit flow phenomenon is eliminated, and the consistency of each flow is significantly improved. The numerical simulation results show that the flow field and temperature field distribution of the A4 scheme are more uniform, the temperature difference at each outlet is reduced from 6 to 1 ℃, and the removal rate of inclusions of different sizes is better than that of the original scheme. In summary, the metallurgical function can be effectively improved by optimizing the structure of the tundish, which provides a technical basis for improving the quality uniformity of the slab.

Ti-La-Mg composite treatment of inclusions has an important influence on nucleation of intragranular acicular ferrite. In order to clarify the effect of Ti content on inclusions in steel during Ti-La-Mg composite treatment,the effect of Ti content on composition and formation process of inclusions in steel was compared and studied.As the results show Ti、 La and Mg are added in turn, and the first added element will inhibit formation of inclusionsby the later adding elements. Since affinity of La and Mg to oxygen is stronger than that of Ti, the later added La and Mg also have a strong modification effect on inclusions formed by adding Ti first, and the composition and structure of modified products are affected by previous Ti content. When mass fraction of Ti is 0, core of inclusions is mainly La-O(-Si), La-Mg-O and MgO, and the outer layer is MnS. When mass fraction of Ti is 0.008%, Ti will combine with La-O(-Si) and La-Mg-O, resulting in La-Ti-O and La-O-(S-Si) in the inner layer of inclusion, La-Ti-Mg-O in middle layer, and MnS in shell. When mass fraction of Ti is 0.015%, La-O(-Si) and La-O-S in inclusions disappear,withthe inner layer transforming into La-Ti-O and MgO, and middle layer of La-Ti-Mg-O, and number is significantly reduced. Outermost layer is MnS and a small amount of TiN. When mass fraction of Ti increases to 0.025%, La-Ti-Mg-O completely disappears and transforms into La-Ti-O. Final inclusions have two layers, where the inner layer is La-Ti-O and MgO, and the outer layer begins to appear obvious TiN. When mass fraction of Ti in steel is further increased to 0.040%, inclusions are still two-layer composite inclusions composed of La-Ti-O + MgO and TiN, and the numberof TiN increases significantly.

To reveal the influence of corrosion-resistant elements on the mechanical properties and corrosion behavior offerritic-pearlitic steel, three types of weather-resistant steels based on carbon steel were designed and prepared, and 0.35 wt.% Cu, 0.32 wt.% Cr, and 0.16 wt.% Ni were added in turn. The results of microstructure and performance characterization show that with the sequential addition of Cu, Cr, and Ni elements, the content of preeutectoid ferrite inferritic-pearlitic steel gradually decreased, and the spacing between pearlite sheets was gradually refined.At room temperature, the yield strength of CuCrNi-containing steel compared with carbon steel increased by 80 MPa, and the plastic toughness did not cause any damage compared to carbon steel. The electrochemical and laboratory periodic infiltration corrosion test results of simulated atmospheric corrosion environment (NaHSO₃ solution) show that with the addition of Cu, Cr, and Ni elements, the self-corrosion potential of the experimental steel gradually increases, and its corrosion resistance is improved; for 3-5 days of corrosion, the corrosion rate of experimental steels of different components gradually decreases with the extension of the corrosion time. At this time, the corrosion rate of Cu steel is the fastest, and the corrosion rate of CuCrNi steel is the slowest;when the corrosion time is extended to 10 days, the corrosion rate of Cu steel and CuCrNi steel further decreases, but the corrosion rate of CuCr steel increases slightly and is higher than that of Cu steel and CuCrNi steel, which indicates that the corrosion resistance of CuCr steel has decreased. X-ray diffraction analysis of corrosion products showed that the corrosion products of experimental steel were all composed of α-FeOOH, γ-FeOOH and Fe₃O₄, among which α-FeOOH accounted for the highest proportion, followed by γ-FeOOH and Fe₃O₄. After 10 d of corrosion, the α/γ (α-FeOOH/γ-FeOOH) of the experimental steels with Cu, Cr and Ni elements increased, which indicates that the stability of the rust layer has increased and the α/γ of CuCr steel is the smallest. It can be seen that after long-term corrosion, the rust layer of Cr-containing steel has low stability, and it is analyzed that it is related to the hydrolysis reaction of Cr³⁺. After further addition of Ni elements, it helps to form a denser rust layer, alleviates the adverse effects of hydrolysis reactions, and improves the stability of the rust layer. Therefore, CuCrNi steel exhibits higher corrosion resistance.

In order to reduce carbon emissions and realize the efficient recovery of zinc and iron elements in metallurgical dust, it is very important to carry out thermodynamic analysis of the reaction system of metallurgical dust under hydrocarbon atmosphere. The effects of different process parameters (such as temperature and time) on the metallization rate and dezincification rate of metallurgical dust were studied by high temperature roasting test system. The regulation mechanism of temperature on phase evolution and microstructure was revealed by means of X-ray diffraction (XRD) analysis method and scanning electron microscope-energy dispersive spectrometer (SEM-EDS) technology, and then the separation mechanism of zinc and iron under the synergistic effect of carbon and hydrogen was clarified. The results show that the migration process of zinc-containing phase under the coupling effect of carbonand hydrogen is mainly divided into two processes. Below the boiling point of zinc ( 907 ℃), ZnFe₂O₄ is basically reduced to ZnO, and when the temperature is above 907 ℃, the phase transition from ZnO to Zn (g) occurs rapidly under the interaction of carbon and hydrogen. The research results show that when the reduction temperature is 1 050 ℃, the duration is 20 min, the carbon-oxygen ratio (C/O) of blast furnace bag ash to converter sludge is 0.8, and a reduction atmosphere of H₂∶CO∶CO₂∶N₂=6∶2∶1∶1 is adopted, both the metallization rate and the zinc removal rate of metallurgical dust reach the optimal values. In addition, due to the different expansion coefficientsamong minerals when hydrogen is used to reduce iron oxide, thermal stress is easily generated at the interface, resulting in the formation of cracks. On the other hand, with the continuous consumption of H₂, the carburizing reaction is intensified, the CO production is increased, and the vapor pressure inside the spherical nucleus is increased, which eventually leads to the rupture of spherical nucleus anda large number of cracks. With the progress of the reaction, cracks are gradually deepened, and the emergence of cracks promotes the reduction of zinc and iron oxides.

In complex industrial environments, strip defect detection has high requirements for accuracy and efficiency, but existing methods are difficult to meet both of these needs simultaneously. To address this challenge, a lightweight multi-level feature fusion defect detection network model called LMFF-YOLOv8 was proposed. This paper introduces improvements to the network architecture in several key aspects. Firstly, we design a C2Faster module to replace the C2f module in the original YOLOv8 ,thereby optimizing the backbone and neck structure of the network to reduce computational complexity. Secondly, an AFPN module was introduced at the neck of the network to enhance the fusion effect of feature maps of different scales. At the same time, a fast selection kernel attention network module was designed to further improve the speed of feature fusion. Finally, the EIoU loss function was used instead of the CIoU loss function to improve the convergence speed and regression accuracy of the prediction box, making the detection results more accurate. To verify the effectiveness of the improved method, comparative experiments and ablation experiments were conducted on the NEU-DET and R-DATA datasets. The experimental results show that compared to the YOLOv8s, LMFF-YOLOv8 improves mean average precision by 4.4% and 3.3% on the two datasets, respectively, while also achieving a higher inference speed. The proposed model provides an effective solution for strip steel defect detection in complex industrial settings.

In view of the current situation that the detection equipment is easily affected by the environmental interference magnetic field, and the law between magnetic signal and stress is not clear.The formula of magnetization and stress is shown based on the magnetization model, and the finite element software COMSOL is used to calculate the magnetic field intensity and magnetic gradient under different stresses. A magnetic field test system for steel stress is developed using non-magnetic and weak magnetic materials. The results calculated by finite element are compared and verified by experiments. Both the finite element calculation and the test results show that when the stress increases from 0 to 40.9 MPa, the magnetization of the steel bar increases, and the absolute values of its magnetic field intensity B_y and magnetic gradient B_yz also increase. When the stress increases from 40.9 MPa to yield strength (355.6 MPa), the magnetization of the steel bar begins to decrease gradually, and the absolute values of B_y and B_yz are also gradually reduced. The curves of the relationship between average absolute values of B_y, B_yz and the stress are reversed when the stress is 40.9 MPa, which is far less than the yield strength (355.6 MPa).

Microstructural evolution and Invar effect of Fe_42.7Co_39.6Cr_8.6Ni_9.1 high-entropy alloy were investigated. After 50% cold rolling, alloy was annealed at 800, 900 and 1 000 ℃. Microstructures were characterized using electron backscattered diffraction, while Invar effect was analyzed using dilatometer. Results indicate that FCC grain size generally increases with increasing annealing temperature and time; static recrystallization model is established and activation energy is determined to be 109.5 kJ·mol^-1, which is similar to high-entropy alloys in the CoCrFeMnNi alloy system. During cooling after annealing, FCC→BCC martensitic transformation takes place; nucleation and growth of BCC are affected by grain boundaries and other factors, so the evolution of BCC fraction with annealing condition is complicated. Additionally, Invar effect is confirmed between 27-218 ℃. It is because the spontaneous magnetostriction effect of ferromagnetic FCC phase counteracts with volume expansion partially caused by lattice vibration. When BCC fraction increases from 5.6% to 25.2%, thermal expansion coefficient decreases from 3.8×10^-6 to 3.3×10^-6 ℃^-1. This indicates that thermal expansion coefficient only slightly changes; therefore, mechanical properties can be tuned through microstructural control while still keeping Invar effect.

Nb can significantly improve the strength and toughness of niobium-containing steel due to its grain refinement crystal and precipitation strengthening effects. However, it can also cause the crack sensitivity if the Nb-containing precipitates occur at the austenite boundary, which will be the stress concentration point. To solve the problem of crack defects on Nb-containing alloy steel during the continuous casting process, the evolution mechanisms of microstructure and precipitates in Nb-containing alloy steel were investigated under controlled cooling conditions. Results show that the γ→α phase transformation appeared first at the austenite boundary when the temperature decreased. This phase transformation also occurred within the interior of the austenite grain with the further decrease in the temperature. Meanwhile, the second phase precipitates formed at the grain boundary area when the temperature reached around 1 000-1 200 ℃. EDS analysis results suggest that Nb and N content in precipitates reduced with the increase in the cooling rate, the average content of Nb reduced from 9.81 to 5.49 wt.%, and that of N reduced from 1.4 to 0.57 wt.%, when the cooling rate increased fromto 20 ℃/s. Generally, the main second-phase precipitates were NbN and NbC. These results also indicate that the precipitation of Nb-containing precipitates can be inhibited, and the ratio of crack defects on the slab can be reduced when the cooling rate is enhanced.

Carburizing heat treatment could effectively improve the strength and fatigue property of gears. There are many factors affecting the fatigue property of gears, among which retained austenite plays an important role. However, how retained austenite affects the fatigue property of carburized gear steel is still under controversy. Therefore, the relationship between fatigue property and retained austenite transformation of 17Cr2Ni2MoVNb gear steel after carburizing was investigated by means of rotating bending fatigue tests, SEM, TEM, EBSD, and hardness testing. The results showed that the block-like retained austenite in the carburized layer preferentially underwent stress-induced martensite phase transformation under cyclic stressing, and the amount of retained austenite transformation was greater with the increase in the stress amplitude. When the type of rotating bending fatigue failure was inclusion initiation, the transformation and cyclic hardening of retained austenite could increase the hardness of carburized layer, which increased the fatigue property of carburized gear steel.

Medium-high manganese steel has become the preferred material for automobile steel due to its high strength-plasticity synergistic effect and lightweight characteristics. However, it faces severe challenges in industrial smelting.The redox reaction between slag SiO₂ and Mn in molten steel during refining process significantly leads to the failure of composition control such as [Si] and (MnO). In order to solve this problem, the thermodynamic equilibrium model of CaO-SiO₂-Al₂O₃-MgO quaternary slag system and Fe-xMn (x=5%,10%,20%,30%) system was constructed based on FactSage thermodynamic software. Under the condition of 1 600 ℃ and steel slag ratio of 10∶1, the interaction mechanism of basicity (R=CaO/SiO₂=1—6) and Al₂O₃ content (20%-50%) on slag-metal reaction was systematically investigated. The key parameters such as SiO₂ activity (a_SiO2), MnO content and desulfurization efficiency in the slag were analyzed. The regulation of refined slag composition on slag-metal reaction was clarified, and the optimal design scheme of slag system was proposed. The results show that increasing the basicity can significantly reduces the activity of SiO₂, inhibits the reaction 2[Mn]+(SiO₂)=[Si]+2(MnO), and reduces the MnO content in the slag from 19.7% when R=1 to 2.3% when R=6. In order to maintain the stability of the refined slag component, the basicity should be controlled to be greater than 4. Al₂O₃ exhibits significant amphoteric behavior. When Al₂O₃ is acidic, its acidic characteristics will weaken the effective basicity, resulting in an increase in SiO₂ activity and a sharp increase in MnO content. The MnO content can be controlled at the lowest value by synergistic regulation of basicity and Al₂O₃ content. When refined slag(R=6, w(Al₂O₃)=30%) reacts with 30%Mn steel, the MnO content is 2.1%. For 0.03S steel, when the basicity of refined slag is 5-6 and Al₂O₃ content is 27%-30%, the desulfurization efficiency is the best, but it is necessary to control w(MnO)≤2% to avoid the significant deterioration of desulfurization effect. Under the condition of satisfying the control of MnO content and the best desulfurization efficiency, the optimized slag system is suitable for the smelting of medium and high manganese steel with w(Mn)≤28%.

The key to endpoint control in BOF steelmaking is accurately predicting carbon content and temperature within the molten bath. To address the limitations of single just-in-time learning (JITL) models, which fail to account for operational condition information during similarity measurement and are susceptible to noise, thereby compromising prediction accuracy,a mutual information-weighted similarity sample selection-based just-in-time ensemble learning (JITL-EL) prediction model is proposed. First, the spectral clustering algorithm is employed to partition historical data samples into several subsets, maximizing inter-subset differences and intra-subset similarities, thereby effectively distinguishing operational conditions. Second, a posterior probability calculation method weighted by intra-class features is introduced based on the correlation between intra-class features and target variables, enabling the determination of the membership degree of the test sample to different clustered subsets. Subsequently, based on the membership degree of the test sample to the clustered subsets, a dynamic selection of varying numbers of similar samples from different subsets is performed using an intra-class feature-weighted metric method, constructing JITL base model learners. Final, the predicted values from the JITL base models of different clustered subsets are weighted and fused according to the membership degree of the current test sample to each subset, yielding the final prediction results. Simulation results using real data collected from steel mills demonstrate that the accuracy of carbon content prediction reaches 80.00%, while that of temperature prediction achieves 83.00%.

Using the cooling platform in the laboratory, a nine-nozzle moving jet cooling test was conducted to systematically investigate the cooling and heat transfer characteristics of the nine-nozzle moving jet system. By varying parameters such as nozzle moving speed, jet velocity, nozzle spacing, and offset distance, the heat transfer and fluid flow characteristics during the cooling process were analyzed. The results show that the impingement of the nine nozzles on the steel plate surface forms distinct impingement zones, interference zones, and stratosphere zones; the extension of the wetting front significantly affects the heat transfer in the stratosphere zone; reducing the nozzle moving speed or increasing the jet velocity can improve the cooling efficiency of the impingement zone; simultaneously increasing the jet velocity and moving speed accelerates the wetting of the steel plate surface. When the nozzle spacing is 20 mm, the balance between jet interference and the independence of a single jet maximizes the cooling efficiency. In addition, an appropriate offset distance (5 mm) improves the heat transfer uniformity, while an excessively large offset distance reduces the overall performance. Through experimental research, the multi-nozzle dynamic jet cooling system in industry is optimized, and future studies can further explore asymmetric nozzle layouts and transient heat transfer models.