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.

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.

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.

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.

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.

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%.

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.

How to control Al₂O₃ oxide inclusions in Al-deoxidized steel has long been a challenging issue in metallurgical production. Calcium treatment can modify high-melting-point Al₂O₃ oxide inclusions into low-melting-point calcium aluminate (12CaO·7Al₂O₃), which effectively inhibits nozzle clogging and improves the hydrogen-induced cracking resistance of steel. However, parameters such as the timing and method of calcium addition directly affect the calcium yield and the degree of inclusion modification. Improper control may, on the contrary, exacerbate the nozzle clogging phenomenon. Therefore, the modification effect of calcium treatment on non-metallic inclusions in Al-deoxidized steel is reviewed. From the perspectives of kinetics and thermodynamics, the mechanism of action and key influencing factors are elaborated, including the effects of molten steel temperature, calcium addition method and timing, CaO/Al₂O₃ ratio of refining slag, as well as the contents of O, S and Al in molten steel on the compositional evolution and liquid phase fraction of inclusions. In addition,the technological optimization directions of calcium treatment is discussed, aiming to improve calcium utilization efficiency and inclusion control level, involving innovative approaches such as secondary calcium treatment, application of calcium-silicon iron, and calcium-magnesium alloy synergism.

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.

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 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.

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.

Iron ore pellet production is recognized as an energy-intensive and high-emission industrial process, and its energy conservation and emission reduction represent a critical component for the iron and steel industry to achieve the “dual carbon” goals. Efforts are made herein to leverage the synergistic effect of high-pressure roll grinding pretreatment and optimized ore blending, thereby reducing the pellet induration temperature while ensuring product quality, so as to provide technical support for the green transition of the iron and steel industry. A systematic laboratory experimental approach was adopted. Firstly, six types of iron concentrates were pretreated using a high-pressure roll mill under a pressure of 14 MPa, and the effects of this process on raw material particle size, specific surface area and pelletizing performance were analyzed. Subsequently, green pellets were prepared by a disc pelletizer, and the preheating and induration processes were simulated in a horizontal tube electric furnace to explore the influence law of different process parameters on pellet strength. Finally, scanning electron microscopy was employed to analyze the microstructural changes of pellets, thus revealing the synergistic strengthening mechanism.Results demonstrate that high-pressure roll grinding can significantly improve the physical properties of iron concentrates. After two passes of roll grinding treatment, the proportion of the 5 mm size fraction in the blended ore can be increased to 75.45%, which effectively enhances particle surface activity and strengthens recrystallization interface reactions, thereby improving pellet strength. Meanwhile, two passes of high-pressure roll grinding can substantially reduce the pellet induration temperature from 1 200 to 1 100 ℃. On this basis, optimized ore blending was further applied to enhance pellet consolidation efficiency. Under the optimal ore blending ratio (5 wt.% ore A, 11 wt.% ore C and 7 wt.% ore D), the minimum induration temperature of pellets can be further reduced to 1 080 ℃, with the compressive strength reaching 3 189 N/P, which far exceeds the industrial standard of 2 500 N/P. Microstructural analysis indicates that the synergistic effect of high-pressure roll grinding and optimized ore blending significantly enhances the recrystallization and intergrowth degree of hematite, reduces internal pores and cracks of pellets, and thus greatly improves structural compactness. The synergistic mechanism of high-pressure roll grinding and optimized ore blending was clarified, and the dual optimization effects of this combined technology on reducing induration temperature and improving pellet strength were quantified via laboratory data.

The low thermal expansion properties of invar steel make it widely used in precision instruments, aerospace components and other fields, but the low strength limits its further development. Adding alloying elements to invar steel and inducing the precipitation of carbide second phase through solid solution-aging can significantly improve the mechanical properties of invar steel.Solid solution-aging is a key prerequisite for precipitation, and carbide dissolution behavior in this process is particularly important. The alloying elements Nb, Mo, V and Ti were added to invar steel, and the carbide dissolving behavior was analyzed and the mechanism was investigated by scanning electron microscopy and high-temperature laser confocal microscopy. The results show that there are two types of carbides in Nb-Mo-V-Ti and Nb-Mo-V invar steels. The larger carbide particles with an average size greater than 5 μm, formed during the solidification process, are called as the primary carbides. The smaller carbides with an average size of less than 1 μm, precipitated from the matrix, are called as the secondary carbides. Both types of carbides are compositeprecipitation phasesof (Nb, Mo, V)C or (Nb, Mo, V, Ti)C corresponding to their respective components. The thermodynamic results and HT-CSLM observation indicate that the dissolution temperature of the primary carbides is close to the solidification transition temperature of the invar steel, so that it is difficult to dissolve. The secondary carbides realize the basic dissolution after heating and prolonging the holding time, and from this, Ti has a hindering effect on the dissolution of the carbides, which makes the carbides have a higher thermal stability. In addition, the Johnson-Mehl-Avrami-Kolmogorov equation is used to characterize the dissolution kinetics of the secondary carbides, and the dynamics model is experimentally verified to be able to predict the dissolution fraction of the secondary carbides better.

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.

The advancement of rolling technology relies on robust technical support, while the current control level has entered a critical turning point. The control effect based on traditional control theories has approached its limit, and numerous key technical problems have not yet been completely resolved. Therefore, it is imperative to introduce brand-new control theories and methods to achieve leapfrog improvement in control performance. In the hot-rolled strip production process, the automatic gauge control of the finishing rolling process occupies a core position, and its control accuracy directly determines the quality and qualification rate of the finished strip. To address the influence of temperature fluctuations on the stability of the exit thickness of incoming materials and the positive feedback problem existing in the traditional gauge feedback control, a hardness feedforward control strategy is proposed. Taking the Ansteel 1700 ASP production line as the application object, the influence coefficients of load distribution on various process indicators are calculated and analyzed; meanwhile, based on the increment equations of thickness, rolling force and crown, the roll gap adjustment values of the F₃—F₆ stands are determined. In hot rolling field practice, the hardness feedforward control of the F₃ and F₄ stands and the hardness over-compensation control of the F₅ stand are successfully realized. In addition, a nonlinear PID control strategy is introduced into the monitoring AGC system, which features a wide parameter tuning range and strong engineering practicability. Statistical analysis of production data of different rolling specifications shows that after the implementation of the composite control strategy, the strip thickness accuracy is improved by approximately 1% compared with the original level, indicating that the control system has good prospects for popularization and application.

Aiming at the degradation mechanism of coke induced by K, Na, KF and NaF gases during blast furnace smelting, gas adsorption experiments on coke were conducted via the gas-phase adsorption method. Combined with characterization techniques including XRD and SEM-EDS, the influence laws of K, Na, KF and NaF gases on the hot-state properties and microstructures of coke were systematically investigated. The results show that coke surface particles are exfoliated under the action of K gas, while powder-like spalling of coke surface is induced by Na gas. In contrast, the number of pores in coke is significantly increased by KF and NaF gases. After the adsorption of K, Na, KF and NaF gases by coke, the interplanar spacing of the (002) crystal plane of graphite microcrystals is enlarged, whereas the microcrystalline stacking height and microcrystalline layer size are reduced, which severely impairs the orderliness and integrity of the microcrystalline structure. The degradation degree of the aforementioned gases on the microcrystalline structure is ranked as follows: K>Na>KF>NaF. The variation of microcrystalline structure leads to an increase in coke porosity, which in turn elevates the coke reactivity index (CRI) and reduces the coke strength after reaction (CSR). Among these gases, the effects of K and Na gases on coke porosity are significantly stronger than those of KF and NaF gases. Specifically, the influence of K gas is greater than that of Na gas, and the impact of KF gas exceeds that of NaF gas. When coke is adsorbed with 1% NaF gas, its hot-state properties (with CRI≤25% and CSR≥65%) still meet the requirements for blast furnace smelting. However, after the adsorption ofmass fraction of 1% K, Na, or KF gas, both CRI and CSR exceed the standard limits. Overall, the influence degree of various gases on the hot-state properties of coke follows the sequence: K>Na>KF>NaF. In addition, with the increase in gas adsorption capacity, the growth rate of CRI and the decline rate of CSR both exhibit a trend of marginal decrease.

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

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

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

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

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

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

In 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.

The mechanism of diffusion bonding between martensitic stainless steel 00Cr12Ni10MoTi and a novel copper alloy Cu3Cr1.5Nb using Ni foil and AgCu37.5 as interlayers is investigated. Vacuum diffusion bonding was conducted at 980 ℃for 90 min under a pressure of 5 MPa. The microstructures and mechanical properties of the joints were systematically characterized by optical microscopy, scanning electron microscopy, X-ray diffraction, and tensile test. The results indicate that all three types of joints achieved interfacial metallurgical bonding to varying degrees. The direct diffusion-bonded joint exhibited a discontinuous interface with a tensile strength of 476.36 MPa and a dimpled fracture surface, characteristic of ductile failure. In the joint with the AgCu37.5 interlayer, Ag diffused toward the Cu side and segregated along the grain boundaries of the steel substrate, resulting in microcracks and Kirkendall voids due to the wetting and spreading of the filler metal. This joint fractured within the weld zone under tension, showing a tensile strength of 479.61 MPa, corresponding to a 0.7% increase, and a mixed ductile-brittle fracture mode. In contrast, the joint with the Ni foil interlayer demonstrated excellent metallurgical bonding on both sides, forming ductile solid solutions, Cr₃Ni₂ intermetallic compounds, and Kirkendall voids. It achieved a tensile strength of 491.38 MPa, representing a 3.1% improvement, and fractured in the copper substrate with clear dimples, indicating ductile fracture. Therefore, the use of a Ni foil interlayer enables sufficient interfacial bonding and superior joint performance in the diffusion bonding of stainless steel to copper alloy.

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

Under the strong impetus of the global“dual-carbon” strategy, the green transformation of the metallurgical industry is imperative. Blast furnace smelting technology with a high pellet ratio has emerged as a key research focus.High-silicon magnesium flux pellets is concentrated, examining their current research status and development trends. Pellets demonstrate significant advantages in low-carbon environmental protection. Their production entails low energy consumption and minimal pollutant emissions. Featuring high iron grade, uniform particle size, and low sulfur content, pellets create favorable conditions for low-carbon and stable blast furnace operation.It effectively advances the energy conservation and emission reduction efforts in the steel industry. High-silicon magnesium flux pellets exhibit distinctive characteristics. Utilizing high-silicon iron ore expands resource options and reduces costs. MgO enhances slag fluidity, facilitating desulfurization. Furthermore, flux pellets contain inherent flux components, which lower costs and improve pig iron quality. However, in blast furnace smelting with high pellet proportions, noticeable changes occur in burden distribution as the pellet ratio increases. The characteristics of the softening-melting zone also alter. Although the melting-dripping performance improves, the temperature of the softening-melting zone rises and its width expands, thereby disrupting gas flow. The slag system is significantly influenced by pellet composition. Variations in gangue elements such as silicon and magnesium modify the slag system’s composition and properties, consequently affecting desulfurization efficiency. Synthesizing existing research, blast furnace smelting technology with high pellet ratios, while promising, still confronts numerous challenges. Future research should prioritize optimizing pellet production processes, precisely regulating blast furnace operational parameters and innovating burden structure design. These efforts will establish a technical foundation for the sustainable development of the steel industry and contribute to the steady realization of the “dual-carbon” goals.

The precipitation behavior of carbonitrides in microalloyed steels is a key factor in controlling the microstructure and properties of the steel. To elucidate the precipitation mechanism of MX-type (M=Ti/Nb, X=C/N) carbonitrides in Ti/Nb composite microalloyed steels and their influence on phase transformation processes, molecular dynamics (MD) simulation methods were employed to systematically investigate the atomic diffusion behavior, cluster evolution kinetics, and precipitation phase formation patterns in the Ti-Nb-C-N multi-component system. The results indicated that Ti/Nb composite additions significantly enhance interatomic bonding energy, promoting the formation of Ti-Nb-C-N atomic clusters, which preferentially form (Ti,Nb)(C,N) composite carbonitrides in the austenite region. Dispersed MX particles refine grain size through the Zener pinning effect and act as heterogeneous nucleation nuclei during phase transformations, promoting ferrite formation and synergistically achieving simultaneous optimization of strength and toughness. The synergistic mechanism of composite microalloying elements was revealed at the atomic scale, and a relationship between precipitate phase evolution and microstructural evolution was established, providing fundamental theoretical guidance for the development of high-strength, high-toughness microalloyed steels.

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

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

The direct sodium roasting process for vanadium extraction from vanadium-titanium magnetite, offering the advantage of high overall vanadium recovery, faces challenges such as excessive sodium salt consumption and difficult utilization of high-sodium tailings. A new process of vanadium extraction by sodium-calcium composite roasting is proposed. Through the synergistic effect of sodium carbonate and calcium carbonate, the amount of sodium salt can be reduced and the recovery rate of vanadium can be improved.Experimental results demonstrate that compared with traditional sodium roasting, the sodium-calcium composite system achieves a 3.29% increase in vanadium recovery (reaching 75.19%) after water leaching while reducing sodium salt dosage from 6% to 4%. Notably, the acid leaching process shows a remarkable 25.18% improvement in vanadium recovery (up to 97.08%) with sodium salt consumption decreased from 6% to 5%. This technology replaces 16.6%—33.3% of sodiumsalt by low-cost limestone, effectively reducing Na content in tailings from 2.360% to 0.032%—1.790% and residual V content from 0.240% to 0.029%—0.211%. The findings highlight the significant advantages of sodium-calcium composite roasting in reducing production costs, improving resource efficiency, and mitigating environmental risks.

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

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%.

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

Blast furnace blowing is an effective method to treat waste plastics, but the large-scale utilization of waste polyvinyl chloride (PVC) has been restricted due to its high chlorine content, easy slagging and equipment corrosion in BFB. The hydrothermal carbonization (HTC) was used as the primary raw material of waste polyvinyl chloride (PVC) as a means of dechlorination and quality enhancement, and the hydrothermal carbon performance of waste PVC prepared under different parameters was investigated. The results show that when the hydrothermal temperature is 250 ℃ and the pH value is 5, the performance of the prepared hydrothermal carbon is the best, where the dechlorination efficiency is 88.92%, the fixed carbon mass fraction is increased to 46.32%, and the high calorific value is increased to 30.92 MJ/kg. In order to further improve the process, waste paper and PVC were introduced for co-hydrothermal carbonization test. It was found that co-hydrothermal significantly improved the dechlorination efficiency and improved the physical and chemical properties of hydrothermal carbon. Under the optimum conditions (hydrothermal temperature of 250 ℃, pH value of 5), the dechlorination efficiency can reach 94.12%, which is 5.2% higher than that of hydrothermal carbonization alone. The fixed carbon mass fraction of the hydrothermal carbon increases by 28.9%, the carbon mass fraction increases by 9.0%, and the high calorific value increases by 4.3 MJ·kg^-1, indicating that the co-hydrothermal carbonization has obvious synergistic effect. Through the analysis of scanning electron microscopy results, it was found that the pore structure of PVC was significantly improved after co-hydrothermal carbonization, and carbon microspheres were formed on the surface. The appearance of carbon microspheres increases the specific surface area and porosity, which can effectively improve the reaction rate and combustion efficiency of hydrothermal carbon and pulverized coal after blast furnace injection. It can be seen from the analysis that the main reason for the improvement of dechlorination efficiency by co-hydrothermal carbonization is that the OH^- produced by the hydrothermal decomposition of waste paper effectively replaces the Cl^- in PVC, and the H⁺ generated by the elimination reaction of PVC also promotes the hydrolysis of waste paper, which provides a new way for the efficient dechlorination and resource utilization of waste PVC.

In order to improve the impact abrasive wear performance of ZG25CrNiMo low alloy wear-resistant steel, based on the beneficial effects of rare earth elements in steel, the effect of rare earth Ce on the inclusions in the steel and the solidification organization of the as-cast state was investigated. After the addition of 0.004 8 wt.%Ce, the inclusions in the cast state of the test steel were modified from large-size, irregular Al₂O₃-MnO-SiO₂ composite inclusions encapsulated by MnS to small-size, spherical CeAlO₃-MnO-SiO₂ composite inclusions with small pieces of MnS attached, while the number of inclusionsand the average size decreased. Thermodynamic calculations were carried out on the rare earth inclusions, and it was found that the CeAlO₃ inclusions were most easily generated at 1 873 K. The inclusions were also found to be more easily generated in the cast steel. The cast solidification organization of the test steel was significantly refined, and the proportion of equiaxial crystals increased from 16.1% to 26.6%. The mismatch between the (011) surface and the δ-Fe (110) surface of CeAlO₃ is 7.86%, which can be used as the δ-Fe non-homogeneous nucleation core to provide more nucleation sites in the solidification stage of the steel to refine the as-cast solidification organization. The addition of rare earth Ce significantly increases the number of nucleation sites during the solidification process of the test steel and significantly refines the solidification organization at the initial stage. After adding 0.004 8% Ce, the solidification organization of the test steel was refined.

The Hami region of Xinjiang is rich in vanadium-titanium magnetite resources, which have high comprehensive utilization value and provide an effective solution to the shortage of high-quality iron ore resources in northwest China and the high costs of imported iron ore. The viscous flow characteristics ofhot metal are key factors affecting the smooth operation of iron ore smelting in blast furnaces. The viscosity of titanium-containinghot metal obtained from smelting vanadium-titanium magnetite is typically higher than that of normal molten iron, leading to issues such as molten iron sticking to the ladle and hooks, which can result in difficulties in tapping and hinder efficient production. Titanium is the main reason for the increase in the viscosity ofhot metal, but the mechanism of the influence of titanium on the viscous flow characteristics ofhot metal containing titanium is still unclear. Therefore,an oscillating cup high-temperature melt viscosity meter was adoded to test the influence of titanium content on the viscosity ofhot metal produced in a certain steel plant. Additionally, molecular dynamics simulations are used to deeply reveal the mechanism of titanium′s impact on the structure of molten iron. The results indicate that the viscosity and melting temperature ofhot metal increase with higher titanium content, particularly spiking sharply when titanium content exceeds 0.3%. At 1 450 ℃, increasing the titanium content from 0.1% to 0.4% results in a viscosity increase of 4.2 mPa·s and a rise in melting temperature of 99 ℃. Molecular dynamics research shows that the interaction between titanium and carbon atoms is significantly stronger than the bonding capacity between carbon and iron atoms. Titanium atoms occupy the coordination space of carbon and iron atoms, forming stable coordination cores with carbon atoms and resulting in complex cluster structures within the molten iron. As titanium content increases, the complexity of these cluster structures grows, reducing the diffusion capabilities of carbon and iron atoms, and leading to decreased fluidity of the molten iron.

High-purity refractory metals are recognized as critical raw materials supporting the development of the advanced electronic information industry. However, mainstream purification methods such as electron beam melting and plasma arc melting are generally plagued by technical limitations, including limited removal efficiency of gaseous impurities and high susceptibility of electrodes to contamination. Inductively coupled plasma melting (ICPM) technology is proven to effectively overcome these drawbacks, thus emerging as a highly efficient and clean purification approach. As the core component of ICPM equipment, the rationality of the structural design of the plasma generator directly determines the stability and continuity of the ICPM purification process. Therefore, numerical simulations are first carried out via Fluent software to optimize the key structural parameters of the generator. Results demonstrate that a stable and symmetrical vortex zone as well as an optimal flow field with uniform cooling can be formed inside the generator when the number of central gas inlet holes is set to 8, the incident angle of the inlet holes is 8°, and the diameter of the cooling gas inlet slot is 6 mm. Furthermore, a magneto-thermal-fluid multi-field coupling model is established by means of COMSOL software to investigate the influence laws of process parameters (including coil power, central gas flow rate and cooling gas flow rate) on the plasma temperature field and flow field. It is found that the enhancement of coil power and central gas flow rate can significantly strengthen the plasma jet intensity and elevate its temperature. In contrast, a critical threshold exists for the cooling gas flow rate; beyond this threshold, a further increase in the flow rate will instead lead to the reduction of plasma jet intensity and temperature. Results of experimental verification indicate that the plasma generator designed achieves stable operation, and the measured morphology of the plasma torch shows high consistency with the simulation results. Conclusions drawn from the work are expected to provide scientific basis and technical support for the engineering design of plasma generators for ICPM equipment.