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 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.

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.

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.

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.

For GCr15SiMn steel castings, the effects of multi-component solute convection and mold structure on the solute distribution of castings were investigated by using the macroscopic transport model of continuous medium, and the root cause of the three-dimensional (3D) effect of round castings was analyzed. The results show that the segregation of GCr15SiMn steel castings can be predicted more accurately by coupling the effects of multiple solutes on the thermal-solute buoyancy and solidification process, especially the elements that play a leading role in the solute buoyancy should be considered. When the taper of the mold increases from 0° to 5°, the maximum solute segregation ratio of the casting decreases by 0.576%, and the recommended taper of the mold is 5°. The hot melt convection and solute migration in the semi-annular mold wall on both sides of the longitudinal section of the central longitudinal section of the round casting are not symmetrical. The three-dimensional effect should be fully considered when the two-dimensional (2D) simplified simulation of the 3D transmission process is carried out.

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.

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 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.

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.

To address the issues of missed and false detections caused by the small defect sizes and high similarity to the background in cable steel wire surface defect detection, a cable steel wire detection network based on dual-path attention enhancement and multi-feature dynamic fusion was proposed. Firstly, a dual-path parallel attention module was designed, in which small defect feature representation was enhanced through a parallel mechanism of channel and spatial attention. Secondly, a multi-feature fusion module was constructed, where self-learnable factors were introduced to dynamically weight multi-scale features, so that background noise interference was suppressed. Then, a parallel spatial pyramid pooling module was proposed, in which both max pooling and global average pooling paths were integrated to ensure that critical texture and contextual information were preserved. Experiments conducted on a cable steel wire defect dataset demonstrated that the proposed method achieved an mAP@0.5 of 94.3%, an mAP@0.5:0.95 of 65.8%, and an F₁ score of 93.7%, which were shown to surpass six other mainstream detection models. Furthermore, through robustness tests, it was indicated that when the brightness was varied by ±50 cd/m², the fluctuation in model performance was maintained below 2.8%, demonstrating that strong industrial adaptability was achieved.

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.

The high-value utilization of solid waste in the metallurgical industry, specifically blast furnace dust and sludge (MBFDS), and the reduction of NO_x emissions have always been hot research topics and challenging problems. To enhance the material utilization of MBFDS, the idea of modifying it to prepare Fe-based selective catalytic reduction (SCR)denitration catalysts was proposed. An acidolysis-chemical coprecipitation method was used to modify and prepare Fe-based catalysts. The raw material composition and properties of MBFDS were determined using characterization methods such as X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) specific surface area analysis, and scanning electron microscopy (SEM). Additionally, the low-temperature catalytic properties of the catalyst were characterized by means of XRD, SEM, BET specific surface area analysis,X-ray photoelectron spectroscopy (XPS), NH₃ temperature-programmed desorption (NH₃-TPD), and H₂ temperature-programmed reduction (H₂-TPR). The results show that the temperature corresponding to the highest NO_x removal rate of the modified catalyst decreases from 380 to 280 ℃, and the denitrification rate increases from 63% to 96.7%. This is because more oxygen vacancies are formed in the modified catalyst, leading to a corresponding increase in its redox ability. The acidolysis modification also improves the alkali metal poisoning resistance of the catalyst and enhances its ability to chemically adsorb oxygen on the surface. The research results can provide theoretical references for the treating pollution with waste in the iron and steel industry.