As a vital soft magnetic metallic material, grain-oriented electrical steel (GOES) is predominantly employed in the fabrication of components such as transformer cores. In GOES manufacturing, the quality of Mg₂SiO₄ layer, which develops during the high-temperature annealing stage, is of critical significance. As the fundamental structural unit of Mg₂SiO₄ layer, the morphological distribution of Mg₂SiO₄ grains decisively influences the magnetic properties and iron loss of the GOES. The Mg₂SiO₄ layer not only facilitates the preferential growth of secondary goss-oriented grains in the matrix, enhances the domain wall pinning effect, improves interlayer resistance, and regulates surface stress, but also provides a dense and intact surface foundation for high-quality insulating coatings in subsequent processes. This undercoating is a key contributor to the superior comprehensive performance of GOES. An in-depth analysis of the formation mechanism of Mg₂SiO₄ layer during the high-temperature annealing was provided, and the regulation principles of magnetic properties in GOES were revealed.Recent advancements in regulating undercoating quality and enhancing magnetic properties were systematically reviewed, focusing on critical factors such as the characteristics of the SiO₂ oxide layer, MgO coatings with additives, and high-temperature annealing parameters. Finally, recent pivotal investigations into the Mg₂SiO₄ layer were summarized, and an outlook on future research trajectories concerning the Mg₂SiO₄ layer in GOES was prospected.

As a byproduct of crude steel production, steel slag is generated in enormous quantities. However, its low utilization rate leads to resource waste and environmental pollution. Therefore, innovating steel slag processing techniques, expanding its application fields, and improving its resource recovery rate have become urgent priorities. First, the current direct and indirect applications of steel slag, leveraging its physical and chemical properties, are reviewed across multiple sectors, including agriculture, functional materials, and construction. Second, mainstream domestic and international processing methods are categorized into rapid cooling and slow cooling techniques based on cooling rates, with a comparative analysis of their workflows, advantages, and disadvantages. Finally, the variations in the physicochemical properties of steel slag under different processing conditions are examined, along with their underlying causes, followed by an outlook on future directions for steel slag treatment technologies and applications.

Due to the inaccurate prediction of the temperature drop of hot metal during the transportation of high-temperature hot metal and the high cost of measurement and test, an intelligent modeling and prediction technology is generated by combining numerical simulation with neural network and applied to the analysis of the temperature drop characteristics of high-temperature hot metal transportation. Taking the process of transporting high-temperature hot metal in a 320 t covered torpedo tank of a factory as the research object, the prediction simulation model of the temperature drop characteristics of high-temperature hot metal was constructed based on CFD technology, and the BP neural network model related to the temperature drop characteristics of high-temperature hot metal was established. The network model is trained by using the numerical simulation temperature field data as samples. The trained BP neural network intelligent model is used to predict and analyze the temperature drop characteristics of hot metal transport under various working conditions. Through the method visualization interface, the seamless connection between the neural network prediction module and the algebraic calculation module is realized. This model can predict the temperature through the neural network and can also perform the calculation of the energy-saving benefit formula to form a“prediction-calculation” integrated function chain. The output data include temperature drop data and energy saving benefit evaluation. The results show that the simulation analysis value of this method is in good agreement with the measured value, and it can be used to predict the temperature drop of high-temperature hot metal transport.

Through thermodynamic calculation, the slag-metal balance law and carbon-vanadium conversion law under different oxidizing conditions in the oxidation process of vanadium-containinghot metal were explored. The results show that lowing the oxygen potential of the system during the converter blowing process can reduce the burning loss of carbon under the premise of ensuring the normal oxidation of vanadium. A comparative test was carried out using three methods: oxygen-nitrogen segmented gas supply, oxygen-nitrogen mixed gas supply and oxygen injection gas supply. It was found that both of the two mixed gas supply schemes can reduce carbon burning loss, and oxygen-nitrogen mixed gas supply performs better. The industrial test of vanadium extraction was carried out by mixed gas injection. It was found that the carbon mass fraction at the end point of vanadium extraction increased by 0.06% and the carbon burning loss rate decreased by 2.17% during the normal oxidation of vanadium.

In the process of converter steelmaking, the amount of ingredients directly affects the quality of molten steel, smelting efficiency and economic cost. Traditional batching methods rely on manual experience and lack scientific basis. The second generation non-dominated sorting multi-objective genetic algorithm (NSGA2) with fast non-dominated sorting mechanism and significant advantages in dealing with multi-objective optimization problems is selected as the optimization algorithm. The model is constructed by integrating three factors of quality, blow loss and economic cost (cost and blow loss are the objective functions, quality is the constraint condition). Aiming at the problems of uneven distribution of the initial population and weak local search ability in the later iteration of the algorithm, two improved strategies of maximum and minimum Latin hypercube sampling and adaptive mutation factor are introduced to improve the optimization ability of the algorithm. Through the test of historical data, the improved second generation non-dominated sorting multi-objective genetic algorithm (INSGA2) can search for more Pareto optimal solutions under the premise of ensuring the quality of molten steel. The selected optimal batching scheme is expected to reduce the blowing loss of 0.012 2 and save the economic cost of 36 230 yuan, providing efficient and economical guidance for converter batching.

Alloy reduction refers to the reduction of the amount of alloy in the steelmaking process by optimizing the alloy composition and improving the production process without affecting the quality of steel. Reducing the addition of ferroalloys can not only reduce costs and increase efficiency, but also save ferroalloy resources and reduce carbon emissions in the process of producing ferroalloys. Taking the actual production data of HRB4Nb-8 as the research object, the Principal Component Analysis (PCA) method was used to effectively eliminate the interaction between variables for data dimensionality reduction, and 13 process parameters were determined as input vectors. The Sparrow Search Optimization Algorithm (SSA) was used to optimize Elman Neural Network (ENN) to construct a prediction model for Mn element yield.The hit rate the yield of Mn element predicted by the PCA-SSA-ENN prediction model is 86.67% within the error range of ±1%, and the hit rate is 96.67% within the error range of ±2%. The results show that the model can accurately predict the yield in advance. The addition of alloy according to the prediction results of this model can significantly reduce the element content fluctuation of the finished molten steel, and the amount of steel alloy added per heat is reduced by an average of 60.3 kg. For example, the company produces about 7 000 heats annually, and the amount of alloy added could be saved by about 413 t; the annual alloying cost could be saved by about 3.024 million yuan, and the carbon emission could be reduced by about 198.24 t.

To obtain therefining slag composition that is most conducive to actual production and has good desulfurization effect, five LF refining slags were adjusted through industrial tests, and the change rule of sulfur content in molten steel was studied. To clarify the desulfurization effect of refining slag, the complete melting temperature, viscosity, theoretical desulfurization capacity and desulfurization index (S_index) of refining slag were calculated. The desulfurization ability of refining slag is related to the content of CaO, and the mass ratio of CaO to Al₂O₃ has a great influence on the properties of refining slag. The results show that the sulfur capacity (C_S) increases infinitely with the increase in the mass ratio of CaO to Al₂O₃ in refining slag, and S_index increases first and then decreases with the mass ratio of CaO to Al₂O₃ in refining slag. WhenCaO/Al₂O₃(C/A) is 1.8-2.0, S_index reaches the maximum, indicating that the desulfurization effect is the best. When the complete melting temperature of the refining slag is lower than 1 600 ℃, the viscosity is at the lowest value, indicating that the fluidity of the refining slag is better at this time. Comprehensively considering the desulfurization ability, complete melting temperature and viscosity of the refining slag, when the mass fraction of CaO in the refining slag is within 55%-58%, C/A is 1.8-2.0, MgO mass fraction is not higher than 6%, and SiO₂ mass fraction is low(8%), the refining slag is beneficial to desulfurization.

High temperature tensile tests were performed on several low-alloyedaluminum killedsteels microalloyed by Nb,Nb-Ti,and Nb-Ti-V within the temperature of 850 to 1 050 ℃ using an MMS-200 thermal simulators to investigate their high-temperature hot ductility. At the same time,the thermodynamics and kinetics of the tested steels were calculated by Thermo-Calc software,and the tensile fracture morphology and precipitates were observed by SEM. The results show that for low-alloyed aluminum killed steel,within the tested temperature range of 850 to 1 050 ℃,the ferrite transformation and the precipitation of AlN and V(C,N) of the test steel have little effect on the hot ductility,and its significant deterioration is mainly caused by the nanoscale fine Nb(C,N). However,the Nb-Ti or Nb-Ti-V treated test steels will form (Nb,Ti)(C,N) or (Nb,Ti,V)(C,N) composite precipitated particles with larger size,which greatly reduces the effect on the hot ductility of the steel. Therefore,when producing the large-section continuous casting slabs with lower straightening temperatures,in order to reduce the occurrence of cracks on th surface of the large-section continuous casting slab,it is necessary that the straightening temperature should be increased to 910-940 ℃ for the low-alloyed aluminum killed steel containing 0.032%-0.046% Nb,or a trace amount of Ti should be added to effectively improve the high-temperature hot ductility of the steel,so that it can be straightened in the temperature range of 850 to 900 ℃.

The plastic strain accumulation and chip formation mechanisms in austenitic stainless steel Fe-25Cr-20Ni with different crystallographic orientations ({001}, {101}, {111}) were investigated under cyclic friction loading. Through multi-pass micro-scratch experiments combined with high-resolution characterization, it was found that crystallographic orientation significantly influences scratch morphology evolution and chip behavior: In single-pass scratching, the {001}0°,{101}30°,and {111}0° orientations exhibited the optimal resistance to plastic deformation. Multi-pass loading (1-10 cycles) led to a nonlinear increase in groove dimensions, with the most significant growth in width and depth occurring during the first two cycles. As the number of scratches increased, chip distribution transitioned from orientation-dependent to omnidirectional coverage. Additionally, work hardening effects dominated groove expansion by suppressing dislocation slip. Dislocation analysis revealed that shallow scratches exhibited significant dislocation multiplication during secondary scratching due to large dislocation density gradients, whereas deep scratches showed limited deformation due to dislocation saturation.

Under the premise that the hardness of both Cr14Mo4V and G30Cr15Mo1N martensitic stainless bearing steels meets the service requirements for bearing steels, selecting materials for special working conditions poses a significant challenge for engineering and technical personnel. This study comparatively investigates the microstructures and wear resistance under ring-on-block wear conditions of Cr14Mo4V and G30Cr15Mo1N steels. The results indicate that both steels exhibit a microstructure composed of a martensitic matrix with carbides. Cr14Mo4V steel contains numerous large-sized eutectic carbides, with an average carbide diameter over three times larger than that of G30Cr15Mo1N steel. In contrast, G30Cr15Mo1N steel features a uniform and fine microstructure, with approximately 10 times more carbides than Cr14Mo4V steel. Under ring-on-block wear conditions, the wear volume of Cr14Mo4V steel is about one-tenth that of G30Cr15Mo1N steel. Both steels demonstrate a mixed wear mechanism involving abrasive wear and oxidative wear. The high hardness and large carbides in Cr14Mo4V steel enhance its wear resistance by providing wear resistance and exerting a pinning effect that hinders the spalling of the martensitic structure during friction.

High-performance bridge steel is a critical material for the construction of advanced steel-structured bridges, and the strengthening and toughening of welds are key to enhancing the application performance of high-performance bridge steel. By controlling key parameters such as welding heat input and welding current, the microstructure of the weld can be regulated, which is an important approach to improve its impact toughness. The microstructural evolution of welds in 500 MPa-grade bridge steel under different welding currents was clarified, and the influence of microstructural evolution on weld impact toughness was analyzed. As welding current increases, the content of needle-like ferrite in the weld rises, leading to improved impact toughness. However, when welding current reaches 630 A, needle-like ferrite transforms into polygonal ferrite. The extensive interlaced arrangement of needle-like ferrite forms a “basket structure”, which extends the crack propagation path and thereby improves the impact toughness of the weld. Polygonal ferrite dissipates energy through uniform deformation and also slows down crack propagation. When the welding current is controlled between 600 and 630 A, the impact absorption energy of the weld at -40 ℃ exceeds 110 J.

In the process of preparing DC53/42CrMo composite materials by liquid-solid composite method, it is difficult to study the evolution law of bimetallic interface′s composition, microstructure and performance due to its small span and difficulty in sampling. Based on the characteristics of the bimetallic composite process, five experiments were designed by adjusting the mass ratio of DC53 to 42CrMo from 5∶1 to 1∶5 which were used to simulate the composition evolution of the bimetallic interface. Effects of composition evolutions on phase precipitation, CCT curves, and microstructure-property relationships were investigated systematically. The results show that with the decrease in the mass ratio of DC53 to 42CrMo, the contents of C, Cr, Mo, V, in the mixed composition steel decrease gradually, the CCT curve shifts to the left, the temperature of M_s and M_f point increases gradually, and the critical quenching cooling rate increases gradually, resulting in an occurrence of the transition from martensite to bainite, and then to pearlite. The carbides in the steel transform from M₇C₃, M₆C to M₃C types, and their number and size gradually decrease. The average microhardness of the steel matrix decreases from 744.5HV to 348.7HV, and the Rockwell hardness decreases from 62.8HRC to 34.9HRC.The limitation of sampling difficulty in traditional bimetallic interface research has been overcome by thermal simulation experiments, and the composition-microstructure-property relationship of the interfacial transition zone of bimetallic composites prepared by liquid-solid composite method is systematically revealed, which provides an effective strategy for the optimization and regulation of interfacial microstructure and properties.

With the comprehensive promotion of the“double carbon” strategy, the development of marine clean energy in China has entered a period of accelerated development. In order to improve the corrosion resistance of 304 austenitic stainless steel in seawater,0, 0.03 wt.% and 0.06 wt.% Nb were added respectively to stainless steel to study the effect of Nb content on its seawater corrosion resistance.The results show that the grain size of 304 austenitic stainless steel decreases obviously with the increase of Nbelement. When the Nb content in 304 austenitic stainless steel increases from 0 to 0.06 wt.%, the current density under potentiostatic polarization decreases from 8.72 to 3.60 mA/cm², and the breakdown potential (E_p) increases from 160 to 200 mV. According to the electrochemical impedance spectroscopy, with the increase of Nb content, the corrosion resistance of the passivation film is also improved, and the passivation film is more compact and stable. Through the Mott-Schottky test, it can be seen that the type of passivation film on the surface of 304 austenitic stainless steel is mainly n-type semiconductor, and the carrier density in the 0.06Nb passivation film is the smallest. X-ray photoelectron spectroscopy (XPS) analysis shows that the passivation film of austenitic stainless steel is mainly composed of iron and chromium oxides. In addition, the higher O^2-/OH^- ratio indicates that the self-healing ability of the passivation film is better. The O^2-/OH^- ratio, which increases with the increase of Nb content, can also explain the reason why the corrosion resistance of austenitic stainless steel after microalloying is enhanced.

Electric furnace refining stainless steel dust and blast furnace dust are typical secondary solid wastes in the iron and steel industry. They contain a large number of valuable metal components and have high recovery value. Blast furnace dust contains carbon. Mixing these two dusts to prepare carbon-containing briquettes can reduce the amount of foreign carbon added in the reduction process. Rotary hearth furnace process has strong adaptability of raw materials and simple process. The effects of raw material ratio, binder addition, molding pressure and holding time on the falling strength of wet carbon-containing briquettes and the compressive strength of dry carbon-containing briquettes were studied. The strength optimization mechanism was clarified, and the optimal preparation process parameters were obtained. The test results show that when the ratio of electric furnace refining stainless steel dust to blast furnace dust is 7∶3, the ratio of coking coal is 12.25%, the mass fraction of bentonite added is 5%, the mass fraction of water is 8%, and the pressure is 40 MPa, the falling strength of the wet block is 13.4 times/0.5 m, and the compressive strength of the dry block is 724.8 N, which meets the strength requirements of the rotary hearth furnace.