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

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

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

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

With the implementation of China's“dual carbon” strategy, energy conservation and emission reduction in the steel industry are urgently needed. Hydrogen-based reducing agents can significantly reduce carbon emissions in the ironmaking process.With the high-phosphorus oolitic hematite used as raw material to prepare self-fluxing pellets and hydrogen gas used as a reducing agent, the reduction process of self-fluxing pellets at 1 073 K is analyzed by thermogravimetric analysis. The microstructure, composition, and phase of the original ore, self-fluxing pellets, and reduction products are analyzed by XRD, SEM, and other methods to study the promoting effect in B₂O₃ on the reduction process of self-fluxing pellets. The results show that when the basicity of the pellets is 2.5, the reduction degree and metallization rate of the pellets first increase and then decrease with the increase in B₂O₃ mass fraction in the pellets. When the B₂O₃ mass fraction is 2%, the reduction degree and metallization rate reach the highest of 85.10% and 83.99%, respectively. This is because B₂O₃ has both promoting and inhibiting mechanisms on the reduction of pellets. An appropriate amount of B₂O₃ can destroy the oolitic structure of minerals and increase the porosity of the pellets, which is beneficial to the diffusion of hydrogen gas within the pellets and provides better kinetic conditions for reduction. However, excessive B₂O₃ in the pellets will consume too much CaO, causing the SiO₂ to combine with FeO to form fayalite, which hinders the reduction process.

Converter steel alloying process is an important production link of the converter-continuous casting process, and the accurate control and forecasting of the liquid steel temperature of this process has an important impact on the overall operation of the steelmaking section, especially the production rhythm of continuous casting and the accurate control of the temperature of the steel. To realize the accurate control and forecasting of alloying temperature of steel out of converter,to speed up the production rhythm and reduce the manual labor intensity,and to improve the low prediction accuracy of the mechanism model established based on the production process of a 120 t converter,by collecting a large amount of key data of the production,the artificial neural network model (BP), the particle swarm optimization BP model (PSO-BP), and the genetic algorithm optimization BP model (GA-BP) are used to predict the temperature of the steelwhich are optimized and compared, respectively. The results show that the model optimized by GA-BP algorithm has the best performance, where its average absolute percentage error P_MAE is 0.13%, root mean square error S_RME is 2.98 ℃, and the hit rate of the absolute value of the error≤5 ℃ reaches 94.85%.The model has been applied in the industry, and the empirical model prediction results are consistent with the measured temperature, where the hit rate of the absolute value of the error ≤5 ℃ is proved to be94.28%, improving the production efficiency, andplaying an important role in reducing costs and increasing efficiency in thesteelmaking process.

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

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

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

In view of softening and second phase precipitation phenomena occurring during coiling process of hot rolled strip steel, influence of different coiling temperatures on microstructure, dislocation density and second phase precipitation behavior of Ti microalloyed high-strength weathering steel for photovoltaic support is simulated, and mechanism of influence of coiling temperature on dislocation density of test steel is revealed by using a variety of characterization means. The results indicate that within the coiling temperature range of 540-660 ℃, as the coiling temperature increases from 540 to 660 ℃, the microstructure of the test steel evolves fromgranular bainite to granular bainite + polygonal ferrite and then to polygonal ferrite. The spacing of precipitates gradually decreases, while the dislocation density first increases and then decreases. At a coiling temperature of 600 ℃, the dislocation density reaches its peak at 2.25×10⁸ mm^-2, and the precipitate spacing is 56 nm. At this point, dislocation strengthening and precipitation strengthening exhibit the optimal synergistic strengthening effect, with a combined strengthening contribution up to 581 MPa.The dispersively distributed small precipitation phase in test steel generated in coiling processwill play a role in hindering dislocation movement, thereby reducing softening effect of coiling process.

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

Improving solidification organization structure is the key to reducing casting defects and enhancing alloy properties. Numerical simulation was used to study evolution of temperature field, solid-liquid interface, mushy zone, dendrite spacing and related solidification parameters of a low-cost second-generation single-crystal high-temperature alloy blade during LMC directional solidification, and accuracy of model was verified by results of metallurgical test measurements. Results show that temperature gradient at solid-liquid interface within blade is always kept above 10 K/mm during LMC directional solidification process, and higher temperature gradient can promote uniform growth of dendrites along a specific direction. Primary/secondary dendrite arm spacing in blade was calculated to be 160-300 and 34-46 μm. Increasing preheating temperature decreases solidification time, the width of mushy zone, and distance between solid-liquid interface and tin-liquid surface, and also raises temperature gradient and cooling rate at solidification interface, which results in an increase in the number of dendrites and a decrease in primary/secondary dendrite spacing in single-crystal blades.

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