The rapid development of the aluminum industry has led to a stockpile of red mud exceeding 1.5 billion tons, yet its comprehensive utilization rate remains below 12%. This massive accumulation not only occupies substantial land resources but also causes environmental pollution and resource waste. This review first systematically outlines the sources, distribution, and environmental hazards of red mud, and analyzes its characteristics in terms of chemical and mineral compositions. It then summarizes the current status and developmental trends in red mud treatment and comprehensive utilization, with a focus on reviewing research progress in its applications, such as in building materials, metal recovery, and environmental remediation. Finally, future prospects are discussed. The paper highlights the need to strengthen technological innovation to address the challenges of high alkalinity and heavy metal stability. It proposes achieving efficient resource utilization of red mud through the co-processing of multi-source solid wastes and the tiered utilization of all its components. Emphasis is also placed on demonstrating practical projects, improving the standard system for various application fields, and leveraging market drivers to promote the large-scale and high-value utilization of red mud resources.

The iron and steel industry is one of the major source of carbon emissions, and advancing pellet technology is one of the effective measures to achieve the "dual-carbon" goals. Excessive reduction swelling of pellets can degrade reactor permeability and even leads to production accidents. This paper systematically reviews the primary mechanisms of reduction swelling in iron ore pellets, including lattice expansion from phase transformations, iron layer cracking due to gas pressure, structural damage induced by carbon deposition, cracking resulting from uneven reduction stresses, and the precipitation morphology of nascent iron. Studies have shown that regulating the formation of iron whiskers is a key breakthrough in inhibiting malignant expansion, while reduction swelling is significantly influenced by preheating/roasting parameters, porosity, gangue composition, and reduction conditions. Key measures to suppress pellet swelling involve optimizing ore blending, rational control of basicity, refining preheating/roasting processes, and restricting harmful element intake. It provides a theoretical foundations and technical pathways for optimizing pellet performance and advancing low-carbon ironmaking technologies.

With the development of the electronic information industry and the intelligent revolution, China′s electronics sector has imposed increasingly stringent demands on the quality and supply of semiconductor raw materials. In the semiconductor industry, copper—particularly high-purity copper—demonstrates significant market potential due to its excellent physical and chemical properties, such as high electromigration resistance, electrical conductivity, thermal conductivity, ductility, low dielectric constant, and corrosion resistance. However, the quality and quantity of its production have consistently fallen short of industry requirements. Hydrometallurgy is the main process for preparing electrolytic copper, which is used for the production of high-purity copper. It enjoys advantages such as simple preparation method, mature process, low production cost, and low energy consumption, and thus dominates the high-purity copper production industry. However, during the process of preparing high-purity electrolytic copper, the differences in the preparation techniques and parameter control result in significant fluctuations in the quality of high-purity electrolytic copper. This paper discusses different electrolytic copper production routes, provides a detailed analysis of the advantages, disadvantages, and implementation cases of various production processes, and summarizes the strengths and challenges of ultra-high-purity metal preparation methods. Finally, based on the current status of production and demand for high-purity electrolytic copper in China, a forward-looking perspective is presented. Accelerating the industrial production and construction of high-purity electrolytic copper will be Accelerating the industrial-scale production and construction of high-purity electrolytic copper will be further conducive to accelerating the localization process of high-purity electrolytic copper needed for the development of China′s semiconductor industry and solving the problem of China′s reliance on imported raw materials in high-end, precision and cutting-edge fields.

Platinum group metals (PGMs) play a vital role in the automotive, petrochemical and electronic devices industries due to their unique physical properties and excellent catalytic activity, rendering them indispensable strategic resources for the country. However, China's PGM mineral resources are scarce with low ore grades and high mining costs. Consequently, recovering PGMs from secondary resources, particularly the large quantities of spent PGM catalysts has become the primary source of these metals. Based on the operating conditions, current PGM enrichment processes can be divided into pyrometallurgical and hydrometallurgical processes. Pyrometallurgical processes feature high processing capacity and short process flows, making them suitable for large-scale operations, but they are energy-intensive and cause considerable environmental pollution. In contrast, hydrometallurgical processes operate under milder reaction conditions and good selectivity for specific materials, though they involve longer process flows and high reagent consumption. After enrichment, PGMs in the solution require purification and refining. The precipitation method is applicable for enriching solutions with high metal ion concentrations but tends to introduce impurities. Solvent extraction yields high-purity products, yet the extractants are often toxic and volatile which increases operational difficulty. Ion exchange achieves high separation efficiency and low pollution, but it is costly and severely restricted by the solution system. This paper summarizes common enrichment processes and conducts detailed analysis of their respective advantages and disadvantages. It also overviews different purification processes and elaborates on their merits and demerits. On this basis, the paper outlines future research directions for PGM recovery from spent catalysts, providing new insights for promoting efficient recycling of secondary PGM resources and developing economical, environmentally friendly, and intelligent recovery processes.

The electric arc furnace (EAF) short-process steelmaking serves as a pivotal pathway for achieving the steel industry′s dual carbon goals of "carbon peaking and carbon neutrality". A systematic review of research advancements in EAF energy-efficient supply technologies and their control models was provided. It analyzes the multi-energy structure of EAFs and evaluates key supply technologies for different energy types, systematically introduces the application characteristics and pros/cons of physical heat enhancement techniques, electrical energy optimization methods, and chemical energy utilization strategies. Furthermore, an outlook has been provided on the innovative breakthrough directions of the current multi-energy supply technologies. Finally, it systematically examines the research progress and development trends of mechanistic and statistical models for efficient EAF energy supply, delves into the material-energy conversion mechanisms under electro-oxygen synergy, clarifies that furnace charge melting and molten pool reactions constitute critical components in developing high-efficiency energy utilization technologies, and explores intelligent development pathways for EAF energy models. These findings provide valuable references for subsequent intelligent development of multi-material structure EAF models and precise control of steelmaking processes.

As a key area of global carbon emissions, the steel industry's low-carbon transformation is of vital importance, and increasing the proportion of scrap steel usage is a crucial measure for steel enterprises to achieve carbon reduction. However, at present, there are two core problems in the carbon accounting of scrap steel, inconsistent standards and difficulty in coordinating technology and economy, which urgently need to be solved. This article aims to explore the optimized path for scrap steel utilization through multi-standard comparison and modeling, helping enterprises balance carbon reduction and benefits. The research systematically compared four major standards, the LCI methodology of the World Steel Association, the "Evaluation Method for Low-Carbon Emission Steel" of the China Iron and Steel Association, the Responsible Steel (RS) standard, and the German LESS, and analyzed the differences in the definition, classification, and accounting boundaries of scrap steel. In light of the production characteristics dominated by converters in China, a collaborative optimization model for thermal balance, material balance, and carbon emission-cost was constructed. The effects of carbon-based/silicon-based heat supplements and preheating of scrap steel on the scrap steel ratio were quantified, and the roles of scrap steel yield and the price difference between molten iron and scrap steel were explored. The results show that the "Evaluation Method for Low-Carbon Emission Steel" is more in line with the national conditions of China's steel production due to the introduction of localized parameters and is suitable to be used as a unified benchmark for domestic carbon accounting. Among the supplementary heating measures, preheating scrap steel is the optimal carbon reduction technical path, which can increase the scrap steel ratio by approximately 9% and has the least impact on the quality of molten steel. Coke supplementary heating can increase the scrap steel ratio by approximately 7%, while ferrosilicon supplementary heating only raises it by about 1%. In terms of the coordinated optimization of the economy and the environment, when the price difference between molten iron and scrap steel exceeds 300 RMB/t (LCI methodology) or 100 RMB/t (evaluation method for low-carbon emission steel), increasing the scrap steel ratio can achieve a win-win situation of carbon reduction and cost. In addition, the scrap steel harvest rate has a significant impact on the stability of material balance and economic and environmental benefits. Improving the quality of scrap steel is the core guarantee for high-proportion scrap steel smelting.

High strength low alloy (HSLA) steel is widely used in building and bridge construction, oil and gas pipelines, ships, and offshore platforms due to its excellent comprehensive properties and cost advantages. The yield ratio serves as a key indicator in the development and application of HSLA steel. This review first summarizes the yield ratio of single-phase steels, such as ferritic, pearlitic, and martensitic steels, as well as ferrite/austenite multi-phase steels, at different strength levels. In general, steels with higher yield strength exhibit higher yield ratio. The introduction of ferrite or austenite phases in steel is beneficial for reducing the yield ratio. Subsequently, recent advances in the design of multi-phase microstructure and the control of rolling and heat treatment processes for high-strength steels with low yield ratio are discussed. Finally, progress in the use of machine learning and artificial intelligence for assisting the study of mechanical properties of HSLA steels is introduced. Achieving a favorable combination of low yield ratio, high toughness, and high plasticity is a development trend in HSLA steel. Constructing multi-phase, metastable, multi-scale, and multi-morphological microstructures provides an effective approach for developing high-strength, high-toughness, and low yield ratio steels. And the integration of physical metallurgy and data science is becoming a key pathway for precise microstructure design of such steel grades.

High-strength automotive beam steel serves as a critical component for supporting vehicle mass and external loads, requiring high strength, high toughness, and excellent cold formability. However, hard inclusions such as Al₂O₃, magnesium-aluminum spinel, and calcium aluminate present in the steel do not readily deform during rolling. Improper control will damage product performance. Cerium (Ce) plays a role in modifying inclusions and refining grain structure in steel. It can transform Al₂O₃, Mg-Al-O and Ca-Al-O inclusions into rare-earth inclusions such as CeAlO₃ and Ce₂O₂S. These cerium-containing inclusions can act as nucleation sites, refining the solidification structure of the steel. Through melting and casting experiments using a high-temperature tube furnace, combined with scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and thermodynamic calculations, the effects of different Ce content on inclusion modification and as-cast structure refinement in high-strength beam steel were systematically studied. The results show that as the Ce content in the steel increases, the inclusion modification sequence follows CeAl₁₁O₁₈→CeAlO₃→Ce₂O₃→Ce₂O₂S→CeS, with the final modified product depending on the Ce content. When the mass fraction of Ce is 0.005 5%, the modified inclusions are Ce-Al-O types, exhibiting polygonal or (near-)spherical morphologies due to genetic effects and modification-induced spheroidization. When the mass fraction of Ce reaches 0.018 0%, the inclusions are further modified into Ce-O-S types with spherical morphologies, showing characteristics of aggregation and growth, while the originally angular Mg-Al(-Ti)-O inclusions disappear. Ce effectively reduces the average size of inclusions and decreases the number of large-sized inclusions. As the Ce content increases, the number of inclusions first decreases and then increases, with the smallest average size and lowest quantity observed at a Ce mass fraction of 0.005 5%. Additionally, Ce exhibits a grain-refining effect in steel. Both Ce-Al-O and Ce-O-S inclusions promote solidification nucleation, with the most significant refinement of the as-cast microstructure achieved at a Ce mass fraction of 0.018 0%. Thermodynamic calculations further elucidate the formation mechanisms of the relevant inclusions.

To systematically investigate the influence of mass fraction of Y₂O₃ and w(CaO)/w(Al₂O₃) on the physicochemical properties of the CaF₂-CaO-Al₂O₃-MgO-Y₂O₃ slag systems, this study addresses the severe burning loss of the Y element during the electro-slag remelting process of Y-containing rare earth steels. It proposes improving slag system performance by adding Y₂O₃ and adjusting the w(CaO)/w(Al₂O₃), thereby increasing the yield of Y. Experiments were conducted to prepare five slag systems with different mass fractions of Y₂O₃ and four slag systems with different w(CaO)/w(Al₂O₃) values. Various testing and analytical methods were comprehensively utilized, including an X-ray diffractometer, an X-ray fluorescence spectrometer, hemispherical melting temperature testing, rotating cylinder viscosity measurement, a Fourier transform infrared spectrometer, and a scanning electron microscope, to conduct a systematic study on the phase composition and content, melting characteristics, viscosity changes, structural features, and precipitated phase characteristics of the slag system. The aim is to provide theoretical support for optimizing slag composition, suppressing the burning loss of the Y element, and improving its yield. The results indicate that the addition of Y₂O₃ promotes the formation of the CaYAlO₄ phase. As the mass fraction of Y₂O₃ increased from 0 to 20%, the melting temperature of the slag first decreased and then increased, while the viscosity first increased and then decreased, with the optimal Y₂O₃ mass fraction of 15%. With the increase of the w(CaO)/w(Al₂O₃) from 0.8 to 1.4, the characteristic peaks of the CaYAlO₄ phase in the slag systems gradually intensified, the melting temperature and viscosity of the slag systems decreased, and the proportion of needle-like CaYAlO₄ in the slag systems increased. The decrease in viscosity might be primarily attributed to the depolymerization of[AlO_nF_4-n]^- tetrahedral complexes and the transformation of[AlO₄]^5- tetrahedra into[AlO₆]^9- octahedra induced by the elevated w(CaO)/w(Al₂O₃). The low viscosity led to the reduction of ionic clusters migration resistance, which in turn reduced the energy potential barrier for nucleation and crystal growth, accounting for the increase in the percentage of CaYAlO₄. The needle-like morphology of CaYAlO₄ may be affected by the growth mechanism controlled by screw dislocations. Based on the above discussion, the optimal slag composition is determined as follows, Y₂O₃mass fraction of 15%, w(CaO)/w(Al₂O₃) is 1.4. The melting temperature of this slag ratio is 1 346 ℃, and its viscosity at 1 600 ℃ is 0.28 Pa·s.

Copper, as a foundational material for the global transition to new energy industries, is facing increasing demand. The rapid development of the copper industry is accompanied by substantial consumption of minerals, energy, and water resources, while also generating significant volumes of wastewater and other pollutants, imposing severe environmental pressure. Water serves as both a critical resource and an essential medium in metallurgical processes, with its consumption directly linked to wastewater generation. Therefore, this study takes a typical pyrometallurgical copper smelting enterprise as a case to systematically analyze the characteristics of water metabolism throughout the entire process, identify key water-saving stages, propose water network optimization strategies, and promote the green transformation and sustainable development of the copper industry. Using material flow analysis, the study quantifies the relationships among water consumption, wastewater discharge, and recycling from a holistic process perspective. It integrates all water-use processes into a water balance system, establishes an optimization model and evaluation index system for the water network of the copper smelting enterprise, and proposes a hierarchical water-use strategy based on a "graded treatment-cascading utilization-closed-loop reuse" framework. The results show that after optimization, the enterprise's fresh water consumption decreased from 15.74 m³/t to 12.51 m³/t, a reduction of 20.52%. The recycled water usage increased from 949.67 m³/t to 1 274.54 m³/t, a rise of 34.21%. Water resource efficiency improved by 68.04%, the water recycling rate increased from 98.2% to 98.7%, system reclaimed water usage rose from 1.30 m³/t to 4.05 m³/t, and wastewater discharge decreased from 5.05 m³/t to 4.43 m³/t. This study reveals the characteristics of water flow in copper smelting processes, proposes hierarchical water-use strategies and water network optimization methods, providing a feasible technical pathway for efficient water resource management and near-zero discharge. Future work could further integrate intelligent monitoring and control technologies to achieve dynamic optimization and refined management of water systems.

With the acceleration of the green and low-carbon transformation in the steel industry, direct reduced iron (DRI), as a clean raw material for electric arc furnaces (EAF) smelting, plays a significant role in reducing carbon emissions and energy consumption. However, the impact of a large proportion of DRI in the EAF on smelting parameters and costs is still unclear. Based on production data, a material energy balance model based on the law of conservation of mass and energy was established. The influence of a large proportion of DRI on the smelting parameters was studied, and the smelting costs were also calculated. The analysis shows that, for every 20% increase in the mass fraction of DRI, the slag volume, steel material consumption, oxygen and lime consumption increase by 28.7, 26.5, 7.2 and 8.3 kg/t respectively, and the electricity consumption increases by 30.2 kW·h/t, and the metal yield rate decreases by 2.1%. When the ratio of DRI is 100%, for every 1% increase in carbon content, the oxygen consumption increases by 14.6 kg/t, the electricity consumption decreases by 8.3 kW·h/t; for every 2% increase in metalization rate, the electricity consumption decreases by 25.2 kW·h/t; for every 100 ℃ increase in the preheating temperature, the electricity consumption decreases by 19.4 kW·h/t. When the scrap price is 2.4, 2.7, 3.0 and 3.3 yuan/kg, according to the smelting cost calculation, the price of DRI is below 2.03, 2.3, 2.56 and 2.83 yuan/kg, respectively, the EAF using DRI will be more cost-competitive.

To address the issue that the excessive strength of hot-rolled ultra-low carbon steel sheets is detrimental to subsequent cold rolling and forming, deformation in the austenite-ferrite two-phase zone can be applied to reduce strength, but this significantly increases deformation resistance during hot rolling. Therefore, compression deformation of low-carbon steel in the austenite-ferrite two-phase region (773-845 ℃) was conducted using a Gleeble-1500 thermomechanical simulator. Optical microscopy (OM), scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD) were employed to investigate the effects of different deformation temperatures and strains on peak stress and microstructure, aiming to obtain process parameters that reduce deformation resistance in the two-phase zone and to analyze the corresponding softening mechanisms. The results show that the microstructure of the steel after two-phase zone deformation consists of ferrite and pearlite. Under a constant strain rate of 1 s^-1, strains of 30% or 60%, and deformation temperatures ranging from 775 ℃ to 825 ℃, dynamic recrystallization is difficult to occur when the specimen is deformed at a low temperature of 775 ℃ with a small strain of 30%. During deformation, the microstructure is dominated by coarse grains that have only undergone recovery and growth. Under these conditions, the ferrite grain size reaches a maximum of 55.4 μm, and the deformation resistance is minimized at 103 MPa. The primary mechanism for the reduction in deformation resistance in the two-phase zone under these process parameters is grain coarsening. Investigating the influence of deformation process parameters in the two-phase zone on the deformation resistance of low-carbon steel is of significant importance for achieving precise control of deformation resistance in industrial production and effectively reducing the strength of hot-rolled plates.

In response to the issues caused by reduced supply of high sulfur low silicon ore powder on the Shougang pellet production line consisting of a grate-rotary kiln-annular cooler, including insufficient sulfur source for the acid production system, decreased magnesium to aluminum ratio in the blast furnace, and deteriorated slag fluidity, a systematic study was conducted on the feasibility of using highsulfur boron-containing iron powder (HSBC, containing B₂O₃ 5%, MgO 10.18%, S 1.0% by mass) to replace Peruvian fines in the production of acid pellets. The phase composition microstructure and thermal decomposition characteristics of HSBC were characterized using a combination of X ray diffraction reference intensity ratio (XRD-RIR), scanning electron microscope energy dispersive spectroscopy (SEM-EDS), and thermogravimetric analysis differential scanning calorimetry (TG-DSC) method. Five gradient tests with HSBC mass ratios of 0, 2%, 4%, 6%, and 8% were designed and implemented on an industrial 10 kg scale disc pelletizer grate machine rotary kiln and annular cooler line for green pellet preparation, basket roasting and sampling detection. The results show that HSBC particles have a rough surface and a fibrous structure. Their particle size is relatively coarse with 72.6% below 74 μm complementing the extremely fine Macheng powder in particle size distribution. This complementarity increased the drop strength of green pellets from 6.2 times to 8.5 times. TG-DSC analysis revealed an exothermic peak at 379 ℃ corresponding to the conversion of Fe₃O₄ to Fe₂O₃ and an endothermic peak between 661.7 and 916 ℃ associated with sulfide oxidation dolomite decomposition and ludwigite lattice reconstruction with a total weight gain of 2.9%. The roasted pellets exhibited a core shell structure characterized by a liquid phase shell and a porous core with porosity increasing from 17.7% to 25.9%. As the HSBC mass ratio increased from 0 to 8%, pellet reducibility decreased from 58.50% to 50.32% while reduction swelling increased from 10.98% to 22.34%. The compressive strength after one hour of reduction improved by 169 N and the softening temperature interval Δt widened from 91 ℃ to 115 ℃. Considering metallurgical performance indicators and blast furnace adaptability, the optimal HSBC addition ratio is determined to be 5%. At this ratio, the compressive strength of the finished pellets reached 3 173 N, the desulfurization rate is 91.5% and the sulfur input is 1 117 mg/m³, which is close to the baseline level. Additionally the pellets demonstrated good reducibility at 55.02% and a controllable reduction swelling rate of 16.36%. The research findings provide a theoretical basis and technical support for the large scale application of high-sulfur boron-containing iron powder in pellet production.

This study investigated the effects of rare earth(RE) and magnesium treatments on non-metallic inclusions in ultra-high purity (UHP) 316L austenitic stainless steel, aiming to enhance steel cleanliness to meet the stringent requirements for semiconductor equipment materials. Traditional aluminum deoxidation processes produce alumina, which is prone to shedding during service and contaminates the entire semiconductor processing system. Although rare earth and magnesium are considered potential alternative deoxidizers, systematic studies on their combined treatment process, particularly the influence of addition sequence on inclusions in UHP 316L stainless steel, remain insufficient. Using a VIM+VAR duplex process, three deoxidation routes were designed, RE (Y) treatment only, Mg-Ce sequential treatment, and Ce-Mg sequential treatment. The effects of each process, under industrial production conditions on the size, distribution, type, and rating of inclusions were systematically examined. Inclusion characteristics and their evolution at various processing stages were evaluated using metallographic microscopy, SEM-EDS, and Thermo-Calc thermodynamic simulations. The results demonstrate that in VIM+VAR smelting of UHP 316L stainless steel, the Ce-Mg sequential deoxidation sequence is the most effective strategy for high-level inclusion control. This approach results in the lowest inclusion distribution density and smallest average equivalent diameter in VIM+VAR samples, with no large inclusions (≥8 μm) observed. The fine Type D inclusion rating is below 0.5, meeting industry standards for UHP 316L stainless steel. In contrast, the Mg-Ce treatment shows poor inclusion control due to severe premature magnesium loss, which limits effective synergy with rare earth. The proper RE-Mg addition sequence fully utilizes the strong deoxidation capability of rare earth elements and the bubble flotation and stirring effects of magnesium vapor, providing a key process route for achieving high cleanliness control in UHP 316L stainless steel.

With the advancement of green and low-carbon transformation in the steel industry, the demand for comprehensive utilization of solid wastes in the metallurgical sector continues to grow. Carbide slag, a high-calcium solid waste generated by the chemical industry, not only occupies land resources but also poses environmental risks due to its large-scale accumulation. As a high-calcium solid waste, carbide slag holds significant potential for replacing conventional calcium-based fluxes in iron ore sintering. This study aimed to systematically investigate the feasibility of using carbide slag as a substitute for conventional fluxes in iron ore sintering and its impact mechanism on the sintering and mineralization processes. Mineralogical analyses of carbide slag, limestone, and quicklime were conducted using XRF, XRD, laser particle size analyzer and thermogravimetric analyzer. The results indicate that compared to conventional fluxes, carbide slag exhibits higher CaO content, finer particle size, lower thermal decomposition temperature and higher thermal stability, demonstrating its suitability as a sintering flux. Through fundamental sintering characteristic tests and micro-sintering experiments, combined with the mineralogical properties of carbide slag, the effects of its substitution for conventional fluxes on sintering characteristics and the mineral phase structure of sinter were systematically analyzed. The results show that as the substitution ratio of carbide slag increases from 0 to 60%, the assimilation temperature decreases, while the fluidity of the liquid phase, the strength of the binding phase and the formation capacity of calcium ferrite improve, promoting the development of an interwoven-corroded structure. However, when the substitution ratio exceeds 60%, although the assimilation temperature continues to decrease, the fluidity of the liquid phase and the formation capacity of calcium ferrite decline, accompanied by an increase in silicate minerals and porosity, leading to a deterioration in the mineral phase structure of the sinter. At a substitution ratio of 60%, the sinter exhibits a uniform mineral phase structure, the highest content of calcium ferrite, predominantly in acicular and columnar forms. The findings of this study provide new insights into the resource utilization of carbide slag and the cost reduction and efficiency improvement in sinter production.

In the blast furnace smelting process, the uniformity of pellet size has a significant impact on the smooth operation of the blast furnace. However, in the industrial pelletizing process, traditional manual screening methods are still used on-site. These methods are inconvenient for direct and continuous measurement of pellet size and have large measurement errors, making it difficult to meet the requirements of real-time measurement. Therefore, this paper proposes a non-contact online method for measuring pellet size. Based on the YOLOv11 model, a multi-scale enhanced upsampling module (MEUM) is introduced to replace the original upsampling structure. Multi-scale feature fusion and edge enhancement design improve the representation ability for different particle sizes and fuzzy boundaries. A local importance attention (LIA) mechanism is embedded in the backbone network to adaptively enhance the response of key regions, improving the robustness of target features in complex backgrounds while maintaining the network's lightweight nature. Furthermore, on this basis, an edge contour-Hough circle joint detection method is proposed to calculate the pellet size. The minimum circumscribed circle is obtained by extracting the edge contour of the processed mask, and then matched and screened through multi-scale Hough circle detection to obtain a stable and reliable fitted circle and calculate the particle size. The results show that the mAP_50-95(The average of the average accuracies calculated under multiple thresholds ranging from 0.50 to 0.95 for IoU) of box detection of the improved model increases from 0.885 to 0.906. The recall rate of mask detection increases from 0.993 0 to 0.999 7, and its mAP_50-95 increases from 0.833 to 0.847. Compared with the other four comparative models, this model achieves the optimal performance. Meanwhile, the maximum error between the proposed pellet size measurement method and the ImageJ measurement method remains within ±1.7 mm, with an average relative error of 3.98%. The proposed pellet size detection method can efficiently handle pellet particle size identification tasks in complex industrial environments and has broad application prospects in the field of intelligent metallurgical industry, providing new ideas and methods for non-contact pellet size detection.

By adopting an appropriate alloy preparation method and element doping to regulate the composition and microstructure of alloy ingots, metal materials can be modified, which is an important means to address the problems of Sm element volatilization, poor preparation stability, and difficult microstructure control in SmFe₁₂-based rare earth alloys. Based on experimental phenomena, it was determined that induction melting method was more suitable for the preparation of SmFe₁₂-based rare earth alloy ingots than arc melting method. Zr, Co, Cu and Ti were doped into SmFe₁₂ alloy ingots, and the doped ingots were subjected to homogenization heat treatment at 1 100 ℃ for 36 h. The phase composition and microstructure were characterized and analyzed using XRD and SEM. The mechanism of the effect of element doping on the alloy phase composition was studied. The effect of element doping was analyzed from the perspective of thermodynamic parameters such as mixing enthalpy, mixing entropy, Gibbs free energy and atomic size difference. Combined with the experimental results and thermodynamic analysis, the problems of poor stability and difficult preparation of SmFe₁₂ alloy ingots have been addressed by element doping. Under the action of interatomic forces, Sm_0.8 Zr_0.2 Fe_8.5 Co₂ Cu_0.5 Ti alloy is composed of SmFe₁₁ Ti phase, SmCu₅ phase and α-Fe phase. Zr and Ti atoms exist in the form of solid solution in the SmFe₁₁ Ti phase, and the solid solubility of Zr and Ti is higher in the SmFe₁₁ Ti phase around the α-Fe phase. Under the attractive force of Cu atoms on Sm atoms and the repulsive force of Cu atoms on Fe atoms and Co atoms, Cu atoms are precipitated to form SmCu₅ phase, which promotes the decomposition of SmFe₁₁ Ti phase and leads to the decrease in SmFe₁₁ Ti phase content and the increase in α-Fe phase content. The results show that, the doping of Zr, Co, Cu and Ti elements improves the stability of the SmFe₁₂-based alloy's main phase while precipitating the SmCu₅ phase, which is expected to further optimize the magnetic properties of the SmFe₁₂-based alloys. High-quality raw materials are provided for future powder preparation, and control of the grain size and distribution of SmCu₅ phase becomes a new research direction.

This study systematically investigates the influence of the sequence between rolling and precipitation processes on the microstructural evolution and high-temperature mechanical properties of heat-treatable Al-Mg-Si-Mn alloy, aiming to provide a theoretical basis for optimizing the manufacturing process and enhancing the overall performance of such alloys. Al-Mg-Si-Mn alloy slabs with excellent surface quality were successfully produced using an independently developed twin-roll casting (TRC) technique. Microstructural analysis shows that under the precipitation-rolling (P-R) process with prolonged precipitation treatment, the average size of precipitates is approximately 70 nm, with a number density of 15 μm^-2. In contrast, the rolling-precipitation (R-P) process combined with short-duration precipitation treatment increases the average precipitate size to 90 nm and raises the number density to 17 μm^-2. Under identical precipitation durations, the R-P process leads to a pronounced spheroidization trend of the dispersion phases, accompanied by the formation of extensive recrystallized microstructures. High-temperature mechanical tests indicate that at 350 ℃, the R-P processed alloy achieves a tensile strength of 83 MPa with an elongation of 5%, while the P-R processed alloy exhibits a tensile strength of 65 MPa and an elongation of 6%. The study demonstrates that the R-P process promotes the precipitation of a greater number of strengthening phases within a shorter time, thereby significantly improving the mechanical properties of the alloy under high-temperature conditions. This provides new insights for optimizing short-process routes for heat-treatable strengthened alloys.

Vanadium-titanium magnetite (VTM) is a composite mineral primarily composed of iron, vanadium and titanium, possessing extremely high comprehensive recovery and utilization value. The non-blast furnace smelting process of VTM has the advantages of a short process, low carbon emissions, and a high titanium recovery rate. Due to the complex mineral composition and structure of VTM, non-blast furnace smelting faces issues such as low reaction efficiency, insufficient metallization rate and difficulties in element separation. In addition, when the reduction temperature exceeds 1 200 ℃, maintaining the reducting atmosphere with heating equipment poses a technical challenge, so the current non-blast furnace smelting process for VTM has not been industrialized. The use of additives can significantly alleviate these issues. Due to their different characteristics and mechanisms of action, various additives exhibit significant variations in their effects on the reduction-separation of VTM after use. This paper reviews the research progress on the impact of different additives, including sodium-based, calcium-based, magnesium-based, and other additives such as borax, as well as composite additives, on the reduction-separation of VTM. It summarizes the enhanced reduction mechanisms and process routes of different additives, and analyzes their respective advantages, issues, and development prospects. It is believed that the sodium-based low-temperature reduction-melting separation process and the B₂O₃ composite additive low-temperature reduction-magnetic separation process have promising development prospects and align with the requirements of low-carbon development, but more research is still needed to verify them. In the future, focus should be placed on the design of composite additives, emphasizing the synergistic optimization of reduction-separation and environmental friendliness.

Complex corrosion environments such as strong irradiation, variable climate and high temperature high humidity high salt condition in marine areas impose higher requirements on high-performance weathering bridge steel.A new low C+(Cu-Cr-Ni) alloyed Q550qENH weathering steel was taken as the research object while ordinary Q355B carbon steel served as the reference steel to investigate corrosion behavior in simulated marine atmospheric environment. Cyclic immersion test, scanning electron microscope(SEM), X-ray diffractometer(XRD) and electrochemical test were employed to study corrosion weight loss and rust layer evolution of Q550qENH steel in 3.5% NaCl solution at different corrosion cycles(72, 168, 360, 576 h). The results show that during 72 h to 360 h of corrosion, the surface rust layer of Q550qENH steel transforms from partial coverage to full coverage, and the corrosion weight loss rate increases rapidly with time extension. X-ray diffractometer analysis of corrosion products indicates that corrosion products of the experimental steel at different cycles consist of α-FeOOH, γ-FeOOH and Fe₃O₄, among which α-FeOOH accounts for the highest proportion, followed by Fe₃O₄ and γ-FeOOH. When corrosion time extends to 576 h, the corrosion weight loss rate of the experimental steel increased slightly, the corrosion products are mainly α-FeOOH, and the content of γ-FeOOH decreases. Electrochemical test results demonstrate that as corrosion time extends from 72 h to 576 h, the polarization curves of Q550qENH steel all shift to the right, and corrosion current density shows a trend of first increasing and then decreasing. This phenomenon means that, with the progress of corrosion the rust layer on Q550qENH steel surface gradually thickens and its compactness enhances. Compared with ordinary Q355B carbon steel, the weight loss rates of Q550qENH steel at different corrosion cycles are 53.56%, 67.38%, 96.45% and 74.85% of those of Q355B, respectively. In the later stage of corrosion, the content of α-FeOOH in corrosion products of Q550qENH steel is significantly higher than that of Q355B steel, and the rust layer is denser.This effectively inhibits the penetration of corrosive media into the matrix, thus endowing Q550qENH steel with better corrosion resistance than Q355B steel.

To meet the construction requirements of liquid ammonia transport ships, this study adopted a low-carbon Nb-Ti-Al composite microalloyed composition design combined with controlled rolling and controlled cooling (CRCC)processes to develop the low-temperature steel plate LT-FH32. Through tensile tests, low-temperature impact tests, metallographic observation and scanning electron microscopy analysis, systematic investigations were conducted on the variation of the microstructure and properties of the test steel with rolling process. The results indicate that with decreasing finish rolling temperature, the microstructure of the test steel transitions from a multiphase structure consisting of polygonal ferrite+quasi-polygonal ferrite+acicular ferrite to a dual-phase structure of polygonal ferrite+bainite. The volume fraction of the soft phase, polygonal ferrite increases from 37% to 63% and the hardness difference between soft and hard phases rises from 68HV0.01 to 119HV0.01. With further application of post-rolling relaxation process, the microstructure evolves into a dual-phase structure of polygonal ferrite+large-sized lath or blocky M/A (Martensite/Austenite) constituents. The volume fraction of polygonal ferrite continues to increase to 89% and the hardness difference between soft and hard phases further increases to 379HV0.01. This microstructural evolution leads to a decrease in yield strength, initial increase followed by decrease in tensile strength and a continuous reduction in the yield-to-tensile ratio. The crack initiation energy first increases then decreases while the crack propagation energy declines continuously, and the ductile-brittle transition temperature rises. When the finish rolling temperature is 770 ℃ and direct water cooling is applied after rolling, the test steel exhibits moderate strength margins with yield strength of 406 MPa and tensile strength of 519 MPa ensuring good safety performance. The yield-to-tensile ratio is 0.78, and the low-temperature toughness reserve is sufficient with ductile-brittle transition temperature below -80 ℃, thus achieving the optimal comprehensive performance.

Electric arc furnace (EAF) steelmaking technology, featuring advantages such as a short process flow, low energy consumption, and reduced carbon emissions, serves as a critical pathway for the low-carbon transition in the steel industry. However, during the smelting process, this technology faces challenges including multivariable coupling and strong nonlinear dynamic characteristics. Leveraging its robust data processing and nonlinear mapping capabilities, machine learning technology exhibits significant application potential in EAF steelmaking production. This paper systematically summarizes the research progress of machine learning applications in the core links of electric arc furnace steelmaking. In the process of electric arc furnace steelmaking, within the field of molten steel property regulation, machine learning technologies have significantly improved the prediction accuracy of end-point carbon content and temperature through multi-algorithm fusion, but still need to overcome challenges such as data dependence and dynamic working condition adaptability. In terms of precise energy consumption management and control, semi-supervised learning technology effectively taps the value of unlabeled data to optimize energy input efficiency, and urgently needs to break through the core problems of model interpretability and cross-scenario generalization ability. Regarding the optimization of slag behavior, although time-series modeling methods can successfully predict the foaming state and guide process adjustment, they are confronted with issues of insufficient data robustness and weak mechanism correlation. In the links of process closed-loop and equipment operation and maintenance, the "data collection-real-time prediction-process adjustment-quality feedback" closed-loop system constructed by machine learning has realized fault early warning and parameter optimization, but is limited by constraints on high-dimensional data processing efficiency and algorithm real-time performance. For the future, the application of machine learning in EAF steelmaking should focus on directions including integrating mechanism modeling, advancing semi-supervised learning techniques, enhancing model interpretability, optimizing algorithmic tools, and addressing complex data processing challenges, thereby driving the intelligent and green-oriented deep transformation of EAF steelmaking.

In ladle furnace (LF) refining process, accurately predicting alloying element yield is of great importance for controlling the chemical composition of molten steel, improving alloy utilization efficiency, and reducing smelting costs. In recent years, machine learning methods have been widely applied to metallurgical process modeling. However, most machine learning models typically rely on complex hyperparameter tuning and often require re-tuning hyperparameter when new data are introduced, limiting modeling efficiency. To address these challenges, a tabular prior-data fitted network (TabPFN)-based prediction model for Si element yield was established using actual production data. And this model′s performance was evaluated using multiple metrics and compared with the reference heat method, multiple linear regression model, and various machine learning models reported in previous studies. Shapley additive explanations (SHAP) was then employed to conduct both global and local interpretability analysis. The results show that the TabPFN model is superior to the existing models in key performance indicators such as R², E_MA, E_RMS, hit rate and model reasoning time without a lot of hyperparameter tuning. The indicators reach 0.83, 1.59, 2.03, 98.4% and 0.430 s, respectively. Meanwhile, the SHAP analysis reveals the influence of each input feature on the Si element yield at the global level, and quantifies the influence of each input feature on the predicted Si element yield at the local level, so as to realize the efficient, high-precision and interpretable prediction of alloying element yield, offering new research ideas and technical pathways for metallurgical process modeling in the context of intelligent manufacturing in the steel industry.

Converter steelmaking, a mainstream modern process, produces molten steel by blowing oxygen into molten iron to efficiently remove impurities through oxidation reactions. The development of converter automated steelmaking technology is of paramount importance for achieving precise end-point control, enhancing product quality stability, reducing raw material and energy consumption costs, and promoting the intelligent upgrading of steel manufacturing. This paper elaborates on the architecture and control principles of the converter automated steelmaking system, provides an in-depth analysis of the critical role of detection and sensing technologies in automated steelmaking, and discusses the application of key means such as sub-lance, off-gas analysis, and spectral monitoring in real-time process parameter acquisition and dynamic regulation. Furthermore, it systematically sorts out the core status of models and algorithms in automated steelmaking, offering a detailed analysis of the construction principles and application effects of static control models, dynamic control models, as well as end-point carbon and temperature prediction models based on machine learning. The paper emphasizes that the deep integration of mechanism models with data-driven intelligent models is key to improving control accuracy, while also noting that current research still has shortcomings in aspects such as the data silo phenomenon and limited model generalization capability. Converter automated steelmaking is poised to evolve towards a full-process, self-adaptive intelligent control direction underpinned by industrial internet platforms, deeply integrating digital twin and artificial intelligence technologies, ultimately realizing smart steelmaking driven by metallurgical mechanisms and data.

In the traditional blast furnace smelting process, a significant amount of carbon emissions are usually associated, including carbon combustion and carbon loss. Ensuring stable and low-carbon production in blast furnaces is crucial for reducing the carbon footprint of the steel industry and mitigating adverse environmental impacts. Timely monitoring and predicting the thermal state of blast furnaces can optimize furnace operation, reduce energy consumption, minimize carbon losses, and enhance production stability. However, due to the complexity of blast furnace production processes and the lagging nature of detection methods, traditional means are inadequate for timely monitoring and prediction of blast furnace thermal states. Therefore, employing machine learning models to monitor blast furnace thermal states has become a new trend in blast furnace ironmaking development. In this paper, causality analysis and integrated learning were combined to mine the strong causal characteristic parameters of blast furnace thermal state by convergence cross mapping (CCM) method. Real-time monitoring of thermal state was realized based on Stacking ensemble learning model, and future state prediction was completed by combining variational mode decomposition-attention mechanism-bidirectional long short-term memory network (VMD-AM-Bi-LSTM) time series prediction model, forming a complete technical chain of "causal feature screening-real-time monitoring-time series prediction". The results show that the goodness of fit of thermal state monitoring of blast furnace is higher than 0.92, and the prediction accuracy (error within ±5%) of silicon content and temperature of molten iron reaches 82% and 88%, respectively, which meets the accuracy requirements for guiding production. Based on the internet platform of blast furnace ironmaking industry, this study realizes the monitoring and prediction of blast furnace thermal state, and promotes the transformation and upgrading of blast furnace ironmaking process to intelligence and low carbonization.

As a new generation of high-strength and high-toughness structural steel, air-cooled bainitic steel has received extensive attention in recent years, because its bainite structure can be directly formed through air cooling without isothermal treatment. Its excellent ability to regulate microstructure and properties, as well as the potential for multi-performance coupling, has shown broad prospects in the field of structural steel application. This paper systematically reviews the development history of air-cooled bainitic steel and elaborates on the characteristics of its microstructure evolution and the mechanism of solid-state phase transformation. The effects of alloying element regulation, controlled cooling paths and non-isothermal heat treatment processes (such as Q&P, B&P) on the formation of its microstructure are analyzed emphatically. Furthermore, at the microscopic level, the performance differences among granular bainite, lower bainite and acicular ferrite structures are compared, and the stability of residual austenite and its important effect mechanisms in enhancing strength and toughness, reducing hydrogen embrittlement susceptibility and improving fatigue performance are summarized. For the new generation of air-cooled bainitic steel, the synergistic strengthening of dislocation density and subgranular structure is regarded as a key approach to improving yield strength and workability.

To address the issues of low alumina dissolution rate in the Bayer process due to the intercalation of aluminum and iron in high-iron bauxite, and the difficulties in red mud settling caused by the presence of goethite, oxalic acid and ammonium oxalate are proposed as iron removal agents. The response surface methodology was used to optimize the process conditions for the removal of interlocked iron and aluminum, and the resource utilization pathways of the leaching solution were systematically explored. The test results show that the optimal conditions for iron removal are as follows. The molar ratio of H₂C₂O₄ to (NH₄)₂C₂O₄ is 0.52. The total amount of C₂O₄^2- is 2.40 times the required amount. The liquid-to-solid ratio is 6.13 mL/g. The temperature is 95 ℃, and the time is 90 min. Under these conditions, the mass fractions of iron and aluminum in the leached residue are 0.27% and 28.00%, respectively. The leaching rates of iron and aluminum are 88.19% and 17.78%, respectively. In the leaching solution, Fe(Ⅲ) and Al(Ⅲ) exist in the forms of Fe(C₂O₄)₃^3- and Al(C₂O₄)₃^3-. Ammonia water can be used to precipitate iron, aluminum, and silicon from the leachate while simultaneously regenerating (NH₄)₂C₂O₄. Al(OH)₃ can be removed from the mixed precipitate using NaOH solution to obtain sodium aluminate solution. Finally, Fe₃O₄ can be prepared by hydrothermal reduction of Fe(OH)₃ with iron powder, while regenerating NaOH. The leaching residue after iron removal and the sodium aluminate solution can be returned to the Bayer process for pulp preparation or sintering process and dissolution process of sintered clinker, achieving effective integration with the Bayer process or sintering process. (NH₄)₂C₂O₄is used in the iron removal process for high-iron bauxite, and the regenerated NaOH solution is used in the hydrothermal reduction process to prepare Fe₃O₄. (NH₄)₂C₂O₄ is used in the iron removal process of high-iron bauxite, while the regenerated NaOH is used for the hydrothermal reduction to prepare Fe₃O₄. This process uses H₂C₂O₄ and (NH₄)₂C₂O₄ as iron removal agents. Not only are the reaction conditions mild, but the process also enables the regeneration of reagents in the leaching solution and the recovery of iron resources. It is a green and efficient resource utilization technology, providing an innovative idea for the full hydrometallurgical treatment of high-iron bauxite.

Distinct microstructural characteristics lead to significantly different mechanical properties in high-strength materials during deformation. To investigate the intrinsic relationship between microstructure and properties, this study fabricated two types of ferrite/bainite dual-phase steels, F/GB and F/BF, through different processing routes. Their microstructural features and their effects on mechanical properties such as strength, elongation, and hole expansion capacity were analyzed. Results show that the F/GB steel consists of 63% granular bainite, 26% (recrystallized ferrite+proeutectoid ferrite), and 11% blocky retained austenite (volume fraction). It exhibits a yield strength of 612 MPa, tensile strength of 1 016 MPa, low yield ratio (0.602), and high ductility (elongation of 18.6%). In contrast, the F/BF steel comprises 64% lath-like bainitic ferrite, 17% recrystallized ferrite, and 19% lamellar carbon-enriched retained austenite. It demonstrates a yield strength of 1 108 MPa, tensile strength of 1 305 MPa, high yield ratio (0.849), and an excellent strength-ductility balance (21.8 GPa·%). Furthermore, the lath width of bainitic ferrite in F/BF steel ranges from 0.12 to 0.38 μm at the submicron scale, while the thickness of the lamellar retained austenite ranges between 45 and 170 nm. During hole expansion deformation, this material exhibits superior hole expansion performance, with a hole expansion ratio of 24%, attributed to the synergistic effects of stress relaxation, volume expansion, and work hardening.

Interstitial-free (IF) steel serves as a critical foundational material in modern automotive manufacturing. Currently, comprehensive studies on the evolution behavior of inclusions throughout the entire IF steel processing route remain scarce. In-depth investigation of this evolution process holds significant practical and theoretical value for optimizing IF steel production, enhancing automotive panel quality, and meeting the growing demand for high-quality products in the automotive industry. This study systematically examined the types, size, distribution, and evolution of non-metallic inclusions throughout the entire processing route of IF steel for automotive panels, including continuous cast blanks, hot-rolled plates, and cold-rolled plates. Through comprehensive metallographic examination, scanning electron microscopy (SEM), and three-dimensional etching analysis of industrial IF steel samples, combined with thermodynamic calculations, the formation mechanisms and evolution behavior of inclusions were elucidated. The study results shows that the main types of inclusions in the IF steel are identified as TiN, TiN-Al₂O₃ complex inclusions, and a small amount of Al₂O₃. The Al₂O₃ inclusions primarily originate from deoxidation products during RH refining, while the TiN-Al₂O₃ complex inclusions mainly form through TiN precipitation during solidification via heterogeneous nucleation on pre-existing Al₂O₃ inclusions. The inclusions in the slab are relatively large (equivalent diameter: 2.1-2.7 μm), initially increasing and then decreasing from the edge to the center. During hot rolling, partial re-dissolution of TiN occurs, transforming the outer TiN morphology in the complex inclusions from regular hexahedrons to an irregular form. The inclusion size decreases significantly after hot rolling (1.9-2.0 μm), indicating improved steel cleanliness. After cold rolling, the inclusion size remains similar to that in the hot-rolled material but exhibits a more uniform distribution. Thermodynamic calculations and mismatch analysis reveal that TiN begins to precipitate at a solid fraction f_s=0.89 in the final stage of solidification, forming TiN-Al₂O₃ complex inclusions through heterogeneous nucleation on Al₂O₃.

To investigate the effect of tempering temperature on the drop-weight tear test (DWTT) properties of X70Q pipeline steel, the influence of different tempering temperatures (300-600 ℃) on the microstructure and mechanical properties, especially the DWTT performance, of X70Q thick-walled pipeline steel and its underlying mechanisms were studied using metallography, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), JMatPro simulation, transmission electron microscopy (TEM), and other methods. The results show that in the low-to medium-temperature tempering range of 300-400 ℃, dislocation recovery and sub-grain coalescence occur in the tested steel, leading to a significant increase in the proportion of high-angle grain boundaries (reaching 68.3% at 400 ℃). Meanwhile, the precipitation of fine M₃C carbides contributes to strengthening, resulting in an optimal combination of strength and toughness. During high-temperature tempering at 500-600 ℃, grain coarsening, brittle-phase precipitation, and decomposition of martensite/austenite (M/A) islands cause a remarkable deterioration in DWTT performance. The deterioration of DWTT performance during high-temperature tempering is mainly attributed to three key factors: grain coarsening and equiaxed, brittle phase precipitation along grain boundaries, and decomposition of small M/A islands. Grain coarsening and equiaxed refers to the transformation of needle shaped ferrite with small fracture units and large orientation differences into equiaxed polygonal ferrite after high-temperature tempering, resulting in an increase in effective grain size, especially the abnormal growth of {001} cleavage plane grains, which reduces crack propagation resistance. Brittle phase precipitation along grain boundaries refers to the precipitation of coarse M₂₃C₆ along grain boundaries after high-temperature tempering, resulting in chromium depletion near the grain boundaries and weakening the bonding strength of the grain boundaries. The decomposition of small M/A islands refers to the important structure that hinders crack propagation. After high-temperature tempering, the small M/A islands are basically completely decomposed, losing their beneficial effects. The research results provide reference for the production of X70Q heat treatment.

The substitution of semi-coke for anthracite as blast furnace injection fuel is of great significance for reducing the coke ratio and saving energy consumption in ironmaking. This study took 36 kinds of industrial semi-coke (referred to as semi-coke) from the Shenfu area as the research object and 8 kinds of anthracite for blast furnace injection as the reference. The feasibility of semi-coke as an alternative fuel for blast furnace injection was comprehensively analyzed from the aspects of composition, combustion, grindability, explosibility and calorific value. The results show that the fluctuation of semi-coke composition is greater than that of anthracite. Approximately 35% of semi-coke has fixed carbon and volatile matter contents similar to those of anthracite, while the ash content is lower than that of anthracite. The flame return length of semi-coke is 0 mm, so it can be used as blast furnace injection fuel to ensure safe production. The grindability index of more than 80% of semi-coke is lower than 55, which cannot meet the grindability requirements of blast furnace pulverizing workshops. The ignition temperature range of semi-coke is 399.25-509.25 ℃, and the burnout temperature range for more than 90% of semi-coke is 580.19-702.15 ℃. For anthracite, the ignition temperature range is 488.22-518.04 ℃, and the burnout temperature range is 681.79- 700.57 ℃. Under rapid combustion conditions, the average burnout rate of semi-coke is 93.10%, which is higher than that of anthracite (87.10%). Both evaluation systems indicate that semi-coke exhibits good combustion performance. Based on the comprehensive results of industrial semi-coke injection tests and the differences in composition and properties between semi-coke and anthracite, to realize the use of semi-coke as an alternative fuel for blast furnace injection, on the premise of ensuring the combustion performance of semi-coke, an important approach is to select suitable raw coal and control the carbonization process to reduce the volatile matter content (9%-10%), increase the fixed carbon content (>79%), raise the calorific value (>30 kJ/g) and improve the grindability (G>55).

With the increasing demand for lightweight, safety and environmental sustainability in the automotive industry, the application of hot-stamped steel has become increasingly widespread. However, the traditional long process is associated with issues such as high energy consumption, significant carbon emission. To address those problem, the study systematically investigates the effect of a multi-mode continues casting and rolling short process (MHS) and traditional long process (THS), with a focus on their microstructure evolution, mechanical properties, and strengthening mechanisms. The results show that the hot-rolled microstructure of test steels from both processes consist of ferrite and lamellar pearlite, which alternate to form a banded morphology along the rolling direction. However, compared with THS steel, MHS steel exhibits finer pearlite colonies and a lower volume fraction of pearlite. After quenching, the uniformly distributed cementite in the MHS steel provides numerous nucleation sites during austenitization, leading to a finer and more homogeneous prior-austenite grain structure and a high fraction of large angle grain boundary(57.7%).Consequently, through the synergistic effect of multiply strengthening mechanism-including a high-density dislocation(2.8×10¹⁵ m^-2), fine prior-austenite grains (1.27 μm), and nano-sized TiC precipitates (25.7 nm), the quenched MHS steel achieves excellent comprehensive mechanical properties, a yield strength of 1 176 MPa and a tensile strength of 1 609 MPa and a product of strength and elongation reaching 16.7 GPa·%, outperforming the THS steel. Further analysis of strengthening mechanisms reveals that both steels are strengthened by multiple coordinated mechanisms. Dislocation strengthening is the most significant contributor, providing an increment of 740 MPa, following by the grain refinement strengthening which contributes 186 MPa. This study provides theoretical and data support for optimizing the short process and enhancing the performance of hot-stamped steel, contributing significantly to automobile lightweighting and green manufacturing.

Chalcopyrite is regarded as one of the most abundant copper minerals, yet its low leaching efficiency and slow kinetics under conventional metallurgical conditions severely restrict efficient resource utilization. Microbial leaching technology, recognized as an environmentally friendly and efficient metal extraction method, has attracted widespread attention in recent years for chalcopyrite processing. Primary reaction mechanisms of chalcopyrite bioleaching are reviewed, covering direct leaching, indirect leaching, and synergistic effects induced by microbial metabolites. The essential role of microorganisms in mineral crystal structure destruction and metal release is highlighted. Commonly employed strains, including Acidithiobacillus ferrooxidans, Leptospirillum ferrooxidans, and sulfur-oxidizing bacteria, are summarized, and their adaptability and synergistic performance in different leaching systems are analyzed. Key factors that influence bioleaching efficiency, such as ore mineralogy, chemical and environmental parameters, and catalytic leaching systems, are systematically discussed. Recent advances in microbe-mineral interfacial reactions, multi-species cooperative metabolism, and electrochemical regulation are integrated. Construction of high-performance composite microbial consortia, optimization of pretreatment processes, and development of industrial-scale reactors are identified as critical directions for enhancing chalcopyrite bioleaching efficiency.

To address the issues of insufficient accuracy in current sintering endpoint prediction models and the reliance on process experience in traditional control methods, this study proposes a sintering endpoint prediction and optimized control model based on a convolutional neural network integrated with an attention mechanism and intelligent algorithms. The isolation forest (IF) algorithm was employed to detect and correct outliers in the data, while feature selection was comprehensively performed using process mechanisms and the maximum information coefficient (M_IC) method. On this basis, a serial multi-block convolutional residual network was constructed to effectively capture complex patterns from historical sintering data under multiple operating conditions. A squeeze-and-excitation (SE) attention mechanism was introduced to enhance the model′s focus on key features, enabling it to learn sintering characteristics under different conditions. To validate the model′s effectiveness, comparative and ablation experiments were designed to systematically verify the synergistic effect of the attention mechanism and residual structure, as well as the optimal model architecture. Using this prediction model as the core, a mathematical model for sintering endpoint optimization control was established, and the non-dominated sorting genetic algorithm (NSGA-Ⅱ) was applied to optimize the operational parameters of the sintering process. Validation using actual production data from a steel plant shows that the proposed sintering endpoint prediction model performs excellently, with a coefficient of determination (R²) of 0.84. The results obtained from the optimization control model reduce the mean absolute deviation (D_MA) by 27.1% compared to the pre-optimization scenario, demonstrating effective control of the sintering endpoint. This provides a new method for intelligent control and optimization of the sintering process.

The Al-Mg-Si-Mn alloy contains relatively high levels of alloying elements, which readily form coarse intermetallic compounds during solidification, directly affecting the alloy′s hot working properties. To enhance the alloy′s hot workability, this study employed twin-roll casting (TRC) and water-cooled copper moulds (MC) to produce heat-treated dispersion-strengthened Al-Mg-Si-Mn aluminum alloy. Characterisation techniques and hot compression tests were utilised to investigate the effects of twin-roll casting on the hot deformation behaviour and microstructural evolution of the Al-Mg-Si-Mn alloy. Dispersoid-strengthened Al-Mg-Si-Mn aluminum alloys were produced by twin-roll casting (TRC) and conventional mold casting (MC). An extra-low temperature homogenization was performed at 430 ℃ for 6 h, which was followed by uniaxial hot compression tests. The results show that the as-cast TRC sample has a lower eutectic fraction with a smaller size compared to the MC samples. During homogenization, a large number of α-Al(Fe, Mn)Si dispersoids precipitates, and TRC sample has a greater dispersoids number density than that of MC sample, which is attribute to the "pipe diffusion" mechanism of solute atoms along the dislocations in the TRC samples. Precipitation-free zone (PFZ) forms near the eutectic regions, and TRC sample has a lower PFZ fraction than that of MC sample. The TRC samples yields higher flow stresses than the MC sample owing to the stronger dispersoid strengthening effect. The MC sample after deformation has serious edge cracks due to the presence of more AlFeMnSi intermetallic compounds, while the TRC sample after deformation has no edge cracks due to the presence of less intermetallic compounds, thereby improving the hot workability of the TRC sample. The research findings provide a theoretical basis for developing high performance Al-Mg-Si-Mn alloy.

AA3102 aluminum alloy is extensively used in hot working processes, and its flow stress behavior and microstructural evolution during high-temperature deformation provide a critical theoretical basis for optimizing hot working parameters. This study employed a Gleeble-3500 thermal simulator to conduct isothermal compression tests on AA3102 aluminum alloy within the temperature range of 400-600 ℃ and strain rate range of 0.01-10 s^-1, obtaining true stress-strain curves. To enhance model accuracy, the original experimental data were corrected for both temperature and friction effects. Based on the corrected true stress-strain curves, a constitutive model for hot deformation was developed by integrating the Arrhenius equation and the Zener-Hollomon parameter to couple the influences of temperature and strain rate, enabling accurate description of flow stress variations across the entire strain range. According to the dynamic material model (DMM), the power dissipation efficiency and instability criterion under different strain conditions were calculated, and processing maps were constructed. Systematic microstructural characterization of specimens under various strain conditions was performed using electron backscatter diffraction (EBSD), and the patterns of microstructural evolution were summarized. The results demonstrate that the predicted values from the established constitutive model agree well with experimental data, with a mean absolute relative error of only 4.24%, confirming its accuracy in predicting the high-temperature flow behavior of AA3102 aluminum alloy. Within the tested range of 400-600 ℃ and 0.01-10 s^-1, no instability regions are observed during hot deformation, indicating excellent hot workability of the alloy in this domain. Particularly under conditions of 500-600 ℃ and 0.01-1 s^-1, the power dissipation efficiency is high, exceeding 30% at its maximum, defining the optimal hot processing window for this alloy. Microstructural analysis revealed that dynamic recovery is the dominant softening mechanism at low temperatures and low strain rates. As temperature and strain rate increase, the dynamic softening mechanism gradually transitions from dynamic recovery to dynamic recrystallization.

High-nitrogen austenitic stainless steel has excellent comprehensive performance, which exhibits wide potential applications in fields of marine engineering, petrochemical and biomedicine. With the development of technology, powder metallurgy technology and metal additive manufacturing have demonstrated unique advantages in realizing the structural and functional integration of high-nitrogen stainless steel and efficient nitrogen-controlled preparation. However, significant challenges remain in achieving synergistic optimization between powder quality and forming processes. This article systematically reviews current research progress in high-nitrogen stainless steel powder preparation, comparatively analyzes nitrogen control mechanisms and process characteristics of solid powder nitriding, gas atomization, plasma rotating electrode atomization methods. Furthermore, the influence of processes such as powder injection molding, hot isostatic pressing and additive manufacturing on the properties of materials is deeply discussed. Finally, for current technological bottlenecks, the future research directions of high-quality powders in fields of raw material preparation and molding are also prospected, which can provide reference for advancing their application in high-end manufacturing.