Extensive, continuous mining has depleted most tungsten deposits, leaving vast quantities of tailings that now represent a potential lean-grade hematite resource. The isothermal reduction kinetics of beneficiated tungsten mine tailings using boiler-grade coal as a reductant were investigated in the temperature range of 1273-1373 K. Reduction experiments demonstrated that both temperature and holding time strongly influence the extent of reduction, with a maximum fractional conversion (alpha) of 0.854 achieved after 60 min at 1373 K. XRD and SEM analyses confirmed sequential phase transformations from hematite to magnetite, w & uuml;stite, and ultimately metallic iron, with crack formation and spherical iron particles observed on the briquette surfaces. Kinetic modeling indicated a mixed-control mechanism: the contracting geometry (CG3) model predominated in the initial stages, while diffusion (D1) governed the later stages. The apparent activation energies were calculated to be 52.18 kJ/mol (CG3 stage) and 65.81 kJ/mol (D1 stage), indicating a higher energy demand for diffusion through the product layer. The findings provide the intrinsic mechanism for the reduction behaviour of beneficiated tungsten mine tailings-coal composite briquettes and demonstrate the potential of utilizing industrial boiler coal as a reductant in solid-state ironmaking.
In the context of the global energy transition, a crucial technological pathway is proposed that uses bamboo scraps (ZX) and bituminous coal (YM) as feedstocks, enhancing energy conversion efficiency through micro-carbonisation. This study systematically explores the potential for producing metallurgical synthesis gas (MSG) through micro-carbonisation under different ratios and temperature conditions. Using various characterisation techniques, including thermogravimetric analysis, gas chromatography, Fourier Transform Infrared (FTIR) and Scanning Electron Microscope (SEM), the gas release behaviour, structural evolution of solid products and energy characteristics during the micro-carbonisation process are revealed. The results indicate that the generation of MSG occurs in three stages: CO-dominated release, generation of CH4 and CnHm and significant H2 production, with no distinct boundaries between these stages and overlap occurring. Under ZX: YM = 7:3 and 500 degrees C, the MSG achieved a maximum cumulative instantaneous lower heating value (LHV) of 144.9 MJ & centerdot;m-3, with H2 and CO as the major gas components. The temperature and raw material ratio significantly influence the gas composition, heating value and carbon content of the solid products. This study provides a theoretical foundation and process optimisation strategies for the synergistic energy utilisation of bamboo-based biomass and YM, providing a proof-of-concept basis and process insights for potential scale-up.
This study systematically evaluates the effects of slurry formulation, specifically the solid-liquid ratio (SLR) and sodium carboxymethyl cellulose (CMC) binder concentration, on the characteristics of spray-dried mold powder granules. Slurry viscosity increased from 0.14 to 0.38 Pa & centerdot;s as the solid loading rose from 44.44 to 54.55 wt.%, accompanied by a more negative zeta (180.85 mV). This promoted the formation of larger, hollow granules with reduced packing density (decreasing from 0.57 to 0.48 g & centerdot;cm(-3)) and lower compressive strength. Conversely, increasing CMC content from 1.00 to 3.00 wt.% increased both slurry viscosity and granule size, resulting in denser particles and raising packing density from 0.45 to 0.59 g & centerdot;cm(-3). A synergistic optimum identified at 50.00 wt.% solids loading with 2.00 wt.% CMC, which collectively improved particle sphericity, size uniformity. The optimized particle characteristics of this formulation are expected to ensure efficient utilization, particularly in high-speed continuous casting applications.
This study developed an indicator prediction model for steel processes adapting to dynamic operating condition deviations. By combining just-in-time learning, ensemble learning techniques, and target similarity extraction, the model improves prediction accuracy and robustness. Validated on industrial rolling and sintering data, the model achieves up to 18% improvement over traditional models. Utilizing multi-dimensional parameters, the 6% error margin hit rates for yield and tensile strength reached 86% and 99% in rolling data, while the Al 2 O 3 hit rate reached 96% in sintering. Notably, for boundary samples (top/bottom 25% quantiles), the model achieved a 56% relative improvement in hit rate. Furthermore, the model significantly enhances prediction robustness under dynamic operating deviations, reducing the accuracy fluctuation across time segments from 12% to 5%.
Interstitial-free (IF) steel is extensively used in many fields because of its brilliant formability and timelessness properties. However, inclusions formed in steel affects these properties to a great extent. To reduce the influence of inclusions on steel quality, an industrial produced IF steel from a steel mill was taken as the research object of this study. A comprehensive assessment of the whole process of IF steel production was conducted, revealing excessive inclusions in both tundish and slab during IF steel production. This was identified tundish as the critical bottleneck limiting the cleanliness. Hence, a systematic investigation was conducted through physical simulation, numerical simulations, and industrial trials to optimise the tundish configuration. Physical simulation results indicated when the immersion depth of long nozzle was 50 mm, the relative distance between the weir and dam was 50 mm, the distance from the weir to the centre of the long nozzle was 400 mm, and the metallurgical effect of the tundish was the best. Simultaneously, numerical simulation results demonstrated that the stagnation time of molten steel in the tundish was extended after implementing the optimised scheme, and low-temperature zone ratio at the working interface was reduced from 14.74% to 9.65%, effectively promoting the flotation and removal of inclusions. Finally, the industrial test results showed that the total oxygen content in the tundish was reduced from 4.11 & times; 10-5 to 3.5 & times; 10-5, and the number density and average size of Al2O3 and TiN inclusions were reduced with optimisation scheme. This study improves the cleanliness of IF steel in steel mills and provides reference for other steel mills to improve the quality of steel grades.
To address the challenges posed by fluorine and alkali metals (K, Na) in Bayan Obo iron ore during blast furnace ironmaking, this study systematically investigates the impact of alkali metal-fluoride composite systems on the thermal performance and microstructure of coke. An immersion method was used to simulate the vapour-phase adsorption and deposition of harmful elements on coke under simulated blast furnace conditions. The results show that alkali metal-fluoride composite systems significantly exacerbate coke deterioration. Coke reactivity index (CRI) exhibits nonlinear growth with increasing solution concentration (increase range: 12.54%-51.12%), while coke strength after reaction (CSR) decreases synchronously (decrease range: 1.73%-19.41%), following the influence order: K2CO3 > Na2CO3 > KF > HF > NaF. Phase analysis indicates that after gasification reactions, low-melting-point silicoaluminates such as KAlSiO4 and NaAlSiO4 are formed in coke immersed in K2CO3 and Na2CO3 solutions, leading to coke volume expansion, matrix cracking, and strength reduction. Scanning electron microscopy (SEM)-energy-dispersive spectroscopy (EDS) reveals the most severe pore evolution in the potassium system (porosity reaches 69.46% for 5% K2CO3), followed by the sodium system, and the least in the fluoride system. Mechanistic studies demonstrate that alkali metals play a primary deteriorative role by catalysing gasification reactions, damaging carbon microcrystalline structures, and inducing pore connectivity, while fluorides enhance alkali metal migration through F- adsorption, with KF exhibiting the most significant synergistic effect. This study first reveals the quantitative relationship between migration ability and catalytic activity in the alkali metal-fluorine composite system. This research provides theoretical support for alkali load control in Bayan Obo iron ore blast furnaces and optimisation of coke blending schemes.
Oxygen blowing critically affects metallurgical efficiency and molten steel quality, making accurate oxygen consumption prediction essential for optimising converter smelting. Growing multi-variety, small-lot production and new steel grade development make small-sample prediction a major challenge in the steel industry. This article proposes a hybrid oxygen consumption prediction model based on parameter optimisation and the oxygen balance mechanism. First, the influence of assumed parameter fluctuations in the mechanism model on oxygen consumption is analysed. Then, oxygen consumption is divided into non-optimised and optimisation-required parts. Finally, the differential evolution algorithm is adopted to optimise parameters and improve prediction accuracy. The dataset is split into development and independent test sets, with 5-fold cross-validation employed to ensure reliable parameter optimisation and model evaluation. The proposed model outperforms unoptimised mechanism, BPNN and SVR models in accuracy and adaptability. It achieves 1.97% MRPE and 255.20 m & sup3; RMSE, with hit rates of 39.39%, 78.79% and 96.97% within +/- 1%, +/- 3% and +/- 5% errors. The model enables accurate small-sample prediction, reducing production costs and improving efficiency.
This study explores the synergistic effects of ultrasonic-assisted additive manufacturing (UAM) and heat treatment on the repair and enhancement of 30CrMnSiA alloy. UAM was found to significantly refine the grain structure, transforming columnar crystals into equiaxed grains and improving interlayer bonding. The subsequent heat treatment further enhanced mechanical properties by relieving residual stresses and homogenising the microstructure. The repaired alloy exhibited a tensile strength of 1902.5 MPa, a 12.65% increase compared to traditional additive manufacturing methods, and a yield strength of 439 MPa, reaching 83.22% of the original material. Fatigue resistance was significantly improved, with low-cycle fatigue life reaching 67,233 cycles, attributed to reduced defects, enhanced grain boundary density, and refined microstructure. These findings demonstrate the potential of UAM and heat treatment in repairing and enhancing high-strength structural alloys for demanding applications.
Factors affecting dissolved oxygen content were numerous. Conventional mechanistic or empirical models tended to have prediction errors that hindered the achievement of high-precision control. It was of great significance for establishing an accurate prediction model to reduce production costs. Accurate prediction of dissolved oxygen contents can be achieved by establishing appropriate machine learning models. The machine learning method including neural network technology, genetic algorithm and mind evolutionary algorithm was applied to predict the dissolved oxygen content and obtain the optimal slag addition amount during the refining process. Four types of prediction models were established to achieve the optimal model. The root means square error and mean absolute error were utilised to evaluate the accuracy. Impact factors were considered to determine the influence degree of each operating factor on the oxygen contents. The optimal slag addition amount with various T.AI contents was also calculated.
Ladle glaze is considered to be one of the major sources of non-metallic inclusions in steel. The effect on inclusions of molten steel and the corrosion behavior of MgO-C refractory by ladle glaze in the production process were simulated by laboratory 1 kg Si2Mo resistance furnace. The results show that the content of T.O in steel increases with the increase of basicity of glaze layer and ladle use times. The mixed use of ladles (Ladles for Si killed and Al killed steel) and the use of ladles for Al killed steel can significantly increase the Al content in steel, and using special ladle for Si killed steel is beneficial to the control of T.O and Al. The inclusions in the experimental steel are predominantly SiO2-Al2O3-MnO-(MgO), in which the proportion of Al2O3 increases with the increase of basicity of glaze, whereas the proportion of MgO is the highest when mixed use of ladles, and increases with the increase of ladle use times. Thermodynamic calculation results show that the MnO component in inclusions is gradually replaced by Al2O3, resulting in Al2SiO5 inclusions. The glaze of special ladle has low interfacial tension with MgO in refractory material, and it is easy to react with MgO, which causes strong penetration and chemical corrosion on MgO-C refractory materials, so it will reduce the service life of refractory materials. However, special ladle is beneficial to the control of vital elements and inclusions in spring steel. The mixed use of ladles will cause structural spalling of refractory materials and significantly increase the number density of inclusions in steel. The use of ladle for Al killed steel is advantageous to the protection of MgO-C refractory materials, but it will increase the proportion of Al2O3 in inclusions. Special ladle is recommended when smelting outstanding performance Si-Mn killed valve spring steel to reduce the influence of hard and brittle inclusions on the fatigue life of valve springs.
Low-carbon-containing Nb microalloyed building structure steel was tested by Gleeble-3500 thermal simulation machine. Based on the thermal simulation data and microstructure analysis of optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD) and transmission electron microscope (TEM), the effect of different deformation temperatures (900 degrees C and 850 degrees C) and deformation amounts (30%, 40% and 50%) on the transformation and the final microstructure was clarified. When the strain amount is constant, with the decrease of deformation temperature from 900 degrees C to 850 degrees C, the initial temperature of ferrite transformation increases from 751 degrees C to 758 degrees C due to the increase in the amount of dislocation and deformation bands in original austenite grains. Meanwhile, the carbon content in the residual undercooled austenite after ferrite transformation increases, inhibiting the nucleation of medium-temperature bainite and decreasing the bainite transformation temperature from 558 degrees C to 544 degrees C. In addition, when the deformation temperature is constant, the grain boundary content of large angle (>15 degrees) increases from 55.7% to 61.3%, and the starting temperature of ferrite transformation gradually increases from 740 degrees C to 758 degrees C with the increase of deformation amount from 30% to 50%. It is related to the amount of the second-phase precipitates. It indicates that the increase in deformation amount could promote the ferrite transformation and result in a smaller ferrite grain size.
XC45 steel, an aluminum-deoxidized and sulfur-containing steel, is widely used for mechanical components, whose fatigue performance and service life are strongly affected by CaO-MgO-Al2O3 (CMA) inclusions with large size and low interfacial tension, and commonly identified as D- or DS-type inclusions. To investigate their formation mechanism and control, systematic industrial sampling was conducted during LF refining, VD treatment, and tundish stages, together with inclusion characterization by SEM-EDS and thermodynamic analysis. The results showed that the composition of CMA inclusions in the billet was fixed at tundish stage, while their size was significantly influenced by the CaO content in inclusions. The changes of MgO content in inclusions affected their aggregation and melting/wetting behavior, thereby altering inclusion growth and removal trend. Based on these findings, a control strategy was proposed by maintaining total calcium at 0.0003-0.0005 wt.%, promoting the formation of removable MgO & centerdot;Al2O3 and CaO & centerdot;2Al(2)O(3) inclusions while suppressing CaS precipitation. This ensures the liquid phase fraction of all inclusions exceeding 20%, thereby alleviating nozzle clogging during continuous casting. Industrial trials confirmed a significant reduction in inclusion amounts larger than 5 mu m in the billets. This study provides an effective guideline for improving steel cleanliness and product quality of aluminum-deoxidized and sulfur-containing steels.
The non-linear influence of hot metal composition and scrap ratio on flux addition requires accurate predictive models to optimise charging operations. A random forest (RF) model was developed using multi-heat industrial data to predict lime and light-burned dolomite additions. The model effectively captured non-linear interactions between key process variables and flux inputs but showed slight systematic deviations under fluctuating operating conditions. To improve prediction accuracy and physical consistency, metallurgical mechanisms were embedded into the data-driven framework. Empirical features for light-burned dolomite were obtained by polynomial fitting, while theoretical lime additions were derived from quaternary basicity theory and used as mechanistic constraints. This hybrid model retained the non-linear learning capability of RF while enhancing interpretability and robustness. After feature enhancement, all performance indicators improved markedly: for dolomite, the coefficient of determination (R2) increased from 0.4801 to 0.5675, the mean absolute error (MAE) decreased from 123.17 kg to 116.52 kg and the root mean square error (RMSE) from 152.90 kg to 139.46 kg; for lime, R2 rose from 0.5843 to 0.7553 and MAE and RMSE dropped by 24.1% and 23.3%, respectively. The proportion of samples within +/- 5% error increased significantly, confirming improved reliability for basic oxygen furnace (BOF) charge prediction and physically consistent steelmaking control.
Electric smelting furnace (ESF) is increasingly adopted as an alternative to conventional cupola furnace for mineral wool production. The application of freeze lining to protect the refractory lining from erosion by molten slag has become a prevalent industrial practice. In this study, a three-dimensional (3D) full-scale mathematical model of a three-phase alternating current (AC) ESF is developed, which incorporates electromagnetism, heat transfer, and solid-liquid phase transitions. The model is used to simulate freeze lining formation and assess the impacts of process parameters. The time-averaged electromagnetic field (EMF) distribution is derived from Maxwell's equations using the finite volume method. The temperature field and phase transitions are modelled through the energy conservation equation, integrated with enthalpy-porous medium model. To optimise control over freeze lining thickness, this study analyzes three critical parameters: pitch circle diameter (PCD), melt pool height (MPH), and sidewall refractory thickness (SRT). Results demonstrate that the model effectively predicts the EMF distribution within the furnace, coupled heat transfer between the solid linings and the melt pool, and the morphology of the freeze lining. Under identical cooling conditions, increasing PCD and MPH slightly reduces freeze lining thickness, while an increasing in SRT complicates its formation. For optimal freeze lining maintenance, it is recommended that PCD, MPH, and SRT be set at 1.5 m, 1.2 m and 50 mm, respectively.
As a crucial functional material in the continuous casting process, mould fluxes play a significant role in ensuring smooth operation and improving the quality of cast billets. To mitigate the environmental impact of fluorides in mould fluxes, TiO2 has been introduced as a network former to reduce viscosity and melting temperature. The formation of perovskite instead of cuspidine also contributes to controlled heat transfer. However, preventing the formation of titanium carbide (TiC) under high-temperature conditions remains challenging. Experimental results indicate that during heating, both CaO-SiO2-TiO2 and CaO-SiO2-CaF2-TiO2 slag systems react to form perovskite. TiO2 participates more readily in solid-state reactions with CaO than CaF2 does, thereby inhibiting the formation of cuspidine. Furthermore, in carbon-containing CaO-SiO2-TiO2 systems, TiC forms along with CO at elevated temperatures. It is revealed that TiC formation does not result from the direct reaction between TiO2 and C, but rather from the reaction between CaTiO3 and C. Under high-temperature carbon-rich conditions, carbon reduces perovskite to form TiC. Consequently, in contrast to fluorine-based fluxes, titanium-bearing mould fluxes require careful optimisation of carbon content to prevent TiC precipitation.
Accurate evaluation of the caking property of non-coking coals, which generally exhibit limited metaplast-generation capacity during carbonisation compared with coking coals, is crucial for unlocking their utilisation potential in both cost reduction and efficiency improvement. Herein, an improved caking test was developed to distinguish weakly/non-caking coals under practical blending conditions. Structural characteristics of coals and macerals were quantified by Fourier Transform Infrared Spectroscopy with peak deconvolution, forming an integrated 'petrology + structure' framework for establishing quantitative correlations with caking indices. Results indicate that lean coal possesses superior blending potential compared to long-flame coal. Despite similarly limited metaplast-generation capability, lean coal forms a stronger carbon skeleton due to its higher degree of aromatisation and structural condensation. In contrast, long-flame coal exhibits more extensive aliphatic branching, higher thermal reactivity and a looser structural configuration, resulting in weaker cohesion and insufficient skeletal support. The generation potential of hydrocarbon (P) was identified as the most reliable predictor of caking behaviour owing to its consistent trends in both raw coals and their macerals. Accordingly, the theoretical P-value of blended coal ( P B . T ) was correlated with the caking index (GR.I) through the relationship lgGR.I = a P B . T 2 + b P B . T +c, enabling accurate prediction of the caking behaviour of blends containing non-coking constituents. This approach reduces testing costs by about 98% and eliminates pyrolysis-related emissions, offering substantial economic and environmental benefits.
In-line assessment of descaler functionality was conducted through use of high-speed infrared (IR) video imaging of moving steel strips following laminar cooling. IR temperature measurements were obtained for fifteen (15) steel strips at a mill location between laminar cooling and coiling. Anomalous temperature values were observed in the IR images and were attributed to the presence of surface oxides. The location and spacing of these oxides were quantified using an outlier detection method consisting of a Gaussian process and Gaussian mixture model. Validation of the outlier detection method was done through comparison of both the morphology and emissivity of oxide regions to those reported in literature. The oxides were predominately located at the mid-width of the strip, while their transverse spacing correlated well with the descaler nozzle spray patterns. The transverse spacing and location of these oxides indicates that the reheat furnace and/or rough-rolling entry descaler was operating with reduced functionality. Total fraction of surface oxides was also shown to be correlated with the amount of silicon in each strip and the total roll reduction.
High-temperature smelting, rolling, and room-temperature tensile testing were conducted on high-strength rebar steels containing 0 similar to 0.01% rare earth cerium. The rolling start temperature is 1128 degrees C similar to 1160 degrees C and the rolling start temperature for pass nine is 840 degrees C similar to 850 degrees C. The carbon/sulfur analyzer, oxygen/nitrogen determinator, inductively coupled plasma mass spectrometer and scanning electron microscopy with energy-dispersive spectroscopy were employed to detect steel composition. With increasing Ce amounts, inclusions were primarily composed of MnS, accompanied by oxides/ sulfides, as well as their MnS-complex counterparts, which is consistent with thermodynamic predictions. The addition of cerium significantly promoted ferrite formation. In the steel without Ce, the ferrite fraction was relatively low at 29.9%, whereas the steel with 0.01% Ce exhibited the highest ferrite content at 37.3%. Trace amounts of Ce facilitated grain refinement by forming Ce-Al-O inclusions, which served as nucleation sites for austenite. The Ce-Al-O inclusions also contributed to the precipitation of VN, enhancing ferrite formation and achieving an optimized balance between strength (874 MPa) and toughness (17.88%). However, excessive cerium content adversely affected steel cleanliness, leading to the formation of coarse Ce-O-S inclusions that compromised elongation to 7.37%.
This study investigates how grain size and grain-size distribution affect high-temperature deformation stability in a commercial Cr-Mn-N austenitic stainless steel. Cold rolling and subsequent annealing produced four microstructures: ultrafine-grained (UFG), coarse-grained (CG), fine-grained unimodal (FG-Unimodal), and heterogeneous fine-grained bimodal (FG-Bimodal). Tensile tests at 600 degrees C showed that UFG had higher ductility and more stable flow than CG, with elongations of 34% and 18%, respectively. After deformation, UFG contained dense intragranular low-angle grain boundaries (LAGBs), dislocation-wall structures, and local recrystallization features, indicating dynamic recovery and polygonization that improved strain compatibility and delayed grain-boundary damage. In contrast, CG showed localized misorientation gradients and grain-boundary-dominated failure. For the fine-grained states, FG-Unimodal showed a higher elongation than FG-Bimodal (34.0% vs. 23.5%). This result indicates that a narrow grain-size distribution promotes more uniform deformation, whereas a bimodal grain-size distribution increases strain partitioning and accelerates strain localization and local softening.
This study investigated the effects of refractories (MgO vs. Al2O3) on the cleanliness and inclusion evolution in Al-killed steel during refining with a CaO-Al2O3-SiO2 slag (56.9% CaO, 35.0% Al2O3, 8.1% SiO2), combining laboratory experiments with thermodynamic calculations. The results show that with MgO crucibles, total oxygen and sulphur contents in steel remained low (6-8 and 4-5 ppm), and inclusions were CaO-Al2O3-MgO and MgO & centerdot;Al2O3-based; area fraction and average size decreased with refining time. With Al2O3 crucibles, total oxygen and sulphur contents increased to 13-16 and 30-46 ppm, respectively, and sulphur reversion occurred. Inclusions were CaO-Al2O3-SiO2 and Al2O3-based, reaching minimum area fractions after 60 min of refining. Thermodynamic calculations revealed that the dissolution of MgO crucibles enhanced the slag's absorption capacity for CaO & centerdot;2Al(2)O(3) inclusions, while inhibiting the absorption of MgO and MgO & centerdot;Al2O3 inclusions. Conversely, Al2O3 crucible dissolution weakened the slag's absorption capacity for calcium aluminate, MgO & centerdot;Al2O3, and Al2O3 inclusions.
