Metallurgical and Materials Transactions B最新文献

In response to the imperative for sustainable iron production with reduced CO₂ emissions, this study delves into the intricate role of TiO₂ in the direct reduction of iron oxide pellets. The TiO₂-dependent reducibility of iron oxide pellets utilizing H₂ and CO gas across varied temperatures and gas compositions is thoroughly investigated. Our findings unveil the nuanced nature of the TiO₂ effect, underscored by its concentration-dependent behavior, revealing an optimal range between 1 and 1.5 pct TiO₂, where a neutral or positive impact on reduction kinetics and diffusion coefficient is observed. Notably, the synergistic interplay of CO and H₂ at 1000 °C emerges as particularly efficacious, suggesting complementary effects on the reduction process. The introduction of H₂ into the reducing atmosphere regulated by CO not only extends the transition range but also markedly expedites the rate of reduction. Furthermore, our study highlights the temperature sensitivity of the TiO₂ effect, with higher TiO₂ content correlating with prolonged reduction time in a 100 pct H₂ atmosphere at 900 °C. In a 100 pct H₂ atmosphere, the non-contributory role of TiO₂ stems from the water-gas shift reaction. Conversely, introducing H₂ into a CO-controlled reducing atmosphere with TiO₂ enhances the transition range and expedites the reduction rate. Additionally, our findings underscore the role of total iron content, revealing a direct correlation with the reduction process.

Bentonite is an essential binder in the iron ore pelletization process. However, limited research has been conducted on the correlation between the physical and chemical properties of bentonite and its pelletizing performances, while the evaluation criteria for pelletizing bentonite have not been standardized. To optimize the current evaluation methods, this study tested the physical and chemical properties of five representative bentonites, as well as their green balling performance after pelletizing. Additionally, a multiple regression model was constructed using R. Stepwise regression and relative weight analysis were used to optimize and evaluate the indicators of bentonite. The results showed that the raw ball performance was mainly affected by water absorption (WA), swelling index (SI), and swelling capacity (SC). The dry ball performance was mainly affected more by methylene blue index (MBI) and cation exchange capacity (CEC). The following stepwise regression analysis revealed that WA, CEC, and SC were significant predictors for green ball drop strength; WA and SI for green ball compressive strength; and WA, MBI, and SC for dry ball compressive strength. The multiple regression model developed in this study exhibits high goodness of fit and accuracy, making it a valuable way for assessing the impact of different quality bentonites on pelletizing performance as well as optimizing the evaluation methodology of bentonite’s performance in iron ore pelletization.

In addressing the retrofitting issues of conventional non-induction heating tundish, a novel butterfly-type induction heating tundish model was devised. A three-dimensional coupled mathematical model of magnetic, thermal, and fluid fields was established to investigate the temperature distribution, flow characteristics, and temperature rise curves within the butterfly-type tundish. The model for inclusion motion and removal, based on Large Eddy Simulation (LES), was devised, integrating factors such as normal critical velocity, coefficient of restitution, and critical incident angle at the wall boundary conditions to provide a more precise depiction of the reflection and adsorption processes of inclusions on the tundish wall. The findings suggest that induction heating can effectively offset the temperature loss of the molten steel and enhance the removal rate of inclusions, particularly those of large size. The outlet temperature increases by − 15 K, 7 K, 15 K, and 26 K, and the total removal rate of inclusions reaches 69.18, 83.37, 87.69, and 92.01 pct at 0, 600, 800, and 1000 kW, respectively. The channel serves as the primary site for inclusion removal when employing induction heating. Among these, the removal rates within the channel and at the slag layer exhibit a positive correlation with the inclusion diameter, while the remaining wall removal rates show a negative correlation. The implementation of induction heating technology leads to a notable decrease in the entry of large-sized inclusions into the mold.

The phase diagram information of the Nd₂O₃-SiO₂-FeO-Fe₂O₃ system is basic for the design and development of slag for recycling NdFeB magnets by pyrometallurgical processes. The equilibria phase relations of the Nd₂O₃-SiO₂-FeO-Fe₂O₃ system were investigated at 1773 K in air using a high-temperature isothermal equilibration technique followed by quenching. Seven two-phase equilibria regions and seven three-phase equilibria regions were observed by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) analysis of quenched samples. Ternary compounds Nd_9.33Si_6−xFe_xO_26-δ and Nd_0.67Si_0.13Fe_0.2O_δ were found. The 1773 K isothermal section was constructed for the Nd₂O₃-SiO₂-FeO-Fe₂O₃ system.

The proportion of pellets in the blast furnace charge structure is gradually increasing, among which magnesium-bearing fluxed pellets have been widely applied due to their excellent metallurgical properties. To further determine the consolidation mechanism in different reaction layers of magnesium-bearing fluxed pellets, the phase transformation and diffusion behaviors of Fe₃O₄–MgO in different roasting atmospheres were investigated in this study. The results showed that Fe²⁺ preferentially diffused to the MgO layer and combined with Mg²⁺ to form Mg_yFe_1−yO in inert atmosphere, and then, Fe³⁺ and Fe²⁺ binded to Mg²⁺ to form [(MgO)_x(FeO)_1−x]·Fe₂O₃ (0 ≤ x ≤ 1). The increase of roasting temperature was favorable for the entry of Mg²⁺ into the spinel phase. In air atmosphere, Fe₃O₄ was first oxidized to Fe₂O₃. Fe³⁺ and Mg²⁺ counter-diffused and then combined to Mg_xFe_3−xO₄ (x = 1). Fe₃O₄ reacted more readily with MgO in inert atmosphere than in air atmosphere. It was favorable to increase the oxygen partial pressure for Mg_xFe_3−xO₄ (x = 1) generation. The diffusion rate of Mg²⁺ at the interface of Fe₃O₄–MgO system in inert atmosphere was 1.88 µm/min at 1200 °C, which was faster than that of 1.49 µm/min in air atmosphere.

Graphical Abstract

In order to evaluate the potential application advantages of static magnetic field on the development of electroslag remelted large-scale H13 steel technology, the carbides, inclusions, solute segregation and mechanical property of H13 steel were analyzed. The results demonstrated that the implementation of axial static magnetic field (ASMF), the area fraction and size of carbides decreased, and the segregation rate of the elements (C, Mo, V and Cr) decreased. The reason is that the application of ASMF could shorter the local solidification time, decrease the dendrite spacing, alleviate the degree of interdendritic segregation, which limits the time and space for the generation and further growth of carbides. After ASMF was applied, there were lesser and smaller inclusions in H13 steel. Smaller droplet and shallower metal pool are the consequence of utilizing ASMF, which improves the kinetic conditions and removal process that inclusions migration to the slag-metal interfaces. Moreover, samples after forged annealing showed that the average grain size of H13 steel decreased when ASMF was applied, which significantly enhances the mechanical properties. In the absence of ASMF, the product of strength and elongation was 22,599 MPa pct. After applying 60 mT ASMF, the product of strength and elongation increased to 28,770 MPa pct.

Coke and ore sizes are important to the efficiency and stability of blast furnace (BF) operation in practice. However, their selection is usually determined by experience and there is no systematic study on the effects of ore and coke sizes on BF operation. This paper presents a numerical study on the multiphase flow and thermochemical behaviors inside the BF with different ore and coke sizes. This is done based on a recently developed 3D multifluid BF process model. The validation of this model is first confirmed by various applications. It is then used to study the effect of particle size on BF performance. The results show that as coke and ore sizes decrease, the thermochemical utilization efficiency is improved, which is reflected in low coke rate, low top gas temperature, high top gas utilization factor, and high productivity. However, there may be a minimum particle size for a given BF. Three indicators, namely gas pressure drop, liquid flooding in the dripping zone, and particle fluidization at the burden surface are used to determine this minimum particle size. Under the present conditions considered, the suggested minimum coke size should not be less than 20 mm and the suggested ore size should not be less than 12.5 mm. In addition, the effect of ore size on BF global performance indicators, e.g., fuel rate and productivity, is more significant than coke size. In terms of inner states, as ore size increases, the solid temperature drops in the BF shaft and the CZ position drops accordingly. On the contrary, as coke size increases, the solid temperature increases significantly in the BF shaft and the CZ position increases accordingly. Consistently, the increase of ore and coke sizes both increases the CZ thickness. Furthermore, the effect of locally charging large ore and coke particles is also studied. The results show that under the preset simulation conditions, locally charging large ore particles significantly reduces the gas pressure drop, but increases the fuel rate; however, locally charging large coke particles has limited influence on BF global performance indicators. The results provide some valuable guidance for coke and ore size selection in BF practice.

The focus of this paper is on the mechanical activation and reactivity of boehmite (γ-AlOOH) synthesized by thermal transformation (B-TH) and hydrothermal transformation (B-HT) of the same gibbsite (Al₂O₃·3H₂O) precursor. The central idea is to emphasize the role of sample genesis. The samples used had similar size distribution and largely differed in their BET surface area, 264 and 2.98 m²/g for B-TH and B-HT, respectively. Mechanical activation was carried out for different durations, up to 240 minutes, using a planetary mill. On milling, the span of change in physicochemical properties, namely geometric specific surface area, BET specific surface area, degree of amorphization, microcrystalline dimension, and macro strain (in 〈020〉/stacking direction of AlO₄(OH)₂ octahedra layers) was more for B-TH vis-à-vis B-HT. The anomalous decrease in the BET surface area reported in the literature for B-TH is not observed in B-HT. The nature of alteration in pore size distributions with milling time is used to present a plausible explanation for the contrasting change in BET surface area. The samples also showed the opposite sign for macro strain; a negative sign for B-TH which was characterized by a relatively weaker interlayer bonding. The reactivity of the samples was evaluated in terms of leachability in alkali and the lowering of boehmite to γ-Al₂O₃ transformation temperature. In general, higher reactivity was observed for B-TH vis-à-vis B-HT. The reactivity was correlated with physicochemical changes. Despite wide differences in reactivity, the change in reactivity could be expressed in terms of simple multivariate equations with high correlation coefficients.

Direct measurement of the wetting angles of the mold fluxes is a strenuous work and time-consuming, and a mathematical model relating the wetting angle of mold flux to its chemical composition is rarely found up to now. In this work, multiple linear regression (MLR), backpropagation neural network (BPNN), and GA-BP neural network (GA-BPNN) are used to model and predict the wetting angle of mold flux. Results show that the accuracy of MLR, BPNN, and GA-BPNN model is 76, 62, and 83 pct; the GA-BPNN model has the highest prediction accuracy. In addition, according to the standardized coefficients in the MLR model, the influence degree of different chemical components on the wetting angle of mold fluxes is analyzed. The importance of the influence of various components on the wetting angle is Fe₂O₃, F⁻, Li₂O, Na₂O, R, MnO, Al₂O₃, B₂O₃, and MgO from high to low. Among them, Fe₂O₃, Li₂O, Na₂O, R, and MnO have a negative effect on the wetting angle of mold flux, while F⁻, Al₂O₃, B₂O₃, and MgO have a positive effect. The established GA-BPNN model could facilitate the design and optimization of mold slag in the steel continuous casting process.

With the advancement of aerospace, military and related industries, there is a persistent escalation in the performance requirements for steel. According to the actual smelting conditions, this study focuses on Ce-containing high-aluminum steel and various refractories as its research subjects. A combination of laboratory experiments and thermodynamic calculations is employed to investigate and compare the evolution mechanism of oxide inclusions in molten steel. The use of Al₂O₃ refractory results in an increase in [Al] content, whereas both MgO refractory and MgO–MgO·Al₂O₃ refractory lead to a decrease in [Al] content. Additionally, following the utilization of MgO refractory and MgO–MgO·Al₂O₃ refractory, the molten steel exhibits the higher [Ce] content than when Al₂O₃ refractory are employed (t = 30 minutes). Before the introduction of Ce element, the principal oxide inclusions in Al₂O₃ refractory and MgO-containing refractory are Al₂O₃ and MgO·Al₂O₃ inclusion, respectively. After adding cerium-aluminum alloy, [Ce] in the molten steel replaces the element of Al in the Al₂O₃ inclusion, transforming into CeAlO₃, while [Ce] replaces the Mg element in the MgO·Al₂O₃ inclusion, evolving into Ce–Mg–Al–O, which further reacts to form CeAlO₃ and Ce₂O₂S. Over time, the number density of inclusions first increases then gradually diminishes with various refractories. MgO refractory minimizes the number density of inclusions to 53.05 mm⁻². Moreover, the number of small size inclusions in MgO–MgO·Al₂O₃ refractories is the largest, and inclusions less than 3 μm account for 78.63 pct of the total number.