Journal of Sustainable Metallurgy最新文献

Pyrometallurgical processing of lateritic ore produces huge amounts of ferronickel slags, which may contain valuable metals. This paper describes a novel hydrometallurgical route to recover metals from ferronickel slag samples and reduce liability matters using oxidative acidic leaching. Hydrochloric acid and hydrogen peroxide were employed as leachants. A 2^4–1 factorial fractional design with 11 experiments was employed as a screening design to evaluate HCl concentration (3.0–6.0 mol L^–1), H₂O₂ concentration (0.5–2.5 mol L^–1), leaching time (30–240 min), and solid–liquid ratio (75–125 g L^–1). HCl and H₂O₂ concentrations were statistically significant for mass and metals leaching yields, which were studied by Doehlert design with 9 experiments with a response surface methodology (RSM). More than 80 wt% of cobalt and nickel, and ~ 75 wt% of iron were leached under the optimum region indicated by Doehlert design: 5.4–6.0 mol L^–1 HCl, 0.7–1.5 mol L^–1 H₂O₂, 25 °C, 120 min, and 100 g L^–1 solid–liquid ratio. Over 70 wt% of the slag mass was dissolved. The insoluble matter is essentially Fe₃O₄ and SiO₂. Chromium was poorly leached. The mild experimental conditions, namely temperature, leaching time, and leachant concentrations make the novel route very attractive for processing medium- to low-quality ferronickel slags and for reducing the environmental impact of this liability.

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To meet the goals of the national "Dual Carbon" strategy and reduce energy consumption in the steel industry, accurate prediction of steel composition is crucial for precise control over alloy addition in steelmaking. Several models have been created to predict the composition of the converter endpoint with a high level of accuracy. However, the different shortcomings of each have prevented large-scale application in real production environments. CBR prediction model has limited scope to solve the problem. CNN model has complex data processing and no memory. RELM model has randomly given input layer weights and hidden layer deviations. In this study, correlation analysis was used to analyze the factors influencing the carbon content at the endpoint of converter steelmaking. A feasible model was established and applied to predict the carbon content at the endpoint of converter using t-distributed stochastic neighbor embedding (t-SNE), particle swarm optimization (PSO), and backpropagation (BP) neural network. The learning rate, training times, and hidden layer nodes number of the prediction model were optimized. The prediction hit ratios for the carbon content in the error ranges of ± 0.003%, ± 0.01%, and ± 0.02% are 61%, 86%, and 98%, respectively. Meanwhile, apply the established model to actual production, the carbon content of the product can be stably controlled between the lower and median limits, the control effect is significantly better than traditional methods. The results demonstrate that the t-SNE-PSO-BP model performs better than the known models. The accurate prediction of the carbon content at the endpoint of converter can greatly contribute to realizing a “narrow composition control” of the molten steel. Realize accurate prediction of carbon content at the endpoint of converter smelting, and has been effectively applied to industrial production.

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Under the traditional method of predicting the endpoint carbon content of the converter, the hit rate of the middle and lower limits of the carbon content in the product is 48%. The t-SNE-PSO-BP model predicts the carbon content at the endpoint of the converter model, and the product carbon content can be controlled stably between 0.21–0.23%. According to the study results and actual application effects, use the t-SNE-PSO-BP model to predict the carbon content at the endpoint of the converter is appropriate, and is conducive to the “narrow composition control” of the steel composition in the converter steelmaking process.

In this paper, the vanadium extraction tailings (VT) by sodium roasting—water leaching were used to prepare the active catalyst by activate treatment to explore denitrification. The influence of activating parameters and denitrification conditions on NO_X removal of the catalyst were analyzed with selective catalytic reduction (NH₃-SCR). The surface behavior was characterized by BET, SEM, XPS, H₂-TPR, and NH₃-TPD. The results show that optimal catalyst was prepared under the conditions that acid medium was 12% (volume fraction) HNO₃, particle size of VT was less than 38 μm, and calcination temperature was 500 °C; its NO conversion rate reached 95% under the denitrification conditions of 5% O₂, 500 ppm NO, 500 ppm NH₃, and gas hourly space velocity 50000 h⁻¹. The optimal catalyst performed well for against SO₂ poisoning but bad for H₂O. The specific surface area and specific pore volume of optimal catalyst increased by 11.10 and 7.95 times compared with VT. The optimal catalyst featured a greater ratio of Fe³⁺, Mn⁴⁺, V⁵⁺, and chemisorbed oxygen, lower temperature of iron reduction, and higher H₂ adsorption peak, which were in favor of NO_X removal. Moreover, its surface acidity was enhanced reflecting in a larger NH₃ desorption peak area and a 43 °C higher desorption temperature than VT.

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The application of pressure oxidation (POX) followed by thiosulfate gold leaching is an efficient method used to extract gold from double refractory gold ores containing both sulfide and carbonaceous matter. This process is expected to result in high gold recovery rates, as it liberates gold from sulfides and eliminates the preg-robbing behavior of carbonaceous matter. Despite these expectations, the optimization study showed a maximum gold recovery of only 59% after 24 h of leaching. The optimal conditions occurred when the thiosulfate concentration was 0.14 M, the cupric ion concentration was 0.78 mM, and the temperature was set to 50 °C. To address the problem of low gold recovery, additional investigations involving kinetics tests and characterization techniques were conducted. After optimizing the conditions, it was observed that the leaching recovery was hindered at 1 h. However, this impairment did not have a significant impact on the overall recovery at 24 h. An investigation using TEM-mapping revealed that fine gold particles were disseminated within the minerals, and high concentrations of gold were also detected in locked pyritic minerals. This finding exposed the challenge of low gold recovery from alkaline POX discharge. A thiosulfate leaching test following mineral decomposition demonstrated that the complex mineralogy and poor gold liberation of the original ores were the primary factors contributing to low gold recovery. Therefore, this study suggests that increasing the degree of gold liberation is essential to address the issue of leaching recovery from alkaline POX feed.

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In this article, instead of synthesizing the electrode active material using expensive precursors that lead to high carbon emissions to the atmosphere during fabrication, an alternative engineering approach is presented for the utilization of the electric arc furnace flue dust, which is an industrial waste, as anode material in lithium-ion batteries. In this scope, firstly ball milling of the flue dust with citric acid is applied and then in situ carbonization conditions are optimized by pyrolyzing the mixture at different temperatures (600 °C and 750 °C) and times (4 h and 6 h). Every sample delivers capacities greater than graphite. Structural, morphological, and chemical characterization results demonstrate that the designed method not only promotes the formation of a nanometer-thick carbon layer formation over the particles but also induces partial phase transformation in the structure. The best performance is achieved when citric acid is used as the carbon source and the ball-milled powder is treated at 600 °C for 4 h in nitrogen (C6004): It delivers 714 mAh g⁻¹ capacity under a current load of 50 mA g⁻¹ after 100 cycles. This research is expected to set an example for the utilization of different industrial wastes in high value-added applications, such as energy storage.

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Emulsion nanofluid membranes (ENM) represent a novel category of emulsion liquid membranes (ELM), characterized by their composition as water in oil in water (W/O/W) emulsions. The present investigation focuses on the utilization of Al(OH)₃ nanofluid-based emulsion membrane for the extraction of antimony heavy metal from its aqueous solution. The ELM comprises three key components: a carrier fluid responsible for transporting the external feed to the membrane, an extractant that facilitates the extraction of the pollutant, and a stripping agent that effectively removes the pollutant and enables recycling. In the present investigation, the carrier fluid, extractant, and stripping agent employed were kerosene, 1-hexyl-3-methylimidazolium hexafluorophosphate, and NaOH, respectively. The optimization of extraction efficiency of antimony was conducted using Response Surface Methodology (RSM), with a focus on the concentrations of nanofluid, extractant, and stripping agent. With the improved emulsion stability, the formulated ENM was able to extract around 99% of antimony within 15 min. The X-ray fluorescence (XRF) analysis revealed that the formulated ENM exhibits a favorable affinity towards the elimination of heavy metals such as antimony (Sb), tin (Sn), and tellurium (Te). The recent research has demonstrated a straightforward and economically efficient treatment procedure for addressing heavy metal extraction.

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Cement industry is responsible for almost 7% of the total CO₂ emissions, where 60% of them are caused by the unavoidable CaCO₃ calcination to produce Ca-bearing cementitious phases. Meanwhile, steel industry requires substantial amounts of ferrovanadium (FeV), that is produced by aluminothermic reduction, generating calcium aluminate (CA)-rich slags. The FeV slags that are generated contain MgO that is partially or fully incorporated into magnesium aluminate spinel structure. CA phases and MA are the main mineralogical phases in calcium magnesium aluminate (CMA) cements. This makes the FeV by-products suitable alternatives of CMA cement while promoting industrial symbiosis. CMA cement, unlike Portland cement, can be the exact type of cement that is dedicated in high-temperature applications such refractory lining of steel ladles. In this publication, industrial FeV slags were size reduced to match CMA particle size distribution and evaluated as substitutes of commercial CMA cement used for alumina-spinel castables. The refractoriness experiments and the mechanical tests proved that the novel cements are efficient substitutes of CMA. The hydration and also the mechanical behavior of FeV slag-bonded castables is as sufficient as the CMA-bonded castables.

The suspension electrolysis system using sulfuric acid as the electrolyte (SE II system) provides a zero-emission strategy to recover high-purity lead from lead paste. It realized one-step lead recovery without desulfurization pre-treatment process. The dilemma of SE II system for lead past recovery is the difficulty of its main component poor conductive PbSO₄ reduction. PbSO₄ reduction with the help of PbO₂ is worthy to explore as PbO₂ is the second component and is good-conductive. In this study, through exploring the PbO₂ transformation process in SE II system, it is found that PbO₂ was firstly reduced to regular cubic structured newborn PbSO₄ crystals, and later to metal Pb with 94.12% purity. The PbO₂ and its reduction products were deposited and grown on the cathode plate to form an amorphous skeleton. The electrolysis experiment of lead paste in SE II system showed that the three-dimensional skeleton structure could wrap the raw PbSO₄ in the lead paste and then further reduce it to metal lead. The lead recovery rate was 86.26% with a purity of 97.45% Pb. The role of PbO₂ in the lead paste in the SE II system was deeply understood, which is helpful to enhance suspension electrolysis efficiency for the lead paste resource utilization in the future.

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To investigate the optimal operating conditions of a 300-ton RH vacuum refining furnace in a steel mill, a physical model of a 1/4 scale RH furnace was developed in this paper. Under the condition of fixed pressure in the vacuum chamber, the immersion depth of the snorkel and the injection gas flow rate are important conditions affecting the effect of vacuum refining. The effects of snorkel immersion depth, injection gas flow rate, and blowhole blockage on circulating flow rate, the mixing time in ladle, and residence time in vacuum chamber were systematically studied. The flow behavior and the decarburization behavior of the liquid in the vacuum chamber were analyzed. The influence law of RH blowhole blockage on the vacuum refining effect was also studied. As a result, the optimum production process suitable for the production of 300-ton RH furnace was deduced (the optimal immersion depth is 0.52–0.54 m, the recommended injection flow rate used in the early stage of decarbonization is about 160–180 m³/h), which provides guidance for its efficient production.

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With the purpose of recovering the metal values, in this study the copper slag was reduced by coke and biochar at 1250 °C in an argon gas atmosphere using the isothermal reduction/drop quenching technique. The phase compositions of metal, matte, and slag were determined using electron probe microanalysis (EPMA). The effects of reduction time and amount of reductant were investigated. The distribution of elements between metal/matte and slag was ascertained based on the elemental concentrations determined by EPMA. It was found that copper concentration in slag can be effectively decreased to approximately 0.4–0.6 wt% within 5 min by coke and biochar. Copper and nickel can also be successfully recovered into the copper alloy phase once settling has been accomplished.

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