Search Results (46)

In the aluminum electrolysis production process, the traditional cell control method based on cell voltage and series current can no longer meet the goals of energy conservation, consumption reduction, and digital-intelligent transformation. Therefore, a new digital cell control technology that is centrally dependent on various process parameters has become an urgent demand in the aluminum electrolysis industry. Among them, the real-time online measurement of alumina concentration is one of the key data points for implementing such technology. However, due to the harsh production environment and limitations of current sensor technologies, hardware-based detection of alumina concentration is difficult to achieve. To address this issue, this study proposes a soft-sensing model for alumina concentration based on a long short-term memory (LSTM) neural network optimized by a weighted average algorithm (WAA). The proposed method outperforms BiLSTM, CNN-LSTM, CNN-BiLSTM, CNN-LSTM-Attention, and CNN-BiLSTM-Attention models in terms of predictive accuracy. In comparison to LSTM models optimized using the Grey Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), Optuna, Tornado Optimization Algorithm (TOC), and Whale Migration Algorithm (WMA), the WAA-enhanced LSTM model consistently achieves significantly better performance. This superiority is evidenced by lower MAE and RMSE values, along with higher R² and accuracy scores. The WAA-LSTM model remains stable throughout the training process and achieves the lowest final loss, further confirming the accuracy and superiority of the proposed approach. Full article

This paper is devoted to the problem of magnetohydrodynamic stability (MHDS) in the energy-intensive process of primary aluminum production by electrolysis. Improving MHDS control is important because of the high costs and reduced efficiency caused by the instability of magnetic and current fields. In this work, a methodological analysis of modern theoretical and numerical methods for studying MHDS was carried out, and approaches to optimizing magnetic fields and control algorithms aimed at stabilizing the process and reducing energy costs were considered. This review identified key challenges and proposed promising directions, including the application of computational methods and artificial intelligence to monitor and control electrolysis in real time. In this paper, it was revealed that wave MHD instability at the metal–electrolyte phase boundary is a key physical obstacle to further reducing specific energy costs and increasing energy stability. The novelty of this paper lies in an integrated approach that combines modeling and practical recommendations. The purpose of this study is to systematically summarize scientific data, analyze the key physical factors affecting the energy stability of electrolyzers, and determine promising directions for their solution. The results of this study can be used to improve the energy efficiency and environmental friendliness of aluminum production. Full article

The problem of the adhesion of aluminum slag to the inner wall of a vacuum ladle is essential but has not been addressed. Using a high-temperature wettability experimental setup, this paper investigates the mechanism of interfacial wettability, adhesion, and penetration between Na₃AlF₆-Al₂O₃-CaF₂ cryolite-based molten salt and SiC refractory substrate. The composition of the slag was determined based on the slag obtained in the transfer ladle during the aluminum electrolysis process. We mainly study the effects of different Al₂O₃ contents in cryolite-based molten salt and temperatures on the contact angle and surface tension. The results indicate that as the Al₂O₃ content in the slag increases, the contact angle decreases, enhancing the slag’s wettability on the SiC substrate. Additionally, a higher Al₂O₃ content leads to higher slag melting temperatures and surface tension, which improves the slag mobility and enhances the mass transfer and diffusion capabilities of molecules or ions within the slag. The work of adhesion, calculated using the Mills model, also increases with the increasing Al₂O₃ content. The increased Al₂O₃ concentration activates the activity of Na₃AlF₆ in the slag, facilitating the dissolution reactions and improving the wettability between the slag and SiC. Moreover, the wetting behavior of the Na₃AlF₆-Al₂O₃-CaF₂ slag is primarily influenced by the initial Al₂O₃ content and its compositional changes. The results show that the slag penetration resistance and mechanical erosion resistance of the ladle lining can be improved by using an SiC-based refractory with an optimized Al₂O₃ content. This will have important guiding significance for the development, design, and application of inner wall materials for aluminum electrolysis industrial vacuum ladles. Full article

The comprehensive recycling of aluminum electrolysis cell waste barrier material is urgent. This study focuses on the sulfuric acid leaching of waste barrier material, systematically examining the effects of factors such as reaction temperature, liquid-to-solid ratio, sulfuric acid concentration, and reaction time on the leaching of elements like lithium, aluminum, sodium, and silicon. The experimental results show that under the conditions of 0.9 mol/L sulfuric acid concentration, a liquid-to-solid ratio of 20:1, a reaction temperature of 90 °C, and a reaction time of 1.5 h, the leaching rates were 84.5% for lithium, 85.6% for aluminum, 98.5% for sodium, and 4.8% for silicon. The sulfuric acid leaching process of the waste barrier material follows a shrinking core model and is controlled by internal diffusion. The apparent activation energies for the leaching reactions of lithium, aluminum, and sodium were 4.29 kJ/mol, 8.99 kJ/mol, and 9.11 kJ/mol, respectively. The selective leaching of lithium, sodium, and aluminum from silicon was successfully achieved in the sulfuric acid leaching of the waste barrier material. Full article

In the aluminum electrolysis production workshop, heavy-load overhead cranes equipped with multi-functional operation terminals are responsible for critical tasks such as anode replacement, shell breaking, slag removal, and material feeding. The real-time monitoring of these four types of operation terminals is of the utmost importance for ensuring production safety. High-resolution cameras are used to capture dynamic scenes of operation. However, the terminals undergo morphological changes and rotations in three-dimensional space according to task requirements during operations, lacking rotational invariance. This factor complicates the detection and recognition of multi-form targets in 3D environment. Additionally, operations like striking and material feeding generate significant dust, often visually obscuring the terminal targets. The challenge of real-time multi-form object detection in high-resolution images affected by smoke and dust environments demands detection and dehazing algorithms. To address these issues, we propose the YOLOv8n-Al-Dehazing method, which achieves the precise detection of multi-functional material handling terminals in aluminum electrolysis workshops. To overcome the heavy computational costs associated with processing high-resolution images by using YOLOv8n, our method refines YOLOv8n through component substitution and integrates real-time dehazing preprocessing for high-resolution images, thereby reducing the image processing time. We collected on-site data to construct a dataset for experimental validation. Compared with the YOLOv8n method, our method approach increases inference speed by 15.54%, achieving 120.4 frames per second, which meets the requirements for real-time detection on site. Furthermore, compared with state-of-the-art detection methods and variants of YOLO, YOLOv8n-Al-Dehazing demonstrates superior performance, attaining an accuracy rate of 91.0%. Full article

To address the challenge of the real-time monitoring of alumina concentrations during the production process, this paper employs a Deep Belief Network (DBN) within the framework of deep learning to predict alumina concentration. Additionally, the improved Grey Wolf Optimizer (IGWO) is utilized to optimize key parameters of the DBN model, including the number of hidden layer nodes, reverse iteration count, and learning rate. An IGWO-DBN hybrid model is then constructed and compared against DBN models optimized by other techniques, such as the Sparrow Search Algorithm (SSA) and Particle Swarm Optimization (PSO), to evaluate the predictive performance. The comparative analysis reveals that, in terms of predictive accuracy, the IGWO-DBN model outperforms both the SSA-DBN and PSO-DBN models. Specifically, it achieves lower root mean square errors (RMSE) and mean absolute errors (MAE), alongside a higher coefficient of determination (R²). Furthermore, the IGWO-DBN model exhibits a faster convergence rate and a lower final convergence value, indicating superior generalization ability and robustness. Furthermore, the IGWO-DBN model not only demonstrates significant advantages in prediction accuracy for alumina concentration but also substantially reduces model training time through its efficient parameter optimization mechanism. The successful implementation of this model provides robust support for the intelligent and refined management of the aluminum electrolysis industry, aiding enterprises in reducing costs, improving production efficiency, and advancing the green and sustainable development of the industry. Full article

Life cycle assessment (LCA) is used to quantitatively analyze the energy consumption and environmental impact of primary aluminum production in China, the United States, and Europe, as well as global average. The results indicate that electricity and fuel contribute more than 60% of the environmental impact of bauxite mining; steam is the greatest contributor to the environmental impact of alumina production by the Bayer process, with a result exceeding 35%; and electricity contributes >50% of the environmental impact of aluminum electrolysis. The environmental impact of primary aluminum production in China is 1.2 times the global average. The contributions of the three stages of primary aluminum production to the total environmental impact of the process in China are, in descending order, aluminum electrolysis (64.33%), alumina production (33.09%), and bauxite mining (2.58%). If the proportion of thermal power in the electricity source structure is reduced from 60% to 0%, the contribution of electricity to the environmental impact of primary aluminum production will decrease from 38% to 2%, and the total environmental impact will decrease by 73%. Therefore, energy conservation and emissions reduction can be realized through the optimization of the power generation structure, adoption of clean energy production, and improvement of the heat utilization rate in production processes. Full article

The use of reduction leaching in the production of alumina from bauxite by the Bayer process in order to decrease the amount of waste (bauxite residue) by adding elemental iron or aluminum, as well as Fe²⁺ salts and organic compounds in the stage of high-pressure leaching, requires the purchase of relatively expensive reagents in large quantities. The aim of this study was to investigate the possibility of the use of electrolytically reduced bauxite residue (BR) as a substitute for these reagents. Reduced BR was obtained from Al-goethite containing BR using a bulk cathode in alkaline suspension. The degree of deoxidation of Fe³⁺ compounds was 55% after 2 h of electrolysis with a current yield of more than 73%. The addition of reduced BR according to the shrinking core model leads to a change in the limiting stage of the high-pressure boehmitic bauxite leaching from a surface chemical reaction to internal diffusion. The activation energy decreased from 32.9 to 17.2 kJ/mol by adding reduced red mud. It was also shown that the addition of reduced BR increased the rate of thickening of the slurry after leaching by a factor of 1.5 and decreased the Na₂O losses by 15% without the addition of lime. The solid residue was examined by means of X-ray diffraction analysis and scanning electron microscopy to confirm the presence of magnetite and elemental iron. A preliminary techno-economic analysis was carried out to assess the applicability of the proposed process. Full article

The objective of this study is to examine the effectiveness of the electrocoagulation (EC) process in treating real produced water (PW). The impact of the EC process on water quality parameters (pH and conductivity, turbidity, and oil content) was studied using bench-scale 5 L PW for this process. The findings indicate that prolonged EC leads to the release of metal ions and secondary electrode reactions, which resultantly increase the pH of the outlet water. The EC process decreased in several water quality parameters, including Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), and oil and grease (O&G). COD decreased by roughly 1300 mg/L, resulting in a 33% removal. In the same manner, TOC dropped from an initial value of 1300 mg/L to approximately 585 mg/L, exhibiting a maximum removal efficacy of nearly 60%. Oil and gas (O&G) decreased to a value below 10 mg/L, accompanied by a remarkable removal efficacy of up to 99.6%. The turbidity, which was initially recorded at an average of 160 NTU, was reduced to approximately 70 NTU, which is a 44% reduction. The application of centrifugation after EC treatment resulted in a turbidity reduction above 99%. EC treatment removed BTEX (benzene, toluene, ethyl benzene, and xylenes) from PW by more than 99%. The inorganic constituents, specifically heavy metals, exhibited minimal changes following the application of EC, emphasizing the necessity for additional treatment methods to effectively address their presence. In summary, EC demonstrates an acceptable level of efficacy in the removal of turbidity and pollutants from PW, with a special emphasis on organic compounds such as BTEX, but it does not address the elimination of inorganic compounds. Subsequent investigations should prioritize the optimization of EC parameters and the integration of supplementary interventions to effectively address the removal of inorganic elements and insoluble metals from treated PW. The study evaluates the pollutant removal efficiency using iron and aluminum electrodes and the effects of the applied current and electrolysis time on the EC process. Full article

Spent carbon cathode (SCC) is one of the major hazardous solid wastes generated during the overhaul of electrolysis cells in the aluminum production process. SCC is not only rich in carbon resources but also contains soluble fluoride and cyanide, which gives it both recycling value and significant leaching toxicity. In this study, we explore the properties, emissions, and disposal strategies for SCC. Pyrometallurgy involves processes such as vacuum distillation, molten salt roasting, and high-temperature roasting. Hydrometallurgy describes various methods used to separate valuable components from leachate and prepare products. Collaborative disposal plays a positive role in treating SCC alongside other solid wastes. High-value utilization provides an approach to make full use of high-purity carbon-based materials. Finally, we analyze and summarize future prospects for the disposal of SCC. This study aims to contribute to the large-scale treatment and resource utilization of SCC while promoting circular economy principles and green development initiatives. Full article

The addition of rare earth metals to aluminum alloys can effectively improve their corrosion resistance and has been widely used in the aerospace and military industries. However, the current methods for the preparation of rare earth metals involve long processing steps, high energy consumption, and high carbon emissions, which severely constrains the development of aluminum alloys. Its output is further developed. To this end, this paper reviews mainstream rare earth production processes (precipitation methods, microemulsion methods, roasting-sulfuric acid leaching methods, electrochemical methods, solvent extraction methods, and ion exchange methods) to provide basic information for the green smelting of rare earth metals and help promote the development of green rare earth smelting. Based on the advantages and disadvantages of each process as well as recent research results, the optimal process parameters and production efficiency were summarized. Studies have concluded that the precipitation method is mostly used for the recovery of rare earth elements and related valuable metals from solid waste; the microemulsion method is mostly used for the preparation of nanosized rare earth alloys by doping; the roasting-sulfuric acid leaching method is mostly used for the treatment of raw rare earth ores; and the molten salt electrolysis method is a more specific method. This is a green and environmentally friendly production process. The results of this study can provide direction for the realization of green rare earth smelting and provide a reference for improving the existing rare earth smelting process. Full article

In the abnormal situation of an aluminum electrolysis cell, the setting of cell voltage is mainly based on manual experience. To obtain a smaller cell voltage and optimize the operating parameters, a multi-objective optimization method for cell voltage based on a comprehensive index evaluation model is proposed. Firstly, a comprehensive judgment model of the cell state based on the energy balance, material balance, and stability of the aluminum electrolysis process is established. Secondly, a fuzzy neural network (FNN) based on the autoregressive moving average (ARMA) model is designed to establish the cell-state prediction model in order to finish the real-time monitoring of the process. Thirdly, the optimization goal of the process is summarized as having been met when the difference between the average cell voltage and the target value reaches the minimum, and the condition of the cell is excellent. And then, the optimization setting model of cell voltage is established under the constraints of the production and operation requirements. Finally, a multi-objective antlion optimization algorithm (MOALO) is used to solve the above model and find a group of optimized values of the electrolysis cell, which is used to realize the optimization control of the cell state. By using actual production data, the above method is validated to be effective. Moreover, optimized operating parameters are used to verify the prediction model of cell voltage, and the cell state is just excellent. The method is also applied to realize the optimization control of the process. It is of guiding significance for stabilizing the electrolytic aluminum production and achieving energy saving and consumption reduction. Full article

As one core component in hydrogen fuel cells and water electrolysis cells, bipolar plates (BPs) perform multiple important functions, such as separating the fuel and oxidant flow, providing mechanical support, conducting electricity and heat, connecting the cell units into a stack, etc. On the path toward commercialization, the manufacturing costs of bipolar plates have to be substantially reduced by adopting low-cost and easy-to-process metallic materials (e.g., stainless steel, aluminum or copper). However, these materials are susceptible to electrochemical corrosion under harsh operating conditions, resulting in long-term performance degradation. By means of advanced thermal spraying technologies, protective coatings can be prepared on bipolar plates so as to inhibit oxidation and corrosion. This paper reviews several typical thermal spraying technologies, including atmospheric plasma spraying (APS), vacuum plasma spraying (VPS) and high-velocity oxygen fuel (HVOF) spraying for preparing coatings of bipolar plates, particularly emphasizing the effect of spraying processes on coating effectiveness. The performance of coatings relies not only on the materials as selected or designed but also on the composition and microstructure practically obtained in the spraying process. The temperature and velocity of in-flight particles have a significant impact on coating quality; therefore, precise control over these factors is demanded. Full article

The recovery and recycling of metals that generate toxic ions in the environment is of particular importance, especially when these are tungsten and, in particular, thorium. The radioactive element thorium has unexpectedly accessible domestic applications (filaments of light bulbs and electronic tubes, welding electrodes, and working alloys containing aluminum and magnesium), which lead to its appearance in electrical and electronic waste from municipal waste management platforms. The current paper proposes the simultaneous recovery of waste containing tungsten and thorium from welding electrodes. Simultaneous recovery is achieved by applying a hybrid membrane electrolysis technology coupled with nanofiltration. An electrolysis cell with sulphonated polyether–ether–ketone membranes (sPEEK) and a nanofiltration module with chitosan–polypropylene membranes (C–PHF–M) are used to carry out the hybrid process. The analysis of welding electrodes led to a composition of W (tungsten) 89.4%; Th 7.1%; O₂ 2.5%; and Al 1.1%. Thus, the parameters of the electrolysis process were chosen according to the speciation of the three metals suggested by the superimposed Pourbaix diagrams. At a constant potential of 20.0 V and an electrolysis current of 1.0 A, the pH is varied and the possible composition of the solution in the anodic workspace is analyzed. Favorable conditions for both electrolysis and nanofiltration were obtained at pH from 6 to 9, when the soluble tungstate ion, the aluminum hydroxide, and solid thorium dioxide were formed. Through the first nanofiltration, the tungstate ion is obtained in the permeate, and thorium dioxide and aluminum hydroxide in the concentrate. By adding a pH 13 solution over the two precipitates, the aluminum is solubilized as sodium aluminate, which will be found after the second nanofiltration in the permeate, with the thorium dioxide remaining integrally (within an error of ±0.1 ppm) on the C–PHF–M membrane. Full article

The aluminum electrolysis industry continually and unavoidably produces hazardous solid waste in the form of carbon anode slag. Carbon anode slag poses a serious environmental pollution risk, and it must be disposed of in a harmless manner. On the other hand, it contains a few valuable resources, as well. In order for the aluminum electrolysis industry to develop in an environmentally friendly and high-quality manner, the harmless disposal of carbon anode slag and its resourceful utilization are of considerable importance. The selective comminution of carbon and cryolite particles in carbon anode slag can be effectively achieved with grinding pretreatment. However, the optimization study of grinding process parameters has yet to be investigated. Therefore, firstly, the mineralogical characteristics and existing mode of carbon anode slag from the perspective of mineralogical properties are analyzed in this study. Then, the effects of grinding time, grinding concentration, and steel ball diameter on the particle size of the ground product (γ_{−0.074 mm}) are investigated using response surface analysis. The results showed that the effect of grinding time was the most significant, followed by grinding concentration and steel ball diameter. In addition, the performance of the multi-stage flotation process for separating the −0.074 mm ground product was analyzed. Cryolite with a purity of 93.12% and a carbon product with an ash content of 10.67% could be simultaneously obtained through multi-stage flotation. It should be pointed out that the deep dissociation and efficient recovery of fine undissociated particles still need to be further explored. Full article