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Copyright of Nonferrous Metals (Extractive Metallurgy) is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The future production of electrolytic aluminum will be characterized by low temperature, low carbon emissions, and environmental friendliness, which will result in a more complex electrolyte system. Real‐time analysis of electrolytes can significantly enhance the efficiency of the electrolytic process. However, accurately analyzing the composition of complex aluminum electrolytes online has been a technical challenge. This research primarily focuses on determining the ingredient contents of complex aluminum electrolytes based on elemental concentrations measured using X‐ray fluorescence (XRF) according to an applicable standard. Calibration curves were established based on 53 standard samples of complex aluminum electrolytes to establish relationships between XRF fluorescence intensity and real concentrations. Analysis conducted on industrial complex electrolytes confirms that these newly constructed curves effectively reduce relative errors to less than 3%. Additionally, a feasible solution is proposed for determining the cryolite ratio (CR) in aluminum electrolytes using XRF. Results demonstrate an average deviation as low as approximately 0.02, fully meeting industrial production requirements. This technique offers numerous benefits including rapid analysis, ease of use, and cost savings. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As the second largest solid waste in aluminum industry after red mud, the spent cathode carbon block has significant potential pollution hazards to the ecological environment, and is rich in a large number of high-quality graphite resources, with recycling properties. In order to realize the efficient recycling of high-quality graphite resources of spent cathode carbon block, the spent cathode carbon block was treated by high pressure leaching. The differences of physical and chemical properties of spent cathode carbon block, calcined petroleum coke and recovered graphite at different stages were systematically compared, and the recovered graphite was selected and blended with calcined petroleum coke to prepare the aluminum electrolytic carbon anode. The results show that compared with the calcined petroleum coke, the recovered graphite has similar industrial composition, phase composition and element content, but there are significant differences in crystal structure and asphalt wettability. In view of this, the performance of prepared anodes drops gradually with the increase of the amount of recycled graphite. Under the condition of low content, the recycled graphite from spent cathode carbon blocks has the feasibility and application potential of mixing and preparing aluminum electrolytic carbon anode. [ABSTRACT FROM AUTHOR]

Aluminum electrolysis is a typical industry with high energy consumption, and the energy saving of aluminum electrolysis cells is conducive to the sustainable development of the ecological environment. The current density distribution on the steel claws of conventional aluminum electrolysis cells is uneven, resulting in a large amount of power loss. Therefore, a new type of current-equalized steel claw (CESC) is designed in this paper. The ANSYS simulation study shows that the CESC can achieve a more uniform current density distribution and reduce the voltage drop by about 36 mV compared with the traditional steel claw (TSC). In addition, the use of CESC optimizes the temperature distribution of the steel claws and reduces the risk of cracking and deformation. The results of the industrial application tests are highly consistent with the simulation results, confirming the accuracy of the simulation results. The economic benefit analysis shows that using CESC saves 114.1 kWh of electricity per ton of aluminum produced. If this technology can be promoted throughout China, it is expected to save up to 4.75 billion kWh of electricity annually. The development of CESC is promising and of great significance for improving the overall technical level of the aluminum electrolysis industry. [ABSTRACT FROM AUTHOR]

In aluminum electrolysis cells, the emissions of perfluorocarbons (PFCs) are not only associated with the high-voltage anode effect (cell voltage > 8 V), but continuous emissions of PFCs have also been detected during cell voltage below 8 V, especially in high-amperage prebake cells. These PFCs are referred to as low-voltage anode effect PFCs (LVAE-PFCs). In this study, the influence of current density on the formation of fluorocarbon (CFx) film was investigated on an industrial carbon anode with a bottom area of 50 cm2 in a high-temperature see-through aluminum electrolysis cell operating at 940 °C. The formation of CFx films on localized areas of the anode under normal electrolysis conditions was confirmed through observations. The quantity of peeled CFx films and the value of the back electromotive force gradually increase with increasing current density. Simultaneously, the thermal decomposition of the CFx films results in the generation of PFCs. Under conditions of sufficient alumina concentration, the peeling of the CFx films contributes to a reduction in the cell voltage. X-ray photoelectron spectroscopy analysis revealed that regions with high current density on the carbon anode provide favorable conditions for the formation of CFx components with high resistance characteristics, inevitably leading to an increase in cell voltage. [ABSTRACT FROM AUTHOR]

Industrial process data have the characteristics of heterogeneity, dimensional inconsistency and multi time scales, which increase the difficulty of condition evaluation in industrial process using multi-source data. To address these problems, a multi-source heterogeneous data fusion model is proposed for the condition evaluation of aluminum electrolysis cell. Firstly, the deep residual network (ResNet) is used to extract the superheat degree features of the fire hole video, the ResNet and wavelet packet are used to extract the cell voltage features, thereby achieving the isomorphism of heterogeneous data. An anode current features extraction method based on dynamic pivotal sequence is used to reduce the dimension of anode current data and extract features. Then, a fusion model of feature layer and data layer based on CatBoost is proposed, which comprehensively considers the material-energy balance mechanism knowledge and current efficiency to describe the dynamic coupling relationship between various data sources. The experimental evaluation results on the actual industrial aluminum electrolysis dataset show that our method improves the performance by 2.3% compared with existing multi-source data fusion method. [ABSTRACT FROM AUTHOR]

The harmless treatment and resource utilization of spent cathode carbon from the overhaul slag of aluminum electrolytic cells is the bottleneck for achieving green and sustainable development in the electrolytic aluminum industry. The migration patterns of toxic components and toxic elements in spent cathode carbon for aluminum electrolysis are introduced. The technical principle, research status, advantages and disadvantages of high temperature fire method, liquid-phase leaching method and collaborative treatment method are summarized, and the future development trend is prospected. [ABSTRACT FROM AUTHOR]

Copyright of Inorganic Chemicals Industry is the property of Editorial Office of Inorganic Chemicals Industry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

The harmless and reclamation disposal of overhaul slag, which is a hazardous waste from aluminum electrolysis, is a great challenge. Herein, a synergistic disposal strategy, i.e., adopting the overhaul slag as a raw material together with aluminum oxide in the aluminum electrolysis process to produce Al–Si alloy, was proposed. The dissolution behavior of overhaul slag in a cryolite-based molten salt system was investigated by thermodynamic calculation and dissolution experiments. The liquidus temperature of molten salt was decreased with the addition of SiO2 and Al2O3. This suggests that the synergistic disposal of overhaul slag did not cause an adverse effect on the aluminum electrolysis process. The possible dissolution products were Na3AlF6, Na5Al3F14, SiO2, NaAlSiO4, NaAlSi3O8, Na2SiO3, Na2SiF6, Na2 MgAlF7 and SiF4. The addition of Al2O3 could enhance the solubility and dissolution rate of SiO2 and hence shorten the dissolution time. The dissolution process of overhaul slag satisfied well with the mass transfer model, suggesting that the dissolution rate was controlled by the diffusion process. This work provides a basis for the synergistic disposal of overhaul slag in the aluminum electrolysis process.

Overhaul slag, aluminum ash, and carbon slag produced by the electrolytic aluminum process are typical hazardous wastes, which contain a large amount of valuable elements such as A1 and F, and have the dual attributes of environmental pollution and resource recovery. The classification and characteristics of typical hazardous wastes generated from aluminum electrolysis are summarized. Furthermore, the research progress of green and clean recycling methods for typical hazardous wastes in aluminum electrolysis is described. The advantages and disadvantages of flotation and chemical leaching methods are emphatically introduced. Finally, the development trend and direction of recycling technologies for typical hazardous waste in aluminum electrolysis are proposed. [ABSTRACT FROM AUTHOR]

Researching the aluminum molten salt system has always been challenging because of the high temperature and significant corrosion seen in the aluminum electrolysis industry. This paper employs ab initio molecular dynamics simulations to investigate the ionic structure and transport features of the K3AlF6-2.2NaF-AlF3 molten system. The findings indicate that the primary Al-F complex ion species present in K-rich molten salts are [AlF4]−, [AlF5]2−, and [AlF6]3−. The fluorine atom located at the bridge site constitutes around 3% of the overall composition, suggesting a rather modest degree of polymerization for the ionic structure. The relative diffusion rates of the ions in the system are as follows: sodium (Na) has the highest diffusion ability, followed by potassium (K), fluoride (F), and aluminum (Al). With the increase in K3AlF6 concentration, the distribution and diffusion coefficient of complex ions in the melt change, resulting in a decrease in the transport performance of the entire system. These fundamental research findings can contribute to the optimization of the aluminum electrolysis industry in the future. [ABSTRACT FROM AUTHOR]

Efficient recycling and utilization of waste heat from aluminum electrolysis cells is one of the implementation paths for the aluminum electrolysis industry to achieve deep energy conservation and carbon reduction. In response to the technical bottleneck problem of difficult recovery of waste heat on the side of aluminum electrolytic cells, a dedicated heat exchange module for waste heat recovery on the side of the electrolytic cell has been developed. The flow rate of the heat exchange medium in the module has been optimized and controlled, and the heat extraction rate has been adjusted to ensure stable operation of the electrolytic cell without affecting it. The radiant heat on the side of the electrolytic cell shell has been efficiently recovered. The technology was tested in an industrial scale on a 200 kA test cell and the results showed that the overall operation of the aluminum electrolysis cell waste heat recovery system was stable and efficient, with an average heat recovery of 77 734 kJ/h, equivalent to 21.59 kW per hour, 317 kWh per ton of aluminum, and a heat recovery efficiency of 99.71%.The system has achieved stable, efficient, and precise regulation of heat recovery within the range of 18.44-21.59 kW/h, and can optimize and regulate the furnace, which is conducive to the long-term, efficient, and stable production operation of aluminum electrolysis cells. [ABSTRACT FROM AUTHOR]

Sparsity-promoting techniques show promising results in improving the generalization of neural networks. However, the literature contains limited information on how different sparsity techniques affect generalization when using neural networks to model non-linear dynamical systems. This study examines the use of sparsity-enhancing techniques to improve accuracy and reduce the divergence rate of neural networks used to simulate such systems. A range of sparsity methods, including hard and soft thresholding, pruning and regrowing, and L1-regularization, were applied to neural networks and evaluated in a complex nonlinear aluminum extraction process by electrolysis. The results showed that the most effective technique was L1 regularization, which enhanced the important connections in the network and improved the model performance. In contrast, many of the more advanced sparsity techniques resulted in significantly worse performance and higher divergence rates. Additionally, the application of Stochastic Weight Averaging during training increased performance and reduced the number of diverging simulations. These findings suggest that carefully selecting the right sparsity techniques and model structures can improve the performance of neural network-based simulations of dynamical systems.

In the smart manufacturing sector, analyzing time series data is essential for monitoring plants and machinery to prevent costly failures or shutdowns. In order to gain new insights and make better control decisions, new methods are needed for extracting information and interpreting sensor data from hundreds of systems. In this paper, we present an approach for visualizing and interpreting sensor data from TRIMET Aluminium SE Essen (TAE) using time series meta-features and principal component analysis (PCA). We describe our general approach of generating multiple two-dimensional feature spaces to identify salient and implausible sensor data. Using a set of 20 time series meta-features, we applied our approach to sensor data from TAE which were generated by thermocouples. Each step of the approach was integrated into a dashboard to ensure a user-friendly and approachable interaction in finding salient and implausible sensor data. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • Anti-seepage mechanism of DB and the phase composition of SDB are analyzed in detail. • Previous studies have confirmed that SDB cannot be treated by VD or VSR process. • The detailed reduction sequence and mechanism of each component in SDB were obtained. • The recovery Na and F in this process can reached 95.35% and 99.68%, respectively. • The reduction slag obtained meets the standard of making new refractory materials. After the failure of an aluminum battery, a large amount of aluminum cell spent pot lining (SPL) material is produced. The second cutting material of the SPL is mainly composed of spent dry barrier (SDB) material, which is a kind of hazardous solid waste. In the present study, a vacuum aluminothermic reduction process was used to separate and recycle the SDB. The feasibility of separation of each component in the SDB under vacuum and high-temperature conditions was evaluated through thermodynamic analysis. Separate reaction experiments of aluminum and each component in the SDB were carried out, and the reaction mechanism in the aluminothermic reduction process of the SDB was examined. The optimum process conditions of the vacuum aluminothermic reduction SDB process were studied. The results showed that the recovery of sodium and fluoride in the SDB reached 95.35% and 99.68%, respectively, using a reduction temperature of 1150°C, reduction time of 2 h, and aluminum powder content of 10 wt%. The main phases in the slag after reduction were SiO 2 and Al 2 O 3 , and sodium and fluorine concentrations were below 0.1 and 0.05 wt%, respectively, which could be returned to use as raw materials for the dry barrier of aluminum cells or refractory materials. This method can realize the separation, recovery, and reuse of SDB, maximize the value-added utilization of the resource without producing waste such as slag, water, or gas, and achieve cleaner production. [ABSTRACT FROM AUTHOR]

Anode effect (AE) is influenced by adaptive spatial and temporal factors in the aluminum electrolysis process. Anode current signals (ACS) are the only online distributed signals which provide spatial temporal characteristics of AE. How to extract interpretability adaptive spatial and temporal characteristics of ACS for AE prediction is a challenging problem. In this paper, a multi-generator adversarial dynamic spatial–temporal shapelet network is proposed to capture the explainable spatial–temporal characteristics. Multi-generator adversarial training added into shapelet learning is used to reinforce the interpretability of shapelets. A dynamic distance calculation strategy is proposed to extract dynamic shapelets of multi-variable time series whose dynamic discriminative subsequence is not restricted to dimension. Based on the proposed self-regulative spatial network and diversity regularization, the extracted shapelets will have adaptive spatial networked correlations and diversity. Moreover, the proposed method can guide the domain technicians to locate the abnormal conditions. The results of experiment using real-world aluminum electrolysis plant data show that the proposed method is feasible and quite effective to detect anode effect earlier and enhance the interpretability of shapelets. [ABSTRACT FROM AUTHOR]