Aluminum Electrolysis Research Articles

Argon anodic plasma inert anode for Low-Temperature aluminium electrolysis

The aluminum industry is one of the major causes of CO2 emissions into the atmosphere, mainly caused by carbon anode consumption and the emission of perfluorocarbon gases. Carbon anodes are consumed by anodic reactions in the standard technology. The environmental constraints and the costs associated with the utilization of carbon anodes have, for many decades, led to the look for non-consumable anodes, called “inert anodes,” considered for years to be the future of aluminum production. However, the current research on inert anodes is limited to metal, ceramic, cermet, and gas anodes and remains impotent in solving the difficulties of anode consumption, CO2, and other greenhouse gas emissions. Here, we propose the utilization of argon plasma as an inert anode for aluminum electrolysis. The results from emission spectroscopy analysis and Density Functional Theory (DFT) calculations depict a production of positively charged argon ion (Ar+) at the anode region, which infuses into the electrolyte and reacts electrochemically with the oxy-fluoro aluminate complexes (Al2OF6)2-. For a current ≤ 0.4 A, the oxygen evolution occurs anodically from 2Al2OF62- + 4Ar+ → 4AlF3 + O2 + 4Ar, with no argon consumption. Furthermore, the aluminum is reduced cathodically, and the decomposition reaction is 2Al2O3 → 4Al + 3O2. This innovative approach enables carbon-free aluminum electrolysis, a large-scale reduction in greenhouse gas (GHG) emissions, which can be extended to similar electrolytic industries.

Influence of the Sulfur Species on the Current Efficiency and Carbon Consumption in the Aluminum Electrolysis Process

The influence of sulfur species on the current efficiency and carbon consumption in the aluminum electrolysis was investigated. Prebaked and graphite anodes with varying levels of sulfur were used. It was found that increasing the sulfur content in the anodes decreases the current efficiency and increases the carbon consumption of both types of anodes. The current efficiency decreased by 1.3 pct and the carbon consumption rose by 6.1 pct per 1 wt pct S in the prebaked anodes. The addition of sodium sulfate to the electrolyte during electrolysis with graphite anodes led to a decrease in current efficiency from 0.9 to 1.0 pct per 1 wt pct S, and to an increase in carbon consumption from 3.1 to 7.0 pct per 1 wt pct S. Electrolyte analysis showed the presence of sulfates, sulfides and polysulfides. Some link between sulfur content in the anodes and sulfur content in the electrolyte and outgoing gases was found. A comparison of the polarized and non-polarized conditions showed that the electrolysis increases the sulfur depletion from the cell and promotes the formation of soluble sulfides. Reactions of sulfur participation in redox processes have also been proposed.

Resourceful reuse and performance evaluation of modified electrolytic aluminum spent cathode carbon block material as cement admixture

In order to address the environmental hazards and sustainable recycling of spent cathode carbon block (SCCB), this study designed a one-step strategy of “breaking cyanide-sinking fluoride-polydopamine wrapping” and a secondary modification of nanoscale SiO2 grafting. The impact of modified SCCB on cement was also investigated. The results showed that, after harmless treatment, the fluoride and cyanide concentrations of SCCB decreased to 7.3 mg/L (<10 mg/L) and 0.024 mg/L (<1 mg/L), respectively, thereby effectively treating harmful ions. In addition, based on the excellent mechanical properties of highly graphitized carbon blocks in SCCB and the volcanic ash effect of nanoscale SiO2, the dispersibility of SCCB in cement was enhanced, which consequently strengthened mechanical interlocking ability between SCCB and cement. This slightly improved the mechanical properties of cement mortar. These findings concurrently provide a safe and practical approach for the disposal of SCCB and a novel additive material for construction and building materials.

Ab initio investigations of crystal transition for graphite intercalation compounds during aluminum electrolysiss

This paper studies the crystal transition of graphite intercalation compounds during aluminum electrolysis. Transmission electron microscopy (TEM) analysis demonstrates that the transition induces the structural degradation of carbon cathodes. Buckling of basal planes in the hexagonal compounds contributes to the crystal transition of intercalation compounds from hexagonal to rhombohedral modification. First-principle techniques are used to calculate the structural and electronic properties of graphite intercalation compounds by density-functional theory using the plane wave Pseudo-potential method. The results have demonstrated a close relationship between lattice mismatch and intercalation compounds. The electronic band structure close to the Fermi level has been investigated. The main effect of intercalation compounds is to transfer charge from alkali metal s electron to the carbon pz orbitals, rendering the system metallic. With a decrease of band gap, the crystal transition induces an increase in the interlayer spacing and C–C bond lengths and deteriorates the structural stability of carbon cathodes. The overwhelming majority of contribution to the bands neighboring the Fermi level is from C pz orbital in both intercalation compounds. These findings provide new insights into the mechanisms of carbon cathodes deformation, damage and fracture behavior.

Modelling the formation and dissolution behavior of alumina agglomerate in the cryolite

The presence of alumina agglomerates seriously affects the current efficiency of the aluminum electrolysis process. Clarify the dynamic dissolution process of agglomerates is essential to improve the current efficiency of aluminum electrolysis. A mathematical model is proposed to describe the different phenomena from the formation until complete dissolution of agglomerates. Considering permeation and solidification processes of cryolite, a semi-analytical mathematical model is developed to formulate the formation, melting and dissolution processes of agglomerates, and the time duration for each stage is deduced. Porosity and heat mass transfer of agglomerates are explored based on the packing theory and mechanism of heat mass transfer in wet porous media. Dimensionless approach is applied to investigate the main factors affecting the dissolution stages and porosity of agglomerates. The results show that the superheat has a great influence on the formation and melting stage, the diameter of agglomerates can reach 14.93 mm for 200 particles agglomerated. The density decreases with the increase of agglomerated particle number, which varies in the range of 2.27–2.28 g/cm3. The average dissolution rate of agglomerates is about 1.83×10−5−2.95×10−5 kg/s within the range of alumina concentration in this study.

Extraction of ferronickel concentrate from laterite nickel ore by reduction roasting-magnetic separation using spent cathode carbon

Laterite nickel ores are the most important raw materials in nickel production, but processing laterite nickel ores with a low nickel content is difficult. Annually, the aluminum electrolysis industry produces a large amount of spent cathode carbon containing toxic substances, such as fluorine and cyanide, but a considerable amount of it cannot be effectively utilized. The purpose of the present study is to prepare ferronickel concentrates by reduction roasting–magnetic separation using spent cathode carbon as a reducing agent. Different factors affecting the agglomeration and growth of metal particles are studied. The migration of fluorine and the aggregation behavior of iron and nickel after the addition of spent cathode carbon and CaO are studied. Results show that the nickel grade in the ferronickel concentrate is 5.4 wt%, the nickel recovery rate is 84.80%, the iron grade is 67.93 wt%, and the iron recovery rate is 89.91%. Efficient recovery and utilization of nickel and iron in laterite nickel ores are realized. Waste utilization of spent cathode carbon thus provides a new method for the treatment of spent cathode carbon.

A Risk Characterization Model and Visualization System in Aluminum Production

Electrolytic aluminum operation accidents have caused great losses to countries and people. Therefore, taking two typical accidents of explosion and leakage in electrolytic aluminum production as the research object, the form of accident risk characterization was explored and a risk characterization visualization system was designed. Based on the methods of risk assessment and characterization, the likelihood and consequence of accidents were studied. The influencing factors of likelihood and a type of Euclidean distance formula were used to characterize the likelihood. The consequence portion was characterized by two components, with one being the failure degree determined by the accident and the other being the exposure degree of people and equipment. The intensity of event was used to characterize the failure degree and the spatial search model was used to characterize the exposure degree. Finally, the visual system of electrolytic aluminum operation accidents was established based on the risk characterization model.

Deep learning assisted physics-based modeling of aluminum extraction process

Modeling complex physical processes such as the extraction of aluminum is mainly done using pure physics-based models derived from first principles. However, the accuracy of these models can often suffer due to a partial understanding of the process, uncertainty in the input parameters, and numerous modeling assumptions. More recently, with the ever-increasing availability of data, there has been an explosion of interest in applying modern machine learning methods because of their ability to learn complex mappings directly from data. Unfortunately, these models tend to be black boxes, require an enormous amount of data, and do not utilize existing domain knowledge. In this work, we develop a novel approach combining physics-based and data-driven modeling approaches while eliminating some weaknesses. We use a data-driven model to correct a misspecified physics-based model of the Hall–Héroult process in an aluminum electrolysis cell using a corrective source term added to the set of governing ordinary differential equations. Our approach ensures that the existing knowledge is utilized to the maximum extent possible while relying on the data-driven models only to model those aspects which the physics-based model does not represent well. We compare this approach with an end-to-end learning approach and an ablated physics-based model, showing that the proposed hybrid method is more accurate, consistent, and stable for long-term predictions.

Root cause analysis for process industry using causal knowledge map under large group environment

Root cause analysis (RCA) is a powerful tool utilized to identify the underlying causes of an event or problem. However, due to the specificity of production requirements in the process industry, existing methods still face challenges such as insufficient or unreliable data, and intrinsic complexities. Therefore, RCA relies on decision making in the process industry which is actually a typical knowledge-intensive work. To address these challenges, we propose a new causal knowledge maps-based RCA method that combines a newly developed grey reasoning dynamic uncertain causality graph (GRDUCG) with an improved grey relation analysis (IGRA) technique. The proposed method utilizes GRDUCG to construct a causal knowledge map to represent the complex knowledge. Under the large group environment, the IGRA method is employed to integrate causal knowledge provided by domain experts, thus determining the parameters’ values which take the form of interval grey numbers. Due to the importance of distinguishing coefficient in IGRA, a new decision method is proposed to improve GRA instead of subjective decision based on the maximum information entropy. Root causes are identified using the maximum posterior probability on the causal knowledge map. Finally, we demonstrate the effectiveness and practicality of our proposed approach by utilizing GRDUCG-IGRA to analyze abnormal conditions in a real-world aluminum electrolysis plant.

Temperature prediction of aluminum reduction cell based on integration of dual attention LSTM for non-stationary sub-sequence and ARMA for stationary sub-sequences

In aluminum electrolysis process, cell temperature is an important index to reflect the current efficiency of electrolytic cell. Maintaining cell temperature in an appropriate range can improve current efficiency and economic benefits. Because aluminum electrolysis process is in a complex environment with high temperature, strong corrosivity, multivariable coupling and nonlinearity, cell temperature measuring instrument and equipment have the shortcomings of short service life and high cost. Therefore, this paper develops a cell temperature prediction model based on the integration of dual attention long short-term memory (DA-LSTM) and autoregressive moving average (ARMA). Firstly, the cell temperature series is decomposed into non-stationary sub-sequence and stationary sub-sequences by wavelet transform. The DA-LSTM is proposed to approximate non-stationary sub-sequence, which introduces a two-stage attention mechanism including feature attention mechanism and temporal attention mechanism. ARMA is employed to predict the stationary sub-sequences. Then, the integration model for the cell temperature prediction is reconstructed through multiple linear regression of DA-LSTM and ARMA. The integration model can overcome the problems that the prediction accuracy of a single model is low and the hysteresis phenomenon due to the mixed multi-information of aluminum electrolysis time series data. Experiments in a real-world aluminum electrolysis production process are conducted to demonstrate the effectiveness of the proposed model.

Research on microwave hydrothermal alkaline leaching defluorination of spent cathode carbon from aluminum electrolysis

Soluble fluoride present in spent cathode carbon (SCC) is a serious concern for both the environment and human health. To address this issue, the microwave hydrothermal alkaline leaching (MHAL) was used to removed the soluble fluoride from SCC. The structural characteristics and elemental distribution of SCC before and after MHAL treatment were analyzed by X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS). The effect of the primary parameters, i.e., temperature, time, and alkali concentration in the MHAL process, on the soluble fluoride removal rate was assessed using the Box-Behnken design (BBD) in response surface methodology (RSM), and subsequently optimized. The optimization results illustrate that the soluble fluoride removal rate of SCC could reach up to 98.06% under the optimum reaction conditions of 80 °C, 1.16 mol/L alkali concentration, and 8.4 min of reaction time. Under this condition, the experimental data showed that the average soluble fluoride removal rate was 97.11% and were in good agreement with the model predicted values. Furthermore, the MHAL process reduced the treatment process time by 99.4% and increased the soluble fluoride removal rate by 5.8% compared to the traditional hydrothermal treatment process. The MHAL process ensures rapid and efficient hazardous treatment of SCC while minimizing environmental pollution.

Growth behaviour of plasma electrolytic oxidation coatings produced on a SiCp/Al composite in aluminate electrolyte

Plasma electrolytic oxidation coatings was fabricated on a SiCp/Al composite in an aluminate electrolyte, and the growth behaviour of the coating was studied. The results show that PEO process can be divided into four stages: anodic oxidation stage, micro arc discharge stage, uniform spark discharge stage, arc discharge stage. The PEO coating is preferentially generated in the Al matrix and SiC-aluminum interface, then on the SiC particles. The coating grows inward and outward simultaneously. The corrosion resistance of coating is closely associated with microstructural evolution. The coating generated at 0.6 min-5 min is a single-layer structure while the coating is a double-layer structure for 10 min and 30 min. The corrosion resistance of inner barrier layer is better than that of the outer loose layer.

Dataset and formula derivation for Enhancing Electrolytic Aluminum Load to Participate in Demand Response: An Electric-thermal Coupling Model and Continuous-Time Realization

Dataset and formula derivation for Enhancing Electrolytic Aluminum Load to Participate in Demand Response: An Electric-thermal Coupling Model and Continuous-Time Realization

Efficient extraction and recovery of lithium from waste aluminum cryolite electrolyte

The accumulation of alkali metals in cryolite electrolyte has negative impacts on the operation of aluminum electrolysis, and part of electrolytes need to be periodically replaced and discharged. A cleaner and efficient process was proposed to recover LiF and Al2(SO4)3 from the waste cryolite electrolyte. Under the optimum sulfated roasting conditions, 87.55% of Li and 30.30% of Al were leached. The obtained cryolite residue with a low molecular ratio could be returned to the aluminum electrolysis system. The addition of sodium benzoate achieved the efficient separation of Al3+ from Li-containing leachate, and the Al precipitation ratio was 99.78%. Acid leaching of the aluminum precipitate regenerated benzoic acid and recovered 99.62% of Al2(SO4)3. Finally high-purity cubic LiF was prepared from Li2SO4 solution, and the recovery of LiF was 98.78%.

Microstructure and Recrystallization Behavior of Heating Rate-Controlled Electrolytic Capacitor Aluminum Foil under Cold Forming and Annealing.

A novel annealing process of controlled heating rate is used to produce severe cold-formed aluminum plates, which are processed into aluminum foil and mainly used for high-voltage electrolytic capacitor anodes. The experiment in this study focused on various aspects such as microstructure, recrystallization behavior, grain size, and grain boundary characteristics. The results revealed a comprehensive influence of cold-rolled reduction rate, annealing temperature, and heating rate on recrystallization behavior and grain boundary characteristics during the annealing process. The heating rate applied plays a crucial role in controlling the recrystallization process and the subsequent grain growth, which ultimately determines whether or not the grains will become larger. In addition, as the annealing temperature rises, the recrystallized fraction increases and the grains size decreases; conversely, the recrystallized fraction decreases as the heating rate increases. When the annealing temperature remains constant, the recrystallization fraction increases with a greater deformation degree. Once complete recrystallization occurs, the grain will undergo secondary growth and may even subsequently become coarser. If the deformation degree and annealing temperature remain constant, the increased heating rate will result in a lower recrystallization fraction. This is due to the inhibition of recrystallization, and most of the aluminum sheet even remains in a deformed state before recrystallization. This kind of microstructure evolution, grain characteristic revelation, and recrystallization behavior regulation can provide effective help for enterprise engineers and technicians to guide the production of capacitor aluminum foil to a certain extent, so as to improve the quality of aluminum foil and increase the electric storage performance.

Separation and recovery of valuable elements from acid leachate of spent carbon cathode by fractional precipitation method

Spent carbon cathode (SCC), a hazardous waste from aluminum electrolysis industry, has been confirmed that it can be direct treated and purified by hydrothermal acid leaching in the previous study. This work focuses on a hydrometallurgical process to separate and recover the valuable elements from the acid leachate of SCC by fractional precipitation method. Thermodynamic calculation, single factor experiment and characterization of the products are utilized to obtain the ion-transformation mechanism, optimize the conditions of process and confirm the physicochemical properties of the products. The results indicate that 92.6 % Si, 93.07 % Al and more than 99 % Fe, Ca are recovered from the acid leachate in the form of Na2SiF6, Na3AlF6, Fe(OH)3 and CaF2 respectively and concentration of F- in acid leachate decrease from 3115 mg/L to 6.6 mg/L when the conditions attach the optimal. Finally, Na and Cl in acid leachate is recovered in the form of NaCl via evaporation crystallization. The whole process completes the separation and recovery of all elements in acid leachate of SCC, which has no wastewater discharge and is a closed-cycle route.

Robust and Wide Temperature-Range Zinc Metal Batteries with Unique Electrolyte and Substrate Designing.

Rechargeable zinc metal batteries are promising for large-scale energy storage. However, their practical application is limited by harsh issues such as uncontrollable dendrite growth, low Coulombic efficiency, and poor temperature tolerance. Herein, a unique design strategy using γ-valerolactone electrolyte and nanocarbon-coated aluminum substrate was reported to solve the above problems. The γ-valerolactone electrolyte with extremely low freezing point and high thermal stability enables the symmetric cells with long cycle life over a wide temperature range (-50 °C to 80 °C) due to its ability to regulate zinc nucleation and preferential epitaxial growth. Besides, the nanocarbon-coated aluminum substrate can also promote a higher Coulombic efficiency over a wide temperature range in contrast to the low Coulombic efficiency of copper substrates with significant irreversible alloying reactions because this unique substrate with excellent chemical stabilization can homogenize the interfacial electron/ion distribution. The optimized zinc metal batteries can operate stably under various temperature conditions (2000 cycles at 30 °C with 66% depth of discharge and 1200 cycles at 80 °C with 50% depth of discharge). This unique electrolyte and substrate design strategy achieves a robust zinc metal battery over a wide temperature range.

Label Design and Extraction in High-Temperature Logistics Based on Concave Coding and MLFFA-DeepLabV3+ Network

Logistics tracking technology at normal temperature is quite mature, but there are few tracking methods for the high-temperature production process. The main difficulties are that the label materials generally used cannot withstand the high temperature for a long time, and the detection devices are vulnerable to environmental impact. A high-temperature logistics tracking solution was developed for a carbon anode used in an aluminum electrolysis factory. It is based on concave coding and a multiscale low-level feature fusion and attention-DeepLabV3+ (MLFFA-DeepLabV3+) network extraction technique for the coded region of the concave coding. The concave coding is printed on the product as a tag that can endure a high temperature of more than 1,200°C, ensuring its integrity and identifiability. Because there is no obvious color distinction between the coding area and the background, direct recognition is ineffective. The MLFFA-DeepLabV3+ network extracts the coding region to improve the recognition rate. The DeepLabV3+ network is improved by replacing the backbone network and adding of a multiscale low-level feature fusion module and convolutional block attention module. Experimental results showed that the mean pixel accuracy and mean intersection over union of the MLFFA-DeepLabV3+ network increased by 2.37% and 2.45%, respectively, compared with the original DeepLabV3+ network. The network structure has only 11.24% of the number of parameters in the original structure. The solution is feasible and provides a basis for high-temperature logistics tracking technology in intelligent manufacturing.

Influence of B2O3 on viscosity and structure of the CaO–Al2O3-waste electrolyte (WE) based melt

The fluorides contained waste electrolyte (WE) from the electrolytic aluminum industry can be used as a substitution of fluorite (CaF2) in the newly designed mold flux. In this study, the influence of B2O3 on viscosity and structure of CaO–Al2O3-WE based melt was investigated. Results show that the viscosity of mold flux melt decreases with both increasing temperature and B2O3 content. The apparent activation energy (Ea) also reduces from 78.96 ± 1.75 to 55.26 ± 2.79 kJ/mol with the addition of B2O3 from 0 to 7 wt%. The analyses of fourier transform infrared (FTIR) and Raman spectroscopies suggest that the lower symmetry of the original aluminate and silicate structure due to the insertion of [BO4]-tetrahedral and [BO3]-triangular, and the formation of more non-bridging oxygen (O−) and 2D structural units in the network with the addition of B2O3, deceases the viscosity and Ea of the CaO–Al2O3-WE Based Melt.

Rational design of compact ceramic coating on SiCp/Al composites by tailoring soft sparking discharge of plasma electrolytic oxidation

The characteristics of PEO processes on SiCp/Al composite in aluminate electrolyte under the influence of negative pulse were comparatively investigated, aiming to tailor the soft sparking discharge states, thus achieving the compact ceramic coating and providing a deep understanding of the mechanisms involved. Tracking the variation trend of element optical emission intensity by OES technology reflects the influence of negative voltage on the evolution of the spark state, and the results show that large negative voltage accelerates the transition from arc sparking discharge to soft sparking discharge. When the PEO process completely enters the soft spark discharge state, the lowest electron density can also be kept at 1.06 × 1022 m−3, reaching the local thermodynamic equilibrium condition. At this time, the electron temperature in the plasma discharge zone is about 4000 K. In addition, the coating surface roughness value decreases with the increase of negative voltage, and the introduction of negative voltage effectively reduces the irregular convex structures and the macropores in the coating, due to inhibiting destructive high-intensity spark discharge by the soft sparking discharge.