The dynamic mixer is the mainstream of today's mixing equipment, and the mixing effect not only affects the production efficiency of the equipment, but also directly determines the performance of the final product. Among them, the structure of the mixing element in the dynamic mixer directly determines its mixing effect on the processed material. Due to the complex structure of the dynamic kneading mixer, the theoretical research on its mixing characteristics is very limited. In this work, the blade structure of the horizontal mixer was optimized and improved, and the structure design of the main and auxiliary blades was adopted to improve the mixing effect of the mixer. By constructing the three-dimensional model and finite element model of the mixer with a new type of blade structure, the mixing characteristics of the mixer were investigated by means of numerical simulation using the computational fluid dynamics software Polyflow, and the influence of blade speed on the mixing performance of the mixer was analyzed. Mixing index, separation scale, average tensile rate, logarithmic tensile rate, and cumulative depolymerization power were used to characterize the dispersion and distribution mixing ability of the mixer, and the accuracy of numerical simulation results was verified by visual experiments. The results of simulation and experiment showed that the simulation results were consistent with the visual experiment results. The material flow type in the mixer with the new blade structure was shear flow, accounting for about 85%. The average tensile rate and average logarithmic tensile rate in the flow field were always positive, indicating that the mixer had good distribution and dispersion mixing ability. The increase of blade speed had little influence on the flow type of materials in the flow field, but can effectively improve the performance of distributed mixing and dispersed mixing of the mixer. When the blade speed increased from 30 r/min to 120 r/min, the average separation scale of the mixer's transverse distribution mixing decreased by 50%, and the average tensile rate increased by 300%. The average cumulative depolymerization work increased by 1500%.

Methane enrichment is a necessary measure to develop and utilize low concentration coalbed methane. Among many separation technologies, pressure swing adsorption technology has become the most widely used technology in recent years due to its advantages of low energy consumption and low cost. In order to better realize the methane enrichment effect (purity and recovery), it is necessary to study the relationship between the adsorbent and the pressure swing adsorption process, that is, to select a suitable pressure swing adsorption process for the adsorbent. This work uses Aspen adsorption process simulation software to study two different types of adsorbents (N2 selective adsorbent MIL-100(Cr) and CH4 selective adsorbent Silicalite-1) in common and optimal vacuum pressure swing adsorption (adding buffer tank). Simulation results shows that the optimal vacuum pressure swing adsorption process can effectively improve the CH4 recovery, and MIL-100(Cr) has a significantly better recovery improvement effect compared with Silicalite-1. However, when the CH4 content of the coalbed methane is less than 30%, CH4 recovery of 100% can be achieved by using Silicalite-1 adsorbent in the optimal vacuum pressure swing adsorption process. In the actual process of enriching coalbed methane, methane purity and recovery are very important indicators. Therefore, the single cycle efficiency index is proposed to comprehensively evaluate the efficiency of the methane enrichment process. The results show that compared with the common vacuum pressure swing adsorption process, the optimal vacuum pressure swing adsorption process using MIL-100(Cr) adsorbent has a single cycle efficiency improvement of more than 30 percentage point, while that of Silicalite-1 adsorbent even slightly decline 1 percentage point. Comparative analysis shows that the common vacuum pressure swing adsorption process is suitable for Silicalite-1 adsorbent, and the optimal vacuum pressure swing adsorption process with buffer tank is more suitable for MIL-100(Cr) adsorbent.

The Ca(OH)2/CaO thermochemical energy storage technology has garnered significant attention owing to its attractive features of high energy storage density and cost-effectiveness, positioning it as a promising advancement in energy storage methodologies. Nonetheless, traditional fixed bed reactors may pose challenges with their potential to yield a diminished heat storage rate for Ca(OH)2 particles. To address the challenge of low heat storage rate in conventional fixed bed reactor, a novel baffled moving bed structure is introduced. The heat storage process of Ca(OH)2 particles in the moving reactor bed under the influence of gravity is studied by using the coupled method of computational fluid dynamics and discrete element method (CFD-DEM). Compared to porous media models, CFD-DEM offers a closer approximation to real flow conditions and provides detailed physical information at the particle scale. The results indicate that the moving bed achieves a higher heat storage rate compared to its fixed bed counterpart under identical conditions, providing evidence for the feasibility of employing a moving bed as a thermochemical reactor. The introduction of baffles in the moving bed is able to extend the particle residence time in the reactor, consequently amplifying both the heat storage rate and energy storage efficiency. However, it concurrently results in an increased pressure drop on the gas side. The simulations under various inlet conditions reveal that elevating the gas temperature at the reactor inlet positively impacts the heat storage rate. Within specific ranges, an increase in the inlet gas flow rate can improve the energy storage rate, albeit with caution against excessively high flow rates that could induce blockages and diminish the overall heat storage rate. Notably, the inlet solid flow rate exhibits an optimum value, maximizing the comprehensive heat storage rate of the reaction bed.

Computational fluid dynamics (CFD) is a commonly used method to simulate complex gas-solid flow in fluidized beds. Due to the solution of partial/ordinary differential equations, the computational efficiency of this method is still low even if the coarse-grained method is used. The flow field simulation method based on data-driven artificial neural network (ANN) model can avoid the equation solving process and achieve efficient calculation. At present, researchers have applied the ANN model to the prediction of single-phase flow field, and there are only a few studies on the complete fluidized gas-solid two-phase flow field. This work combines CFD and ANN to develop an ANN based field evolution model that quickly obtains the evolution of the flow field in the fluidized bed. Compared with those complex large models, a compact network model has been developed and can be used to complete the prediction of complex two-phase flow field. The model includes different network structures for predictions of particle concentration, gas pressure, and gas-solid two-phase velocity. The results obtained by simulating the fluidized bed with the multiphase particle-in-cell (MP-PIC) method are used as data sets for training. The verification results show that the ANN model successfully realizes the prediction of particle concentration, gas pressure, and gas-solid two-phase velocity in the fluidized bed. In terms of accuracy, the ANN model can accurately predict the flow field in a time step, and there are still obvious errors in the long-term flow field prediction. In terms of computational efficiency, the calculation speed of the ANN model is about 13 000 times that of the MP-PIC method. The multi-time-step continuous prediction performance of current model gradually deteriorates with time, and further research still needs to be done to improve this issue.

Severe environmental protection policies have put forward higher requirements for coal combustion power generation. As a mature clean coal power generation technology, the circulating fluidized bed (CFB) boiler has broad research prospects. CFB post-combustion technology is a new type of fluidized bed out-of-stock technology that has been applied to 75 t/h CFB coal slime boilers and achieved ultra-low NOx emissions. Exploring the feasibility and effectiveness of post-combustion technology in larger-scale CFB boilers has become the focus of future research. In this study, a numerical model of the flow and combustion of a 150 t/h CFB boiler in full-loop was established using the method of computational particle fluid dynamics (CPFD). The availability of the model was verified by comparing it with industrial data. The effects of excess air ratio in CFB, primary air ratio, and ratio of upper and lower secondary air on furnace combustion and NOx emissions were studied after the addition of post-combustion technology. The results showed that there was a typical core-circulation structure in the furnace. On the one hand, oxygen-poor combustion inhibited NOx generation, and on the other hand, the high CO concentration zone caused by combustion was also conducive to NOx reduction. After the use of post-combustion technology, the reduction atmosphere of the furnace increased, and the NOx emission reduced from 174.6 mg/m3 to 114.2 mg/m3. Combined with the air stage, optimizing the primary air ratio and the ratio of upper and lower secondary air, CO emission increased from 3.4×10-5 in the basic working condition to 7.1×10-5, the combustion efficiency was slightly reduced, and NOx emission was further reduced. Under optimal working conditions, NOx emission decreased from 174.6 mg/m3 to 76.3 mg/m3, NOx emission decreased by 56.3%, and the furnace temperature distribution was uniform. The research results can provide valuable theoretical insights for the application of post-combustion technology in CFB boilers and provide support for its practical application.

In order to increase the service temperature of mild steel, the 9Cr-1Mo coating was prepared on Q235 base material using cold metal transition welding (CMT) technique. Significant residual stresses are formed in the fusion zone and heat-affected zone of the substrate after cladding due to thermal effects of welding. The residual stress distribution was measured by blind hole drilling method, and a finite element model was developed by SYSWELD software to simulate the temperature and stress field distribution of CMT cladding 9Cr-1Mo coating. The effect of martensitic phase transformation on the residual stress distribution was analyzed. The results showed that the coating was mainly martensitic, and the heat affected zone (HAZ) was mainly consisted of ferrite and pearlite. Multiple thermal cycles in multi-pass welding had a significant effect on the evolution of residual stress in the coating. Welding thermal cycles in the later passes can redistribute the stress generated during the fusion of the first passes and simultaneously change the direction and magnitude of the residual stress. Compressive residual stress formed in the cladding layer due to martensitic transformation, while the tensile stress mainly distributed on the HAZ and adjacent base metal. Among them, the maximum transverse residual tensile stress located in the HAZ adjacent to the fusion line, with a peak value of 300 MPa, and the compressive stress were concentrated on the fusion cladding layer near the fusion depth with a peak value of -200 MPa. The highest longitudinal residual tensile stress appeared in the heat affected zone between the weld passes, and the peak value reaches 550 MPa, and the peak of the compressive stress occurred at the bottom of the passes with a peak value of -400 MPa. The distribution of residual stress in the surface layer was caused by martensitic transformation and thermal cycling in the pass after welding. The simulation results agreed well with the experimental results.

In consideration of the real-time, multi-dimensional, and nonlinear nature of chemical process parameters, as well as the complexity of chemical processes with numerous mutually interfering factors and single warning method, this work proposes an early warning method combining deep learning regression prediction and ADF (Augmented Dickey-Fuller) test. For monitoring and early warning analysis of over-temperature abnormal conditions in condensation reactions, convolutional neural network, and long short-term memory (CNN-LSTM) models are employed in this study to predict crucial process parameters for the next 400 s. Simultaneously, the ADF test is utilized to examine the trend of temperature time series parameters. When the result is an unstable trend and the CNN-LSTM model predicts that the temperature will exceed the alarm threshold at a specific time point, security personnel will be alerted accordingly. The results showed that during the condensation reaction's over-temperature anomalies at feed rates of 700 and 800 kg/h, the CNN-LSTM model's regression forecasting for temperature metrics manifested R2 values of 0.9827 and 0.9882. Correspondingly, the model elicits RMSE (Root Mean Square Error) values of 0.1425 and 0.1453, and MAE (Mean Absolute Error) values of 0.1184 and 0.1234. These indices testify to the model's exceptional fidelity and precision, surpassing the conventional LSTM model's predictive accuracy as reflected in its R2, RMSE, and MAE values. The ADF test results on the temperature time series data corroborate the presence of an unstable trend, aligning with the actual process behavior. By combining both methods, the early warning model is able to detect temperatures exceeding the alarm threshold 18 and 16 s earlier than the simulated alarm point, respectively, and issues a timely alert. The dual application of these methods provides a robust means of monitoring chemical process parameters, enabling the early detection of abnormal conditions in chemical processes and advancing the field of chemical process parameter monitoring.

In response to the challenges posed by the high energy consumption, poor environmental performance, and low production efficiency associated with the lightly burnt magnesia rotary kiln, researchers have introduced a promising solution in the form of a new calcination furnace that exhibits substantial energy-saving potential. However, to further enhance the effectiveness of this innovative furnace and refine the production processes, it is imperative to gain a more comprehensive understanding of the thermal decomposition kinetics of magnesite. This research is rooted in an analysis of the gas phase composition within the furnace during the actual production of magnesite calcination. Employing the TG-DTA thermal analysis technique, the study investigates the thermal decomposition kinetics of magnesite under N2 and CO2 atmospheres. The findings reveal that under N2 atmosphere, the thermal decomposition kinetics of magnesite involves two distinct stages: the phase boundary reaction shrinkage columnar mechanism and the random nucleation and growth mechanism. On the other hand, under the CO2 atmosphere, the kinetics process consists of three stages with two mechanism modes, including the random nucleation and growth mechanism, as well as the phase boundary reaction shrinkage spherical mechanism. Furthermore, the study's analysis indicates that the impact of CO2 on the thermal decomposition process of magnesite is twofold. On one hand, CO2 raises the activation energy of the reaction, resulting in an elevated decomposition reaction temperature. Conversely, CO2 also has the capacity to induce the nucleation and growth of the product CO2, thereby making the decomposition reaction rate more sensitive to the change of temperature. The present work's elucidation of the kinetic mechanisms governing magnesite thermal decomposition under N2 and CO2 atmospheres not only provides valuable data to support the optimization of the new type of calcination furnace, which has important engineering application prospects, and can also provide reference value for further research . Expanding upon these insights through further research and development endeavors holds the potential to drive substantial advancements in the field of magnesite processing and contribute to the overall sustainability of industrial processes.

High-purity copper has been widely used in semiconductor materials, optoelectronics and other fields due to its excellent physical and chemical properties such as ductility, thermal conductivity and electric conductivity. With the rapid development of electronic information industry, the copper product with high purity is pressing needed. Numerous methods such as zone melting, electron beam melting and electrolytic refining have been developed for the preparation of high-purity copper. Among these technologies, electrolytic refining has been investigated extensively and used in the industrial production for high-purity copper owing to its operation flexibility, simple-process and environmental-friendliness. In general, the electrolytic refining methods for the preparation of high-purity copper could be divided into nitric acid system and sulfuric acid system electrolytic refining. The electrolytic refining for high-purity copper preparation in sulfuric acid system has been widely used in industry. However, the high-purity copper prepared in sulfuric acid system generally contains the higher content of impurity elements such as S than in nitric acid system. Therefore, in this study, the 5N purity of copper was prepared from the raw materials of 4N copper in nitric acid system by one-step electrorefining. The effects of H2O2 addition, current density, electrolyte pH, Cu2+ concentration during the electrorefining process were systematically studied. Under the optimum conditions of Cu2+ concentration of 80 g/L, pH of 1.0, H2O2 addition of 0.10 mL/100 mL, and current density of 200 A/m2, the electrolytic product deposited on the cathode surface exhibited the smooth morphology, and the current efficiency during the electrorefining process was over 97%. Furthermore, the impurity elements including S, Ni, Se, As, Sb, Pb, Bi in the electrolytic product were detected by ICP-MS. The results showed that the purity of the copper prepared under the optimum conditions reached the 5N grade, which was consistent with the national standard of 5N high-purity copper.

Lithium iodide, an important raw material for synthesizing lithium battery electrodes, is in increasing demand with the continuous expansion of the new energy market. The current preparation process of lithium iodide requires hazardous chemicals such as biphenylamine and sulfureted hydrogen, which limits its large-scale application. Therefore, finding an environmentally friendly and efficient process for preparing lithium iodide is crucial. In this work, lithium sulfate was used as the lithium source, and electrodialysis metathesis (EDM) was used to cleanly prepare lithium iodide. The effects of the operating voltage, the initial volume ratio of the product liquid to the feed liquid, and the initial feed concentration on the EDM were investigated, and the process was analysed economically. The experimental results showed that increasing the operating voltage can shorten the process time; decreasing the initial volume ratio can significantly improve the concentration of lithium iodide, but the current efficiency will decrease; increasing the initial feed concentration can significantly improve the concentration of lithium iodide and enhance the capacity of the system. Under the conditions of a voltage of 25 V, an initial volume ratio of 1:1, and initial potassium iodide and lithium sulfate concentrations of 0.2 mol/L and 0.1 mol/L, respectively, lithium iodide was prepared with a purity of up to 98.8%, and the cost of the process was approximately 3.6 ￥/kg LiI. The electrodialysis metathesis process for the preparation of lithium iodide is economically feasible and has great potential for industrialization. This indicates that the preparation of lithium iodide by EDM has the advantages of simplicity, low energy consumption, and environmental friendliness and is of reference significance for realizing the green scale preparation of lithium iodide.

Electrolysis of NEU-1 lunar regolith simulants was operated in 43KF-57AlF3 electrolyte at 650℃ in a quartz crucible. The Fe-Ni alloy was used as inert anode which consisted of 57Fe-43Ni and the cathode was made of nickel mesh with the lunar soil simulant in it. Electrode reaction phenomena during electrolysis were visualized using a see-through cell and electrolytes, cathode products and anode gas were characterized by X-ray Diffraction (XRD), Energy Display Spectrometer (EDS) and gas infrared on-line analyzer. The see-through cell was designed with a transparent quartz window in order to observe the phenomena during the electrolysis, It was found that different zones of the electrolyte showed different colors during the electrolysis. The electrolyte divided into three zones as the upper zone, the mid layer and the lower layer. Specifizally, in the upper zone, electrolyte appeared yellowish-brown, and its main phase were KAlF4 and Fe3O4 after condensation. The electrolyte in the mid-layer was transparent, while the center area was black, and the phases after condensation were SiO2, NiO, and Fe-Ni, along with small amount of Fe3O4 and Al-Fe alloy found in the side of mid-layer. The lower layer was bluish-purple metal fog with the predominant phases being Al, Al2O3, and Fe-Ni-Si-Ti alloy. The metal products were present in the form of fine particles located in the area close to the nickel mesh cathode. In the cathode nickel mesh, the main metal product was Fe (35.09wt%), with a small amount of Ti (1.06wt%), Al (9.38wt%), and Si (3.62wt%). It was found that gas bubbles were continuously generated at the bottom of the inert anode during the electrolysis in the see-through cell. Furthermore, an experiment was designed to collect the gas which generated by the electrolysis and detect the anode gas by using an on-line infrared gas analyzer. The result indicated that after 2 hours of electrolysis, the volume fraction of oxygen in the anode gas was stabilized at 95vol%.

The carbon dioxide mineral sequestration is constrained by the leaching rate of Ca2+ and Mg2+ in the raw materials, so the raw materials need to be pretreated. The traditional pretreatment methods (high temperature, acid leaching, etc.) have disadvantages such as high energy consumption and easy pollution, and the use of microbial leaching pretreatment can avoid these disadvantages. A strain well adapted to anorthite was isolated from soil and identified as the fungus Ramichloridium apiculatum. The effects of culture conditions on fungal growth and metabolism were investigated using czapek's medium. Anorthite leaching experiments were carried out under three environments, deionized water, czapek's medium, czapek's medium and fungus, analysis of anorthite changes before and after fungal action by XRD, FTIR, and SEM-EDS. Dialysis was used to further investigate the differences in element release from anorthite under direct/indirect contact modes of the fungus. The results indicate that the optimum growth environment for the fungus is: 4wt% inoculum quantity, glucose as carbon source, NH4Cl as nitrogen source and initial pH of 7.5. The addition of fungus significantly improved the leaching rate of Ca2+ and Mg2+ in anorthite. Compared with deionized water, the leaching rate of Ca2+ and Mg2+ under the action of fungus was 10.04 and 10.11 times that of deionized water. In the direct/indirect leaching experiment, the concentration of Ca2+ and Mg2+ in the direct experiment was always higher than that in the indirect experiment, after 21 days, the leaching rate of Ca2+ and Mg2+ in the direct experiment was 2.94 times and 2.51 times that in the indirect experiment. These results suggest that Ramichloridium apiculatum promotes the leaching of Ca2+ and Mg2+ from anorthite in at least two ways, the first being proton exchange and complexation of fungal metabolites, and the second being physical interaction between the fungus and the mineral.

In the acid pulp leaching solution of non-ferrous metals, there are often fine silicate minerals, which are charged on the surface, can form a stable system in the acid pulp, and it is difficult to settle, which leads to the extraction and electrodeposition process. Moreover, most non-ferrous metal hydroxides are insoluble in water and cannot neutralize the surface electricity of silicate minerals by adjusting pH, which also brings difficulties to the separation of silicate minerals in acidic systems. Polyacrylamide (PAM) is an effective flocculant, which is widely used in water treatment and paper making. Polyethylene oxide (PEO) is widely used in pharmaceutical industry, oil mining, light industry textile and other fields, and has been shown to be effective in flocculating silicate minerals. Polystyrene sulfonate (PSS) has a large amount of negative charge, which can effectively reduce the surface potential of silicate minerals in acidic pulp. Tannic acid (TA) can make the polymer compound associate, thereby increasing the apparent length of molecular chain and improving its flocculation performance. Therefore, in order to solve the problem of silicon removal in acid leaching pulp, the flocculation and sedimentation behavior of fine kaolinite in acid system was investigated by using -2000 mesh (6.5 μm) kaolinite as raw material in this work. The results showed that the flocculation performance of polyacrylamide was stronger than that of polyethylene oxide. Coagulant aid PSS can further improve the flocculation effect. The flocculation effect of PAM and PEO was the best when combined with 100 g/t PSS. The effect of TA on coagulation was not obvious. Using the focused beam reflectance measurement (FBRM), it was found that the size of flocs produced during flocculation was positively correlated with the amount of drug used, but the larger the flocs, the weaker the shear resistance, and the failure process of flocs was irreversible. Zeta potential indicated that PSS can effectively reduce its surface potential, which was the main mechanism of kaolinite flocculation in acidic system.