Hydrogen is one of the most promising energy carriers for future energy. Biomass gasification for hydrogen production can realize the resource utilization of waste biomass and reduce environmental pollution, and is considered to be a technology with development potential and prospects. To solve the problems of low hydrogen yield, large tar yield, and unstable reaction in conventional biomass gasification hydrogen production technology, high-energy electrons and active substances (·OH,·O,·CH, etc) generated by low-temperature plasma high-voltage discharge can enhance the efficient conversion of biomass tar by-products. The co-catalyst regeneration can further delay the rapid deactivation of the catalyst, and at the same time greatly improve the hydrogen yield. From the perspective of overcoming the bottleneck of traditional biomass gasification hydrogen production technology, this article summarizes the types and applications of low-temperature plasma reactors, the optimization of reaction conditions, the synergistic effect of catalysts and the reaction pathway. The advantage of low-temperature plasma biomass gasification hydrogen production technology lies in the realization of biomass conversion at lower temperatures (<550℃) to improve the conversion rate and selectivity of reactants and gases; further research and improvement are needed in terms of improving the gasification efficiency and reducing costs to promote the application of low-temperature plasma in biomass gasification hydrogen production industry.

As a highly efficient and energy-saving distillation technology, dividing wall column (DWC) has attracted extensive attention due to its superior performance in chemical separation processes. The research progress on the optimal design and dynamic control of DWC is reviewed. The applications of iterative algorithms, metaheuristic algorithms, and machine learning-based optimization algorithms in optimizing the operating parameters of DWC are analyzed. Furthermore, the development of control structures for DWC is discussed, ranging from three-point control structures, four-point control structures, temperature inferential control structures, to more advanced intelligent control strategies, which have progressively enhanced the dynamic control performance of DWC. In particular, the application of model predictive control (MPC) strategy for controlling DWC is emphasized. Finally, this work highlights the current challenges in research and provides an outlook for future development, aiming to further promote the industrialization of DWC technology.

Electrochromism refers to the technology in which the optical properties of materials (such as transmittance, reflectance, etc.) undergo stable and reversible changes under an applied electric field. Electrochromic smart windows have broad application prospects in the field of building energy conservation, helping China achieve its carbon peak and carbon neutrality goals. Tungstate nanomaterials, as promising inorganic electrochromic materials, offer numerous advantages including abundant sources, simple synthesis processes, diverse types, and tunable structures. Electrochromic devices made from tungstate nanomaterials exhibit a wide spectral modulation range, short response time, high coloration efficiency, and excellent cycling stability, demonstrating immense potential for applications in smart windows and building energy conservation. This review summarizes the structural characteristics and preparation methods of tungstate nanomaterials, elaborates on the research progress in the field of electrochromism both domestically and internationally, and discusses future research and development prospects.

Metal oxides are widely used in the field of gas purification because of their adjustable structure, easy modification and low cost. However, the reaction activity of metal oxides without defective structures to gaseous pollutants is low, and the selectivity still needs to be improved. After introducing crystal defects into metal oxides, their crystal structure and physicochemical properties can be changed, thereby significantly improving their adsorption activity and selectivity to gases. Nevertheless, in gas removal reactions, the promoting mechanism of defects is extremely complex, which makes it difficult to explore the mechanism of defects in the reaction between metal oxides and gases, and also makes it challenging to apply the research results of reaction mechanism to guide the strategic introduction of defects. In this review, the types of defects in metal oxides are summarized, and then the methods of introducing defects are classified and summarized, and the application status of defect metal oxides in gas purification field in recent years is summarized. Finally, the improvement methods and future research directions of metal oxide defect engineering are prospected, in order to provide reference for the subsequent research on the construction of metal oxide defect engineering and the reaction mechanism of defect promotion.

Green carbon science has become the scientific foundation for carbon neutrality. The evolution of C—C and C—H bonds during the hydrocarbon conversion process runs throughout the entire carbon cycle. In the process of C—C bond evolution, the breaking and formation of C—H bonds are inevitable, that is, hydrogen transfer reactions also exist in this process. This paper focuses on hydrogen transfer reactions in the hydrocarbon conversion process, reviewing from three dimensions: mechanisms of hydrogen transfer reactions, regulation of hydrogen transfer reactions, and application of hydrogen transfer reactions in product-oriented hydrocarbon conversion processes. From the perspective of hydrogen transfer reactions, it envisions the reasonable roles of different carbon resources (fossil resources, biomass resources, waste plastic resources, and CO₂ resources) in their efficient conversion as hydrogen acceptors or hydrogen donors. Biomass and water, as potential sustainable hydrogen donors, will play a core role in the construction of future energy systems guided by green carbon science.

Polyurethane (PU) has received a lot of attention due to its high degree of freedom in performance adaptation. However, its diverse properties have led researchers to disagree on the effects of modifying the high and low temperature rheological properties of PU-modified asphalt. Therefore, it is crucial to gain a deeper understanding of the connection between different PU raw material properties, synthesis processes, product structures and the high and low temperature properties of modified asphalt. Based on the chemical modification mechanism of PU, combined with the molecular formation process and the performance evaluation criteria of polymer modified asphalt, this paper systematically explores the properties of different types of soft and hard segments and the structure of PU modifiers prepared by different synthesis methods on modified asphalt. It was shown that the degree of physical and chemical cross-linking of PU molecules within the asphalt is a key factor in the improvement of performance: the nature of the soft and hard segments and the molecular structure mainly affects the microstructural stability of the physical cross-linking, while the content of the isocyanate group directly determines the strength and complexity of the chemical cross-linking. The composite system of PU with polymers and other modifiers in asphalt was further analyzed for the modified mechanism. The addition of modifiers enhances the performance by changing the structural distribution of the internal components of asphalt with PU. However, it is difficult to accurately quantify the degree of cross-linking of PU through the microstructure in the current study, which restricts the precise tuning of the synthesis parameters and processes, which in turn leads to a low predictability of the modification effect. In addition, the structural instability of the composite system and the weak chemical interaction between modifiers often triggered the decrease of storage stability or the deterioration of certain properties. Finally, the development trend and outlook of the research on PU and its composite modified asphalt are proposed.

Lithium-ion batteries have been widely utilized in the new energy market due to their high energy density, long cycling life, and low self-discharge rate. However, the commonly employed polyolefin separators in lithium-ion batteries will shrink and meltdown at high temperatures, which can lead to the occurrence of battery thermal runaway. The development of novel separators with high thermal stability is expected to improve the safety of the battery. The latest research progress of new separators with excellent thermal stability in the field of lithium-ion batteries is systematically reviewed, and their design ideas and structure-activity relationship are discussed. At the same time, the key characteristic parameters of the above separators, such as thickness, ionic conductivity, thermal shrinkage, etc., are summarized and compared. Finally, the future development direction of lithium-ion battery separators is prospected.

The freezing point is an important thermodynamic parameter to represent the solid-liquid phase change process. Experiments showed that electrostatic field can change the solid-liquid equilibrium, thus, it is a method of regulating the solid-liquid phase transition process. In this paper, based on the principle of phase equilibrium, and employing the expression of chemical potential under the action of electrostatic field, a mathematical expression for freezing point with the influence of electrostatic field was derived. The characteristics of the change in freezing point with electrostatic field was investigated through numerical calculations, which showed that the change is proportional to the square of the electric field strength, and the change is also related to the physical properties of the material. According to the difference in dielectric constants between solid phase and liquid phase, the freezing point of some substances increases and others decrease under the action of electrostatic field.

For the isoprene-pentane azeotropic system commonly found in C₅ fractions, this paper proposes a method to evaluate the extractive distillation process with the help of an intelligent optimization algorithm and to design it based on thermodynamic principles. First, a conceptual design is developed based on the residue curve map, followed by closed-loop global optimization of process parameters using an improved genetic algorithm. The optimization is carried out with economic performance, energy efficiency, and extractive section separation efficiency (unique to extractive distillation) as evaluation criteria. Subsequently, the TOPSIS (technique for order preference by similarity to ideal solution) method is employed to select the optimal design scheme from the Pareto front solutions, followed by an analysis of the optimization results from the thermodynamic perspective. The results indicate that the best scheme excels in separation efficiency, economic viability, and energy utilization; reducing the amount of extraction agent, appropriately increasing the number of trays, and optimizing the reflux ratio can effectively enhance separation efficiency while lowering costs. This research provides theoretical foundations and design guidance for the efficient separation of isoprene and pentane in industrial applications.

In this work, the constants of the standard k-ε turbulence model were optimized to reduce numerical diffusion during simulations of gas diffusion in a binary fluidized bed. The research results show that when the Launder turbulence model constants are used, the turbulence intensity of the flow field in the fluidized bed is too large, resulting in a large difference between the simulation results and the experimental data. By adjusting the turbulence model constants, the calculation accuracy can be significantly improved, and the simulation results are more consistent with the experimental data. When the gas velocity is low, turbulence has little effect on the radial diffusion of gas. But when the gas velocity is high, the consistency between the simulation results and the experimental data using the new model constants is significantly improved. As the concentration of heavy particles in the fluidized bed increased, the tracer concentration in the central region initially decreased, and then increased. The introduction of the second component affected the turbulence intensity in the fluidized bed in a more complex manner.

In order to increase the cave area, reduce the stagnant area, and improve the mixing efficiency of pseudoplastic fluid, the fractal theory is applied to the perforation design of the impeller, and a fractal perforated impeller is proposed to enhance the mixing behavior of pseudoplastic fluid. The mixing behavior of pseudoplastic fluid in a fractal perforated impeller stirred tank was investigated by combining experiment and computational fluid dynamics. The results showed that the power consumption and power number of FPT impeller system were lower than those of RT system, but the power consumption and power number increased with the increase of fractal iteration number of perforated holes at the same Reynolds number. Under the same power consumption, FPT impeller can enhance the shear effect on the fluid, increase the shear strain rate, increase the fluidity of the fluid, shorten the dimensionless mixing time, enlarge the cavern area, reduce the stagnation area and enhance the fluid chaotic mixing degree compared with RT impeller. Among them, the dimensionless mixing time of FPT-1 impeller system is shortened by 2.88%—5.65%, the cave area is increased by 6.58%, and the dimensionless mixing time of FPT-2 impeller system is shortened by 8.04%—11.00%, and the cave area is increased by 8.25%. Compared with conventional matrix perforation, fractal-arranged perforation was more advantageous in enhancing fluid mixing effect and improving fluid mixing efficiency.

Numerical simulations were conducted to study the flow condensation process of methanol in horizontal tube. This study examines the impact of vapor quality on methanol condensation heat transfer and pressure drop characteristics under varying mass flux conditions. The investigation also elucidates the flow pattern transitions and liquid film properties during the condensation process. The results show that the heat transfer coefficient reaches a peak value in the range of dryness of 0.87—0.95, and the peak value corresponds to an increase in dryness from 0.87 to 0.95 when the mass flux is 25—75 kg·m^-²·s^-¹. The pressure gradient increases with increasing mass flow rate and vapor quality; however, when the vapor quality exceeds 0.9, the pressure drop gradient decreases with further increases in vapor quality. The primary flow patterns during the condensation process under the simulated conditions are annular/mist flows and stratified/wave flows. During the flow process, the local minimum thickness of the liquid film is observed at θ=90°. An increase in mass flux improves the uniformity of the liquid film distribution.

The synergistic enhancement of thin liquid film boiling heat transfer by electric field and macrostructure is expected to break through the bottleneck of high heat flux heat dissipation of electronic devices. In this study, six distinct macro-structured surfaces are designed and fabricated to systematically investigate the effects of liquid film thickness, structural parameters, and applied voltage on the boiling heat transfer performance with ethanol as the working medium. High-speed imaging and precise heat transfer measurements are employed to evaluate the boiling characteristics, providing insights into the underlying mechanisms driving the observed enhancements. The dynamics of boiling bubbles are found to significantly influence the enhancement of critical heat flux (CHF). When a 4 kV voltage is applied, the bubble departure frequency increases by up to 80%, while the bubble departure diameter decreases by 28% as compared to 0 kV, resulting in a CHF enhancement of approximately 20%. CHF is positively correlated with liquid film thickness and rib height, but exhibits a negative correlation with rib spacing, achieving an increase of up to 139% in CHF under optimal conditions. Further analysis of the CHF enhancement ratio reveals that liquid film thickness exerts the greatest influence on CHF improvement (0.37), followed by rib spacing (0.24) and applied voltage (0.20).

To investigate the effects of different modified cylindrical particle shapes on the wall effect and flow-heat transfer characteristics in packed beds, computational fluid dynamics (CFD) methods were employed to perform numerical simulations on six types of packed beds filled with particles: unmodified cylindrical particles and modified single-hole cylindrical, 3-hole cylindrical, trilobe, 3-hole trilobe, and 9-hole trilobe particles. The radial and axial porosity distributions, flow characteristics, and flow-heat transfer performance were analyzed. The results show that the cylindrical particles can improve the uniformity of fluid flow by either internal openings or external slots. Internal perforation reduces the proportion of flow near the wall, and the number of perforations has no significant effect on the flow near the wall. However, increasing the number of perforations weakens the uniformity of radial flow distribution while enhancing the uniformity of axial flow distribution. External grooving of cylindrical particles into a Trilobe shape improves the heat transfer coefficient but significantly increases the unit pressure drop. In contrast, internal perforation reduces both the heat transfer coefficient and unit pressure drop. Increasing the number of perforations enhances heat transfer performance but also results in a higher pressure drop. Considering both heat transfer performance and flow resistance, the mixed-modified 9-hole trilobe particles exhibit the highest overall heat transfer efficiency and demonstrate the best comprehensive heat transfer performance.

According to the influencing factors of nanoparticle agglomeration and breakage, the calculation method of Re was modified based on the Gidaspow drag model, and a multi-component DQMOM model was proposed. The flow process of nanoparticles in a micro fluidized bed, as well as the changes in the number and diameter of agglomerates, are numerically simulated. The experimental values are in good agreement with the simulation results, verifying the accuracy and reliability of the micro fluidized bed model. The mixed nanoparticles of SiO₂ and ZnO are simulated to explore the effect of adding large particles to improve fluidization. The results show that a higher content of particles with better fluidization performance can enhance the fluidization performance of the mixed particles. When the content of SiO₂ particles is relatively high, smaller-sized particles have a better effect on improving the fluidization performance; when the content of ZnO particles is relatively high, particles with larger density have a better effect. When the content of particles with good fluidization performance is relatively high, adding a small amount of large particles can effectively improve the fluidization performance of the mixed particles.

To enhance the performance of the electrolyzer, a mathematical model was constructed for the proton exchange membrane (PEM) electrolyzer, and the influence regulations of the flow channel height, flow channel width, and water flow on the performance of the electrolyzer were analyzed. Subsequently, based on the standard quadratic polynomial response surface model and the multi-objective genetic algorithm model, the flow channel structure of the PEM electrolyzer was optimized. The research results show that: as the flow channel height or flow channel width increases, the anode flow channel pressure drop decreases, the oxygen volume fraction in the gas-liquid diffusion layer increases, the current density decreases, and the electrolysis energy consumption increases. Increasing the water flow will enhance the pressure drop of the flow channel and mitigate the oxygen accumulation phenomenon. Through multi-objective optimization, in comparison with the initial flow path structure, the optimized flow path structure reduces the pressure drop by 9.84%, the oxygen volume fraction in the gas-liquid diffusion layer by 0.74%, and increases the current density by 6.77 A/m². The electrolytic energy consumption is decreased by 0.03 W·h/m³(standard condition).

Ultra-supercritical boilers have important applications in the chemical industry due to their high efficiency and low emissions characteristics. The transient response characteristics of water-cooled walls are crucial for the safe and efficient operation of supercritical units. By introducing the moving boundary theory, a moving boundary model that can uniformly describe the different working fluid states of supercritical boiler water-cooled wall is proposed. The model does not require separate modeling and solving of various working fluid states, which simplifies the calculation to a certain extent. The proposed grid movement scheme can achieve the tracking of critical pressure points, which reduces errors compared to previous static approximation calculation methods. It can more easily and reasonably solve the switching problem between different working fluid states, and then achieve full condition simulation. A dynamic simulation study was conducted on the transient response characteristics of the water-cooled wall of a 1000 MW supercritical boiler, and the correctness and reliability of the model were verified by comparing it with experimental data. The results indicate that when the disturbance parameter step change by the same amount, the time required for the outlet pressure to reach steady state again after a step change is shorter, while the time required for the inlet enthalpy value to reach steady state again after a step change is longer. Under the same input disturbance conditions, the time required to reach steady state again after disturbance under low load conditions is longer, while the transition time under high load conditions is shorter.

Temperature is one of the important factors that affect battery life, energy conversion efficiency and safety. An efficient battery thermal management system (BTMS) can effectively control the temperature and temperature uniformity of battery charging and discharging. A composite thermal management experimental system was set up by combining the paraffin-expanded graphite composite phase change material (CPCM) with the micro grooves flat heat pipe (FHP) with acetone mixture as working medium. The performance of the thermal management system was studied by setting up three kinds of heat pipe arrangement and five different thermal management modes: natural convection, air cooling, heat pipe, air cooling-heat pipe and phase change material-heat pipe. The results show that when the heat pipe is placed vertically, the heat transfer effect of the working medium is the best under the dual drive of gravity and capillary force, and the temperature of the battery can be reduced better. When the heat pipe is placed horizontally, the working medium is mainly driven by capillary force, and the heat dissipation effect is lower than that of the heat pipe placed vertically. At low discharge rate of 1C, compared with natural convection without thermal management, air cooling at 3 m/s can reduce the maximum temperature of the battery by 19.42%, with the best temperature control effect. PCM could not reach the melting temperature at low calorific value, but could also achieve 12.55% maximum temperature drop after coupling with HP. At the higher discharge rate of 5C, the battery quickly reached the melting temperature of PCM, and the maximum temperature was reduced by 32.10%, while the air-cooling heat dissipation was reduced by 20.39%. The phase transition heat absorption showed significant advantages, and the maximum temperature difference between the batteries was always maintained within 5℃, meeting the requirements of temperature uniformity.

The CO₂ absorption and mass transfer characteristics of the TETA/DEEA (triethylenetetramine/diethylaminoethanol) biphasic absorbent solution in the microchannel were investigated by high-speed video, and the effects of two-phase flow rates, absorbent concentration, and TETA proportion in the total amine on the initial bubble length L_B0, bubble volume reduction ΔV_B, CO₂ absorption percent φ and liquid-side volumetric mass transfer coefficient k_La were systematically examined. The results show that L_B0 is closely related to ΔV_B, and both decrease with the increase of liquid flow rate, total amine concentration and the proportion of TETA in total amines, as well as the decrease of gas flow rate. For CO₂ absorption percent, it decreased with the increase of gas flow rate, and showed a tendency of increasing and then decreasing with the increase of TETA proportion. The experimentally measured k_La values ranged from 0.88 s^-1 to 13.65 s^-1, which were 1—2 orders of magnitude higher than those of the conventional reactor, indicating that the microchannel reactor can significantly enhance the CO₂ capture process by the TETA/DEEA biphasic absorbent. In addition, based on the experimental data, an empirical correlation was proposed to predict the k_La with good prediction performance.

Methyl lactate (MLA) is an important biomass-based platform compound, among which the preparation of MLA by continuous alcoholysis of biomass sugar in a fixed bed is the direction of future industrialization. In our previous studies, two long-life catalysts, TS-1 and In-TS-1, were developed in a batch reactor. This study investigated the continuous alcoholysis of fructose to produce MLA using TS-1 and In-TS-1 catalysts in a fixed bed reactor. The results showed that at 200℃ and 4.8 MPa, TS-1 and In-TS-1 catalysts could operate stably for 144 h without deactivation, achieving MLA yields of 50.4% and 60%, respectively. Characterization findings from XRD, N₂ adsorption-desorption, TG-DSC, Py-FTIR, and ICP-OES indicated that the catalysts maintained their crystal structure, pore structure, and surface acidity after the reaction, with minimal loss of Ti and In metals. This confirmed the stability of TS-1 and In-TS-1 catalysts in the fixed bed continuous reaction process. This study provides fundamental data for the development and industrialization of In-TS-1 catalyzed continuous alcoholysis of fructose to produce MLA.

The use of photocatalytic technology to convert atmospheric CO₂ into high-value-added chemical raw materials is an effective way to alleviate energy and environmental problems. In this work, BiOBr was synthesized via a hydrothermal method, and polyvinylpyrrolidone (PVP) was used to regulate the morphology of BiOBr. The catalyst characterization results show that nano-spherical BiOBr-xP (x represents the amount of PVP introduced) was successfully prepared by introducing PVP. Compared with BiOBr, BiOBr-xP has a larger specific surface area and increases the exposure probability of active sites. Meanwhile, the use of PVP improved the band structure of BiOBr, resulting in a more negative conduction band potential for BiOBr-xP, effectively improving its reduction capacity. Photocatalytic CO₂ reduction tests indicate that BiOBr-2P exhibits optimal photocatalytic activity, achieving a CO generation rate of 2.74 μmol‧g^-1‧h^-1, which is 3.38 times greater than that of BiOBr without PVP (0.81 μmol‧g^-1‧h^-1).

Methyl propionate (MP) is an important basic raw material for organic synthesis and a key intermediate for the synthesis of methyl methacrylate, which has broad applications in various fields such as aerospace, electronics, and new energy vehicles. For the synthesis process of MP, constructing an efficient catalyst system is of great practical significance to meet the rapid growth of MP demand. In this paper, the effects of palladium species, acid promoter, phosphine ligand/Pd(OAc)₂ ratio and p-toluenesulfonic/Pd(OAc)₂ ratio on the catalytic activity of palladium-phosphate homogeneous catalyst system for ethylene hydroesterification were investigated. Through proton nuclear magnetic resonance (NMR) characterization, hydrogen bonding interactions between different anions and methanol are revealed, which activated methanol dehydrogenation, and highlighting a positive correlation between the catalyst's turnover frequency (TOF) and hydrogen bond strength, as well as a negative correlation between activation energy and hydrogen bond strength. At the same time, the optimal reaction conditions such as stirring speed, reaction pressure, catalyst concentration and water content were obtained, and the variation law of catalyst's TOF during continuous reaction process was investigated. The reaction order of methanol, carbon monoxide and ethylene was 1.25, 0.58 and 0, respectively.

Ni-MOF-74 metal-organic framework membranes were successfully prepared by solvothermal synthesis with nickel acetate and 2,5-dihydroxyterephthalic acid (DHTA) as raw materials. The influence of the ratio of nickel ions to DHTA on the crystal phase structure, micromorphology, and separation performance of the membrane material was systematically investigated. The Ni-MOF-74 membrane was fully characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetry (TG) and gas permeation test. The experiments show that the raw material ratio can significantly affect the crystal phase structure and micromorphology of Ni-MOF-74 membrane. As the ratio of nickel ions to the ligand increases, the grain size of the membrane gradually decreases, and the crystallinity of the membrane layer first increases and then decreases. When the molar ratio of metal ions to DHTA is 4∶1, the prepared Ni-MOF-74 membrane has the fewest defects. The results of the gas permeation separation test indicated that the ideal selectivity of H₂/CO₂ of this membrane exceeds 20, surpassing the Knudsen diffusion selectivity, demonstrating good H₂/CO₂ sieving ability.

Due to the Due to the prevalence and danger of oxidation reactions in the chemical industry, a study was conducted on the typical process of cyclohexane oxidation. Aspen Plus was employed for process modeling and kinetic modifications. Before correction, the maximum error among the main products was 28.56%, which was reduced to 3.11% after correction. A multi-objective optimization of the non-catalytic oxidation of cyclohexane was conducted using the genetic algorithm (GA), with Dow's fire and explosion index (F&EI), total annual cost (TAC), and residual oxygen concentration as objective functions. The optimization generated a Pareto front. The results demonstrated that, compared to the original operating conditions, the optimized conditions achieved significant improvements. Under the constraint of maintaining the tail oxygen concentration below the industrial warning threshold of 3%, the equipment cost remained largely unchanged, while operating costs decreased by 34.7%. Additionally, the F&EI index was reduced from 156 to 76.66, lowering the risk level from “moderate risk” to “low risk”.

Ethylene cracking furnace is the core device of ethylene production, and the complex high-temperature cracking reaction of hydrocarbon raw materials occurs in the cracking furnace. It is very important to timely identify the changes in the operating conditions of the cracking furnace for the safe and efficient operation of the equipment. A large number of process data generated during the operation of ethylene cracking furnace are usually multi-variable and high-dimensional, which increases the complexity of data processing and analysis. How to timely detect the change of ethylene cracking furnace operating conditions based on process data has become an urgent problem to be solved. Referring to the excellent performance of contrastive learning algorithm in image classification, this paper proposes a method of cracking furnace operating condition recognition based on contrastive learning. Firstly, the industrial data of ethylene cracking furnace were normalized, and the data were dynamically extracted using time windows of different lengths and converted into grayscale images. According to the information in the image, the image is data-enhanced and then input into the encoder to obtain the global semantics, category, content invariance and other features of the image. These features are applied to calculate the loss function of contrastive learning, and the classification of gray images is realized by minimizing the contrastive loss function. Through the method in this paper, the changes of working conditions can be quickly found according to the process data. Its classification accuracy is significantly improved compared with the self-supervised contrastive learning for universal time series representation learning (TimesURL) method, which can effectively realize the identification of ethylene cracking furnace working conditions.

With the increasing penetration of renewable energy into the grid, the volatility of wind energy and load uncertainty have an increasingly significant impact on the stable operation of the system. Hydrogen storage emerges as a key technology for achieving renewable energy consumption and mitigating fluctuations. This paper proposes a multi-time scale optimal scheduling strategy considering source-load uncertainty and electrolyzer start-stop characteristics, based on wind power hydrogen production to meet downstream hydrogen load demands. The method integrates a multi-state model of the electrolyzer and state-switching constraints. In the day-ahead scheduling stage, a two-stage robust optimization method is adopted, combined with the hot and cold start-stop characteristics of the electrolyzer, to minimize the day-ahead operating cost and cope with the worst-case scenario. In the intra-day adjustment stage, model predictive control (MPC) is used to dynamically adjust each unit in the system based on real-time wind power data and day-ahead optimization results. To verify the effectiveness of the proposed method, a simulation analysis of the electrolytic hydrogen production system is conducted under typical day scenarios obtained through clustering. The results show that, compared with the traditional scheduling scheme, the proposed method can reduce operating costs by about 5%—6% and significantly reduce the number of start-stop cycles of the electrolyzer, thereby improving system stability.

Based on the analogy between mass and heat exchange processes, devices and networks, the mass-energy network analogy optimization can be used to analogize the mass exchange network with small-scale characteristics to the generalized heat exchange network, effectively expanding the solution domain and improving the global optimization quality. However, this method has not yet fully considered the optimal network structures of different individuals of the generalized heat exchange network in different evolutionary periods, and there is still much room for improvement of its global and local optimization performance. To this end, a synchronous analogy and parallel evolution strategy for the generalized heat exchange network and the mass exchange network was established to achieve the real-time regression of the local optimal structure of the generalized heat exchange network to the mass exchange network, and further global and local optimization was implemented in the parallel evolution layer. The analysis of the results of phenol removal and ammonia removal shows that the mass-heat analogy and parallel evolution can give full play to the global search capability of the generalized heat exchanger network in a larger solution domain, and take into account the local optimum accuracy through parallel evolution, providing a more effective method for mass exchange network synthesis.

Due to the characteristics of low ignition energy and wide combustion range, hydrogen is prone to explosion accidents after leakage. To effectively control explosion pressure, venting measures are widely utilized, with vent membrane thickness identified as a critical factor influencing venting performance. Based on the fact that the boundary effect of short pipes is more obvious, a square pipe with a length-to-diameter ratio of 10∶1 was selected to carry out explosion experiments with a diaphragm pressure (P_v) range of 0—48 kPa. The results indicate that an increase in membrane pressure significantly prolongs the flame propagation time, with the flame propagation velocity exhibiting a trend of initial decrease followed by an increase. The maximum overpressure difference between the two ends of the pipe decreases with increasing membrane pressure. Compared to 15 kPa, the pressure differences at 28, 39, and 48 kPa decrease from 30.08 kPa to 28.96, 20.68, and 10.44 kPa, respectively. The pressure-time curve at the venting end displays a double-peak structure, with the second peak pressure (P_ext) being lower than the initial peak pressure. During the early stages, flame and pressure propagation are hindered by the tensile strength of the membrane. After the membrane ruptures, the pressure rises sharply, and the flame exhibits oscillatory propagation within the pipe. Additionally, the pressure amplitude increases significantly with higher membrane pressure.

As a core production unit in the refinery, the catalytic cracking unit converts heavy oil into light oil products, which is an important link in improving the economic benefits of the refinery. Due to the complexity of the production process and the frequent variation in crude oil types in petrochemical industries of China, the prediction accuracy of catalytic cracking unit models based on process simulation often fails to meet the requirements of real-time optimization. To address this, a novel method for operating conditions classification and yield prediction based on unsupervised time series clustering is proposed in this study. By extracting valuable information from process data, the method achieved automatic classification and identification of operating conditions, thereby improving yield prediction performance under conditions of mixed crude oil processing. Through practical data analysis, the proposed method was demonstrated to possess strong predictive capability and generalization ability, enabling high-precision real-time yield prediction for catalytic cracking unit products. This approach can effectively meet the need for dynamic real-time optimization of catalytic cracking units, thereby benefiting the promotion of economic performance in refineries.

Ammonia is one of the most produced inorganic chemicals in the world, and the green ammonia process mainly relies on the use of renewable energy such as solar energy and wind energy to generate water electrolysis to produce green hydrogen, and then uses iron-based catalysts to promote the catalytic reaction of green hydrogen and nitrogen under high temperature and high pressure conditions to synthesize green ammonia. However, the inherent intermittency and seasonality of renewable energy generation directly lead to instability in the supply of hydrogen, a key feedstock for ammonia synthesis, thereby preventing continuous operation of green ammonia production at full load. Therefore, to effectively adapt to the fluctuating energy supply, it is essential to develop a flexible operating strategy that ensures the continuity and stability of production. In this study, a comprehensive mathematical model incorporating key process units, including water electrolysis for hydrogen production, gas compression, ammonia synthesis, and product separation, was developed by integrating mechanistic and surrogate models. This model was used to thoroughly analyze the steady-state operating range and operational flexibility of the green ammonia production system, particular emphasis was placed on examining the impact of varying operational parameters, such as the H₂/N₂ and the inert gas content, under partial load conditions. The results indicate that the flexible production of green ammonia can be realized in the load range of 30% to 100% by adjusting the H₂/N₂ and the inert gas content.

Integrating renewable energy-based hydrogen production into refinery hydrogen systems contributes to green and low-carbon production while reducing operational costs. However, the inherent volatility of renewable energy can affect the stability of hydrogen supply in refineries. To address this issue, a mathematical optimization model is developed to optimize hydrogen production scheduling, ensuring stable hydrogen network operation. Operational units such as hydrogen pipelines, networks, and compressors are modeled with the aim of minimizing operational costs. A mathematical programming model with complementary constraints is constructed, and the optimal hydrogen production schedule is obtained by solving the model. Through analysis, the production plan of the optimized scheduling model can reduce the gray hydrogen output by up to 1373 kg within a production cycle (24 h), corresponding to a reduction of approximately 0.9% in system CO₂ emissions. As for the system operating costs, the model's results show that the maximum reduction can be 3930 USD, which is about 2.0% of the total cost. The results show that even in the case of fluctuations in renewable energy supply, this production plan can ensure the stable operation of the hydrogen system, meet the needs of hydrogen-consuming devices, and keep the pipeline pressure within a safe range. Moreover, this approach effectively controls operational costs and enhances economic efficiency. This approach is of great significance in promoting the transition of the refinery industry toward greener and more efficient production modes.

Multi-effect evaporation is one of the most important desalination methods at present, which contains multiple manipulated variables and the variables are coupled and act together. In the actual production process, operations are frequently optimized to meet specific freshwater production requirements and to achieve the optimal gained output ratio. Simultaneously, the operating conditions and requirements fluctuate periodically throughout production runs, which complicates the continuous optimization of the operational scheme established in accordance with the process over the entire operational cycle. This paper firstly proposes a decision-making strategy for operating variables, which determines the intrinsic relationship and mechanism between each operational variable and secondary steam production through correlation and path analysis, and comprehensively considers the correlation between system effects and device energy recovery, ultimately determining the optimized decision variable. Furthermore, recognizing that steady-state optimization is primarily based on initial conditions, this study addresses the dynamic changes throughout the full operational cycle. The paper introduces a rolling optimization method and proposes a full-cycle operational optimization strategy aimed at maximizing the cumulative gained output ratio over the entire cycle. The results indicate that, compared to the example simulation, the cumulative gained output ratio achieved through the full-cycle operational optimization method is significantly improved by 12.15%.

Aiming at the problem that the non-stationary and multi-working conditions of wastewater treatment process (WWTP) make it difficult to predict water quality efficiently and accurately, this paper proposes an event-triggered fuzzy neural network (ETFNN) model to predict total phosphorus (TP) of WWTP. This method can perceive the non-stationary and multi-working conditions during the evolution process of the TP state in the form of events, thereby achieving efficiently-accurately tracking and prediction. First, the fuzzy neural network (FNN) is trained using the historical data of total phosphorus, and events are defined according to the trend of training error changes that can reflect the switching of multiple operating conditions. Second, an event-triggered learning is designed to adaptively update the parameters of FNN, where the different learning steps will be triggered when some different events occur. This event-triggered learning can perceive and recognize the non-stationary and multiple operational conditions in WWTP. Meanwhile, the convergence analysis of the ETFNN model is given by analyzing the performance potential function of the equivalent Markov decision process. Finally, the ETFNN is considered as the soft-sensing model to predict TP of WWTP, and then a comprehensive analysis is given as well. Experimental results show that the proposed ETFNN-based soft-sensing model not only improves the accuracy of TP prediction, but also identifies and skips invalid data in the form of events, thereby reducing the computational complexity of the prediction model.

Tricalcium neutralization process is a crucial procedure in the citric acid extraction technology and a key stage influencing the quality and yield of the final citric acid products. The process is characterized by time delay, absence of reference trajectory, significant variations in initial materials, irreversible reaction, which is difficult to be optimally controlled by traditional control algorithms. Aiming at the above problems, the actual tricalcium citrate neutralization process is optimized and controlled by the reinforcement learning algorithm deep deterministic policy (DDPG). Considering that model-based reinforcement learning approach enables the agent to conduct cost-free exploration within the learned model, the long short term memory (LSTM) model of the tricalcium neutralization process is established, and its loss function is improved to reduce the gap between the simulation model and the actual environment. Subsequently, the model is used to participate in reinforcement learning training, and finally the trained control strategy is used in the actual tricalcium neutralization process. The experimental results indicate that this method can successfully apply the optimal strategy trained through simulation to the actual tricalcium neutralization process, achieving satisfactory results.

Aiming at the problem of concentration prediction in the penicillin fermentation process, an online soft measurement method based on temporal difference memory network (TDMN) was proposed. In view of the multi-batch and non-stationary characteristics of penicillin fermentation process data, this paper uses a sliding window for preprocessing, uses the TDMN model to capture local features, and realizes real-time update of the model through incremental learning to achieve online soft measurement of penicillin concentration. The experimental results show that the model exhibits significant accuracy in penicillin concentration prediction. Compared with traditional methods such as artificial neural network (ANN), recurrent neural network (RNN) and long short-term memory network (LSTM), it has higher real-time and adaptability, and can effectively track the concentration changes during the fermentation process. Through comparison with other models, it is found that the method based on incremental learning significantly reduces the prediction error and improves the prediction accuracy. This method can not only dynamically update the model, but also effectively track changes in penicillin concentration, providing a new solution for monitoring and controlling the status of the fermentation process, and has important application value and industry significance.

For the prediction of chemical oxygen demand (COD) concentration in the effluent of a sewage treatment plant, a COD prediction model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD) secondary decomposition and bidirectional long short-term memory (BiLSTM) neural network is proposed, and the blood-sucking optimization algorithm (blood-sucking leech optimizer, BSLO) is used to optimize the model. Firstly, design the CEEMDAN algorithm to decompose the original effluent concentration sequence, breaking down the complex time series into several relatively simple sub sequences. Then, VMD is applied to perform quadratic decomposition on subsequences with unstable high-frequency irregular waveforms. Finally, BSLO was applied to optimize BiLSTM, and the performance of 80 models in predicting COD concentration in wastewater treatment plant effluent was compared under undecomposed, first decomposed, second decomposed, and non optimized algorithms. The results show that the introduction of optimization algorithms improves the performance of model prediction, and the BSLO model has faster speed and higher accuracy. Compared with other models, the BSLO+CEEMDAN+VMD+BiLSTM model based on quadratic decomposition can effectively overcome the nonlinearity and complexity of measured data, and exhibits excellent prediction accuracy and generalization ability in the COD prediction of the effluent from the plant.

To address the corrosion problems in the distillation and solid caustic soda production processes of chlor-alkali industry, the corrosion behavior of Q235 carbon steel in hydrochloric acid and sodium hydroxide media, as well as the corrosion protection performance and mechanism of two types of hybrid epoxy resin organic coatings (EP-SiTiMg and EP-SiAlCa), were studied. The results show that the increase of HCl concentration and temperature will increase the hydrogen evolution reaction rate of Q235 and aggravate pitting corrosion. In the basic NaOH environment, when the temperature was less than 90℃, the carbon steel corroded initially and a passive film was formed on the surface, slightly reducing the corrosion rate. When the temperature was further increased, the passive film gradually dissolved, and the corrosion rate increased to 0.522 mg/(cm²·h), reaching the severe corrosion standard. EP-SiTiMg coating had excellent corrosion protectiveness in acidic environments, and could maintain a high impedance value of over 4×10⁹ Ω·cm² at 150℃. It was suitable for long-term use in the distillation workshop. EP-SiAlCa coating had better corrosion protection effect in the alkaline environment at temperatures below 150℃. It reduced the corrosion rate by more than 52% compared to the carbon steel and was suitable for use in the solid caustic soda section at corresponding operating temperatures. When the temperature reached 150℃, the corrosion resistance of both coatings decreased slightly, and the impedance of the coatings remained around 10⁴ Ω·cm², still providing corrosion protection for the carbon steel.

With the development of graphite circumferential seals towards the goal of low wear and long life, the efficient and accurate solution of the performance of dynamic pressure type graphite circumferential seals with different slot structures is particularly important. This study focuses on three groove patterns of circumferential seals: rotor-grooved, stator-grooved, and double-grooved structures. A generalised transient Reynolds equation applicable to different grooving patterns is derived to solve the pressure distribution within the seal film. Dynamic mesh and finite volume methods are used in self-programming to obtain pressure distribution and performance parameters and to compare them with commercial software. Under the same groove depth conditions, the pressure distribution, lifting force, and leakage rate of the three grooving patterns are analyzed and compared over time. Furthermore, the effects of operating parameters such as rotational speed, inlet pressure, and sealing gap on the performance of the three grooving patterns are investigated. The results show that the pressure distribution obtained by self-developed programming closely matches the results of commercial software under the same mesh density. Meanwhile, the computation time is approximately 5% to 30% of that required by commercial software, indicating a significant improvement in efficiency. Compared to single-groove seals, the time-averaged lifting force and time-averaged leakage rate of double-groove seals decrease significantly. Due to the relative positional variation between the grooves on the rotor and stator surfaces, double-groove seals show periodic backflow and high-leakage fluctuations, weakening sealing and film-forming properties. The proposed layered model in this paper offers a new approach to the performance analysis of grooved circumferential seals.

Taking the shrift-fit mechanical seals used in the turbo-pumps of liquid rocket engines as the research objective, taking the interference fit effect of the stationary seal ring as well as the contact between the seal ring and its seats into consideration, the thermoelastic-hydrodynamic lubrication coupling model under cryogenic conditions is established. The interior point optimizer method for nonlinear programming (IPOPT) was employed to address the problem of deformation solution arising from the boundary contact. Subsequently, the influences of the interference fit values of the stationary seal ring, rotational speeds, and sealing pressures on the end-face deformation and thermo-elasto-hydrodynamic lubrication characteristics of the shrift-fit mechanical seals of the turbo pump under the cryogenic environment were investigated. The results show that: under the thermal coupling of the sealing ring and the contact between the sealing components, a non-monotonic film thickness distribution is generated between the end faces of the dynamic and static sealing rings along the radial direction, and the temperature deformation in the cryogenic environment is much greater than the force deformation of the sealing pressure. Moreover, the initial interference fit value of the stationary seal ring exerts an impact on the liquid film thickness distribution of the seal in the working state after grinding and removal after the assembly process. Consequently, both the interference fit value of the stationary seal ring and the thermal deformation under the cryogenic environment are crucial factors to be considered in the structural design of the seal rings. The present thermos-mechanical coupling model, considering the contact effect of the sealing components, can provide theoretical foundation for the structural optimization of the shrift-fit mechanical seal ring.

The dry gas seal of a supercritical CO₂ compressor exhibits unique properties and high parameterization near the critical point. The medium flow demonstrates characteristics of multiphase flow, intense turbulence, and property distortion in the sealing gap. Focusing on a segmented micro-grooved dry gas seal, a thermo-hydrodynamic lubrication phase-change simulation model is constructed for supercritical CO₂ dry gas seals, considering real fluid effects under axial force equilibrium. A method to characterize the thermodynamic processes on the seal face is proposed, and the effects of operating conditions, including rotating speed, inlet pressure, and inlet temperature, on the thermodynamic processes, flow field parameters, and steady-state performance of the seal are analyzed. The results indicate that increasing the inlet temperature significantly suppresses liquid-phase condensation on the seal face, while increasing the rotating speed and inlet pressure can only inhibit liquid-phase condensation in the groove region and increase the area of non-liquid phase area on the end face, but has little effect on the gas-liquid two-phase area of ​​the sealing dam. When the inlet temperature reaches 320 K and 340 K, the pure liquid phase area and gas-liquid two-phase area on the end face disappear successively. Expanding the non-liquid phase area benefits the enhancement of the gas film stiffness of the seal.

Droplet blockage in micropore throats in the late stage of reservoir development has an adverse effect on the actual oil production process. Nanoparticles adsorbed at the emulsion interface reduce interfacial tension and induce interfacial viscoelasticity. Understanding their role in regulating emulsion migration and blockage in micro-pore throats is of significant importance. This study uses microfluidic visualization experiments to investigate the influence of nanoparticles on droplet blockage during migration. By analyzing the relationships between droplet size, critical blockage flow rate, and critical blockage capillary number, the mechanism by which nanoparticle adsorption affects droplet blockage is elucidated. Specifically, the induced interfacial viscoelasticity exacerbates droplet blockage during migration. A mathematical model for the critical conditions of droplet blockage is derived using droplet equilibrium relations. By examining the phase diagram of droplet migration and blockage states, the critical transition conditions for blockage are determined, demonstrating that droplets are more readily captured and blocked in micro-pore throats due to nanoparticle adsorption at the interface.

Surfactants have an important influence on the properties of oil-water interface. The high temperature and high salinity reservoir environment seriously affects the interfacial chemical properties and oil displacement effect of surfactants. In order to study the effect of different surfactant structures on the properties of oil-water interface. The microscopic behavior and mechanism of anionic surfactant sodium dodecyl sulfate (SDS) and group-modified surfactant SDS-B at the oil-water interface were studied by molecular dynamics simulation. The results show that the introduction of alkane in the hydrophobic tail chain of SDS surfactant changes the arrangement of surfactant molecules at the oil-water interface. Compared with the single hydrocarbon chain surfactant, the double hydrocarbon chain structure makes the surfactant still closely perpendicular to the oil-water interface under high temperature and high salt environment, and SDS-B has good molecular interface behavior. At the same time, the increase in the number of alkane groups causes the SDS molecules to show slight bending, causing the surfactant molecules to form multiple aggregates, which is conducive to the formation of multilayer adsorption. The repulsive effect of SDS-B head group on Ca²⁺ was significantly stronger than that of SDS, and the first peak value of radial distribution function decreased by 0.89. The oil-water interface thickness of SDS-B in Ca²⁺ environment was improved compared with that of SDS, and the thickness increased from 1.13 nm to 1.52 nm, which significantly enhanced the interface stability, indicating that the introduction of hydrocarbon chain improved the Ca²⁺ salt resistance of surfactants. The head group of SDS-B is easy to form an intramolecular hydrogen bond structure with the hydrocarbon chain group, and the hydration ability of the head group is improved. The cations in the brine are greatly bound. The diffusion coefficients of Ca²⁺, Mg²⁺ and Na⁺ are reduced by 0.027×10^-4, 0.065×10^-4 and 0.064×10^-4 cm²/s, respectively. The hydrophilic and interfacial behavior of SDS-B head groups is superior to that of SDS in complex salt environments and higher ionic concentrations. This study has important guiding significance for the design of new surfactants in tertiary oil recovery.

The development and utilization of natural gas hydrate resources is the research frontier in the current energy field. At present, related scientific research and new technology development are increasingly relying on large-scale simulation devices. This study, used a large-scale fan-shaped reactor to simulate the depressurization process of methane hydrate exploitation, obtaining the evolution characteristics of the temperature field, pressure field and wave speed, as well as the patterns of hydrate decomposition and fluid production. The results show that during the initial stage of depressurization, the pressure propagation is slow with a pressure difference of 3—4 MPa across a 3 m radial distance. After the whole reservoir pressure stabilizes, the pressure difference narrows to 0.3—0.4 MPa. Here the radial rate of hydrate decomposition varies significantly due to pressure effects. Moreover, there is secondary hydrate generation behavior in the near-well area during the initial stage of depressurization, which has a negative impact on the rate of pressure reduction. Additionally, this study explored the impact of the external environment on the depressurization process through an external constant-pressure water supply system. The results indicate that the continuous seepage of external seawater compensates for the reservoir pressure and has a significant impact on the evolution of temperature/pressure and the production of gas/water.

To reduce the impedance between the Li_1+x Al _x Ti_2-x (PO₄)₃ (LATP) electrolyte membrane and the lithium metal anode, suppress the side reactions between LATP and lithium metal and the growth of lithium dendrites, and improve the performance of the LATP electrolyte membrane, PVDF was used to modify the interface of LATP-based electrolyte membrane, and its electrochemical properties were studied. The LATP ceramic powder was mixed uniformly with polyethylene oxide and LIFSI and cast into a film. The PVDF solution was uniformly coated on the surface of the electrolyte membrane and dried to obtain the modified electrolyte membrane. The performance of the modified electrolyte membrane was studied by electrochemical experiments, charge-discharge experiments, and surface characterization methods. The results show that PVDF affects the crystal structure of LATP and optimizes the lithium ion migration channel. The room-temperature ionic conductivity of the modified electrolyte membrane is improved, the electrochemical window at room temperature increases from 3.74 V to 4.10 V, the lithium ion transference number increases from 0.915 to 0.978, and the cycle time of the lithium metal symmetric battery at a current density of 0.05 mA/cm² increases from 45 h to more than 280 h. The growth of lithium dendrites is effectively suppressed, and the stability of the interface between the electrolyte membrane and lithium metal is improved. The polarization voltages at current densities of 0.025, 0.050, 0.100, and 0.200 mA/cm² are 27, 60, 110 and 220 mV, respectively. A good SEI interface is formed in the LFP|SSCEs-1|Li full battery after more than 25 cycles. The capacity retention rate from the 25th cycle to the 100th cycle is 87%, and the Coulombic efficiency remains above 95%. The PVDF modification layer improves the electrochemical performance of the LATP electrolyte membrane and the stability of the interface with lithium metal, which has positive significance for the application of all-solid-state lithium batteries.

The narrow light absorption range of photocatalysts and the rapid complexation of photogenerated electron-hole pairs are important factors affecting the photocatalytic hydrogen production performance. Doping modification is an effective method to improve it. The C/g-C₃N₄-TiO₂ composites were synthesized by hydrothermal and calcination methods, and the C-doped g-C₃N₄ not only modulated the energy band structure of g-C₃N₄, but also significantly enhanced the visible light absorption ability of TiO₂. Then the photocatalytic performance of C/g-C₃N₄-TiO₂ with different C/g-C₃N₄ contents in decomposing water to hydrogen was further explored. The experimental results showed that the introduction of C/g-C₃N₄ significantly enhanced the absorption ability of TiO₂ in the visible region and broadened its photoresponse range. When the mass ratio of C/g-C₃N₄-TiO₂ was 0.1, the ternary complex showed the highest hydrogen production rate [4.66 mmol/(g·h)], which was 2.31 times that of TiO₂ and 7.17 times that of C/g-C₃N₄. And it still has certain enough stability after seven cycles. This is mainly due to the synergistic effect between C/g-C₃N₄ and TiO₂, which effectively promotes the separation and transport of photogenerated carriers and reduces the complexation of electron-hole pairs, thus improving the photocatalytic efficiency. Therefore, by rationally designing and optimizing the composite structure of photocatalysts, their performance in the process of water splitting for hydrogen production can be significantly enhanced, providing new insights and directions for the development of efficient photocatalysts.

Anion-doping-induced vacancy engineering effectively regulates the electronic structure of transition metal sulfides, thereby improving their adsorption and sulfur utilization efficiency for lithium polysulfide (LiPSs) in lithium-sulfur batteries (LSBs). Herein, diketone coal tar pitch-based porous carbon (DCC) with Co nanoparticles was prepared, and then Co nanoparticles were converted into Se-doping CoS₂ with S vacancy catalyst(CoSe _x S _y @DCC) via one-step high-temperature sulfurization and selenization processes. The obtained CoSe₅S₂@DCC has abundant pores and S vacancies, effectively improving the adsorption capacity to LiPSs and accelerating the reaction kinetics of sulfur conversion. The electrochemical test results indicate that the CoSe₅S₂@DCC/S cathode after S being loaded exhibits good rate performance (with a specific capacity of 1120 mAh·g^-1 at 0.1 C and 488.5 mAh·g^-1 at 5 C), cycling stability (maintaining a specific capacity of 400.3 mAh·g^-1 after 2000 cycles at 5 C, with a coulombic efficiency of 100%) and fast ion diffusion. This work has important reference value for the study of using anion doping to induce vacancy engineering to improve the catalytic activity of catalysts for lithium-sulfur batteries.

Industrial heating has a wide range of applications and requires a large amount of heat, resulting in high carbon emissions when using gas or electric boilers. High temperature heat pumps play an important role in efficient electricity-heat conversion and energy conservation and carbon reduction. The refrigerant has significant impact on the system performance. Low global warming potential (GWP) refrigerant R600, R601, R601a, R1224yd(Z), R1233zd(E), R1234ze(Z) and R1336mzz(Z) were selected and compared with R245fa. A single-stage heat recovery high temperature heat pump model was established. Based on the system minimum superheat theory, it was compared in terms of safety, energy efficiency, environmental impact and economy. The results show that: with the evaporation temperature is 50℃ and the condensation temperature is 80—130℃, R601, R601a and R1233zd(E) have significant advantages over R245fa. With the condensation temperature is 130℃, coefficient of performance (COP) of R601, R601a and R1233zd(E) is 12.39%, 11.04% and 11.16%, respectively, higher than that of R245fa. While exergy efficiency increased by 10.29%, 9.20%, 9.29% respectively. The total equivalent warming impact (TEWI) decreased by 11.39%, 10.32%, 10.41% respectively. The environmental benefits increased by 46.12%, 41.61% and 42.01% respectively.

Waste incineration has the advantages of volume reduction and resource utilization. In recent years, it has gradually replaced landfill and become an important way of solid waste disposal vigorously developed by countries around the world. Waste components are complex and harmful substances are diverse. After incineration, toxic and harmful aromatic hydrocarbon compounds will inevitably be produced, which will harm the atmospheric environment and human health. This paper developed an online monitoring system for aromatic hydrocarbon compounds in waste incineration flue gas based on photoionization time-of-flight mass spectrometry. The online monitoring system was then used to study the online monitoring and dynamic emission characteristics of representative substances such as benzene series, phenolic compounds, polycyclic aromatic hydrocarbons, and chlorinated aromatic hydrocarbons at the inlet and outlet of the selective catalytic reduction (SCR) device in a large-scale waste incineration plant. The study clarified the removal effect of the SCR device on typical aromatic hydrocarbon compounds in waste incineration flue gas. The results showed that the detection limit of the on-line monitoring system can reach ppb level, and the relative deviation (RSD) of the signal intensity of continuous monitoring for 5000 min was only 4.2%. The profile of aromatic hydrocarbon in the flue gases at inlet of SCR equipment was obviously different from that at the outlet, among which xylene and toluene were found to be the major contributors to this distinction. The SCR equipment has a good effect on the removal of aromatic hydrocarbon in flue gas. After flowing through the SCR equipment, the signal intensity of BTEX, phenols, PAHs, chlorobenzene, chlorophenol, chlorotoluene and chlorocresol decreased by 11.3%—91.5%, 47.7%—93.0%, 66.3%—94.9%, 26.4%— 84.5%, 48.5%—88.7%, 53.9%—89.5% and 67.3%—91.0%, respectively.

A combination of experiments and numerical simulations was employed to investigate the effects of low swirl configurations on the flame stability limits and emissions of ammonia-methane-air premixed swirling flames. The results indicated that high pollutant emissions were observed under all conditions in high swirl combustion, particularly unburned ammonia, carbon monoxide, and nitrogen oxides. In contrast, the low swirl configuration effectively reduced these pollutant emissions with only slightly narrowing the stability limits. However, ammonia-methane-air flames under low-swirl configurations produced higher levels of nitrous oxide (\mathrm{N}₂\mathrm{O}), which can be attributed to the lower flame temperature that inhibited the thermal decomposition of \mathrm{N}₂\mathrm{O}. When the non-swirling flows were further increased, the stability limits became very narrow, even though emissions were further reduced. Overall, the low-swirl configuration achieves an optimal balance between pollutant emissions and flame stability, making it suitable for combustion applications requiring reduced pollutant emissions. In general, the low swirl configuration can achieve an optimal balance between pollutant emissions and flame stability, and is suitable for combustion application scenarios that require reducing pollutant emissions.

Silicone rubbers are widely used in many fields due to their excellent performance, but they are prone to degradation in high temperature. In this paper, vinyl-containing polysiloxanes with phenyl (P1) and phenylene (P2) were synthesized via anionic ring-opening and condensation polymerization using tetramethylammonium silanolate (TMAS) as catalyst, deionized water as capping agent, and octamethylcyclotetrasiloxane (D₄), 1,3,5,7-tetramethyl-2,4,6,8-tetravinylcyclotetrasiloxane (D₄Vi), and octaphenylcyclotetrasiloxane (D₄Ph₂) or 1,4-bis(dimethylhydroxysilyl)benzene (BHB) as monomers. The effect of reaction temperature, time and the dosages of catalyst and capping agent were investigated. Their structure was studied by spectroscopic characterization techniques including FTIR, ¹H, ¹³C, and ²⁹Si NMR, and Raman spectroscopy. The effects of vinyl and phenylene on the mechanical properties and thermal stability of cured polysiloxanes were studied. The results showed that the introduction of vinyl and phenylene significantly increased the carbon residue rate of the polymer, which is due to the cross-linking reaction of vinyl and the branching reaction of phenylene at high temperatures. In addition, compared with P1, P2 with a high vinyl content has a higher initial decomposition temperature and better resistance to hot air aging.

This study successfully developed a new double-layer scale-inhibiting hydrophobic coating, the purpose of which is to effectively inhibit the formation of crystals in tunnel drainage pipes. The coating is composed of nano-silica, sulfamic acid, hydrolyzed maleic anhydride and EDTA, and is designed as a hydrophobic inner layer and a scale-resistant outer layer. The function of the hydrophobic inner layer is to prevent the crystallization particles from adhering to the inner wall of the pipe, while the scale inhibition outer layer protects the inner layer and prevents the formation of crystals. Through the static and dynamic simulation experiments in the laboratory, it is found that the anti-crystallization rate of the hydrophobic inner layer is stable over 82%, and the scale inhibition rate of the outer layer is stable over 93%. In the dynamic simulation experiment, the theory predicts that the hydrophobic inner layer can maintain 428.47 d, the scale inhibition outer layer can maintain 188.57 d, and the total of the two can maintain 617.04 d. Through simulation calculations using Ansys fluent software, the results show that the double-layer scale and hydrophobic coating can maintain its performance for up to 634.72 d. The error rate between the verification experiment and the simulation results is 2.87%, it is proved that the simulation model is consistent with the coating performance and can adapt to different flow and velocity conditions, which provides a reference for simulation under various working conditions. This double-layer coating not only realizes the dual functions of hydrophobic and scale inhibition, but also shows excellent durability and slow release performance, which has a remarkable effect on inhibiting the formation of crystals in tunnel drainage pipes, providing an innovative solution for the maintenance of tunnel drainage systems.

Bamboo char, with its distinctive porous structure, offers significant potential for applications in adsorption and energy storage. However, bamboo is a silicon-rich plant. The inorganic components in bamboo carbon, especially Si, can seriously affect its performances. Therefore, it is of significance to develop an effective and cost-efficient approach for impurity removal. In this paper, an innovative method was presented to remove Si and other inorganic components from bamboo char, in which bamboo was impregnated by KOH, followed by co-carbonization of KOH and bamboo, and acid washing. The effects of KOH concentration, impregnation duration, and carbonization temperature on the removal efficiency of silicon and other inorganic components were systematically investigated using EDS and ICP-MS, and the mechanism of alkali impregnation-carbonization-acid washing was explored. In addition, hard carbon samples were prepared from bamboo char and low ash bamboo char, respectively, and their electrochemical properties were characterized. The results show that KOH can be effectively loaded onto bamboo. After the bamboo is immersed in 3 mol·L^-1 KOH solution for 4 h and carbonized at 650℃ and then acid-washed, the ash content of bamboo charcoal can be reduced to 0.55%, the deashing rate reaches 84.76%, the Si content is reduced to 0.3%, and the desiliconization rate reaches 76.19%. During carbonization, KOH reacts with silicon in bamboo to form acid-soluble silicates, which are effectively removed by acid washing. The electrochemical performance of hard carbon prepared from bamboo char with low ash and silicon contents is significantly better than that from un-deashed bamboo char samples. The initial coulombic efficiency reaches 70.67% at a current density of 50 mA·g^-1. After charging and discharging at a current density of 50 mA·g^-1—5 A·g^-1, the reversible specific capacity of the hard carbon prepared from low ash bamboo charcoal is still as high as 365 mAh·g^-1 when the current density is restored to 50 mA·g^-1. Acid washing of char from carbonization of alkali-impregnated bamboo is an effective approach for deep deashing and desilication. Hard carbon derived from bamboo char with low ash and silicon contents has excellent electrochemical performance.

In order to enhance the cold storage performance of R134a hydrate preparation system, the effects of different pore density and different material thickness on the cold storage performance of three kinds of porous foam materials (silicon carbide foam ceramic, aluminum foam and copper foam) were studied, and the optimization of the system was studied by Fluent. The results show that when the charging pressure is 0.25 MPa, the addition of porous foam materials with different pore densities (10, 20, 30 PPI) can promote the cold storage performance of R134a hydrate test rig, but with the increase of pore density, the cold storage performance of the three materials systems decreases. The experimental results show that when the pore density is 10 PPI, the hydrate cold storage characteristics are optimal when the material thickness is 30 mm. And when the material is copper foam, the system's precooling time and cold storage time are the lowest, 35.80 min and 42.61 min respectively, the total cool storage capacity is 937.71 kJ, the cool storage rate is 0.364 kW, and the mass of hydrate formation is 0.992 kg. The numerical simulation results show that when the inlet velocity of diffuser is 8 m/s, the two-phase flow performance in reactor is optimal, which is more conducive to the formation of R134a hydrate around porous media.

As a promising blood perfusion adsorbent, hypercrosslinked polystyrene resin plays an important role in the field of blood purification. However, the hypercrosslinked polystyrene resin currently used in clinical practice has problems such as cumbersome preparation process and high toxicity, which need to be further improved and optimized. In this study, the hypercrosslinked polystyrene resins named HCP-FDA and HCP-DTM were prepared through one-step Friedel-Crafts post-crosslinking reaction of pre-crosslinked polystyrene microspheres named P(St-DVB), using two types of small-molecule external crosslinkers with different molecular weight. The chemical structure and micropore structure of the adsorption resins were characterized by FTIR, XPS, SEM, and BET measurements. The results show that the small-molecule external cross-linking agent can effectively construct chemical cross-linking in the resin, and the prepared HCP-FDA and HCP-DTM have a three-dimensional multilevel (hierarchical) nanonetwork structure. Adsorption experiments show that the prepared HCP-FDA and HCP-DTM have excellent adsorption performance towards medium-to large-molecular-weight uremic toxins, coupled with good blood compatibility. They are expected to serve as novel whole blood perfusion adsorbents, providing a new technical solution for clinical blood perfusion purification therapy in uremia.

The genetic algorithm based on fixed detector network is further developed by using the unsteady adjoint equation, and is used to invert the leakage position and leakage rate after leakage in chemical tank area. First, the source-detector relationship is established by unsteady adjoint equations based on computational fluid dynamics (CFD) simulations. Then, the sources are estimated using genetic algorithm. Unsteady adjoint equations can establish the source-detector relationship accurately while saving massive CFD simulation computation, and the high efficiency of genetic algorithm can realize the prompt estimation of leakage. After considering the measurement errors and thresholds of the detectors, estimation is performed for 10 leakage sources. The results show that the estimation accuracy of each source is high. Additionally, the estimation accuracy changing over leakage time is discussed, indicating that the proposed method can promptly and accurately estimate the leakage sources under complex flow conditions.

This study systematically investigates the ignition characteristics of n-dodecane-methane dual-fuel mixtures in low-to-intermediate temperature conditions using experimental and numerical simulation methods. The ignition delay times of the dual-fuel mixtures, obtained from rapid compression machine experiments, reveal a nonlinear promoting effect of n-dodecane addition on ignition. Furthermore, the type of diluent gas significantly affects the ignition characteristics of the dual-fuel mixture. Combined with the newly developed reaction kinetic mechanism (Mai2024), the experimental data were numerically simulated and analyzed to reveal the mechanism of action of n-dodecane addition and the type of dilution gas on the dual fuel ignition. The experimental data align well with the model predictions, verifying the accuracy of the Mai2024 model in predicting the ignition characteristics of n-dodecane-methane dual-fuel mixtures. The results indicate that adding n-dodecane promotes ignition in a nonlinear manner, consistent with a nonlinear increase in the ·OH radical production rate. The nonlinear promoting effect of n-dodecane addition on ignition is partly due to its low-temperature oxidation process, which enhances the generation and accumulation of the radical pool, and partly from the heat release of its low-temperature oxidation, which raises the system temperature. Additionally, the type of diluent gas has little impact on the first-stage ignition of the fuel, but for total ignition delay time, differences in the thermal properties of the diluent gas play a decisive role in the low-temperature region, while chemical effects primarily influence ignition characteristics at higher temperatures.