The high viscosity and low mobility of heavy oil are the technical bottlenecks restricting its recovery. Water-soluble polymer viscosity reducers, with their unique synergistic mechanism of reducing oil viscosity and increasing water viscosity, provide a promising chemical flooding approach to address this problem. This article reviews the mechanism of action of water-soluble polymer-based heavy oil viscosity reducers and explores the progress in molecular design of polymer-based viscosity reducers. It focuses on dissecting the progress of polymer structures from conventional long-chain alkyl and aromatic monomers to stimuli-responsive monomers. The viscosity reduction effect and mechanism of different types of polymer-type viscosity reducers are analyzed. Although existing polymer-based viscosity reducers have demonstrated notable success in lowering heavy oil viscosity, they still face challenges, including unclear transport behavior in porous media, difficulty in demulsification, and concerns regarding economic feasibility.

Aromatic amines are important raw materials in the chemical industry, widely used as intermediates for dyes, fragrances, synthetic pharmaceuticals, rubber, pesticides, and other fine chemicals. Catalytic hydrogenation of aromatic nitro compounds is a common method for the preparation of aromatic amines. Pt-based catalysts are widely used in the hydrogenation process of aromatic nitro compounds due to their high hydrogen dissociation ability. The size of Pt sites can affect their electronic state, coordination environment, metal-support interactions, etc., thereby influencing catalytic activity. This article elaborates on the research progress of Pt-based catalysts in the hydrogenation of aromatic nitro compounds from the perspective of active metal size. It also reviews the influence of Pt size effects on the hydrogenation performance of aromatic nitro compounds and provides prospects for future research on Pt-based catalysts.

All-solid-state lithium batteries, as the next-generation high-energy-density and high-safety-performance energy storage devices, have drawn significant attention to the research of their core solid-state electrolytes. Sulfide solid electrolytes have shown significant industrialization potential due to their ultra-high ionic conductivity, excellent mechanical properties and good interface compatibility. However, sulfide electrolytes still face challenges such as poor air stability, interfacial side reactions, and lithium dendrite growth. This paper systematically reviews the classification and structural characteristics of sulfide-based solid-state electrolytes, deeply analyzes the failure mechanisms of air stability and electrochemical stability, and summarizes the optimization strategies. Finally, it proposes future research directions for key issues such as large-scale preparation, interface optimization, and thin-layer electrolyte development, providing theoretical references for the practical application of sulfide electrolytes.

As global energy consumption and greenhouse gas emissions become increasingly severe, the development of efficient and environmentally friendly thermal insulation materials has become a significant topic in the field of materials science and engineering. Thermal insulation materials are widely used in construction, industry, aerospace and other fields, especially in reducing energy loss and improving energy efficiency. This paper summarizes the recent progress in the preparation and structural research of thermal insulation materials, with a focus on the structural characteristics and thermal insulation performance of organic, inorganic, and their composite aerogels and foams. By comparing and analyzing the thermal conductivity and temperature resistance of different materials, the review systematically outlines the applicable scenarios and current applications of various material systems. Finally, the future development trends of thermal insulation materials are discussed, suggesting that the integration of multi-scale structural design, biomimetic structures, and sustainable materials will be the key path to enhancing thermal insulation performance.

Lithium sulfur(Li-S) batteries, as an energy storage system with high energy density, are a key research object in the field of energy. However, problems such as the shuttle effect of soluble lithium polysulfides and slow redox kinetics during charge and discharge have seriously hampered the commercialization of Li-S batteries. As an indispensable part of the lithium sulfur battery system, the electrolyte is usually composed of lithium salts, organic solvents, and various additives. It plays a role in protecting the lithium negative electrode and conducting lithium ions during the charging and discharging process. Its function has an impact on the reaction process, cycle life, and safety performance of the battery. In recent years, electrolyte additives have attracted much attention from researchers. Adding them to electrolytes can achieve functions such as inhibiting polysulfide (LiPSs) shuttle, enhancing electrode interface stability, and improving ion conductivity. Through a survey of recent relevant literature, this article introduces the molecular design of additives containing nitrogen, fluorine, sulfur, and multi atom synergistic effects, as well as strategies and research progress to enhance the redox kinetics of battery charging and discharging and suppress the shuttle effect of polysulfides. It also analyzes the different mechanisms exhibited by these additives in regulating the interface between polysulfides and electrodes due to differences in electronegativity. At the same time, the important role of lithium salts in electrolytes was briefly explained, including providing lithium ions, participating in electrode reaction processes, maintaining charge balance, and ensuring ion conduction, which expanded the ideas for the molecular design and practical application of lithium sulfur battery electrolyte additives. Finally, we provide some perspectives on the future development of electrolyte additives for lithium-sulfur batteries.

In recent years, sodium-ion batteries (SIB) have received more and more attention due to its cost advantage and potential as an alternative to lithium-ion batteries (LIB). Layered oxide cathodes, as the most promising sodium-ion cathode materials, offer advantages such as high theoretical specific capacity and simple synthesis processes. However, they also suffer from drawbacks such as irreversible phase transitions, structural degradation, and voltage decay, which hinder the commercial development and large-scale application of SIBs. The high-entropy strategy is a comprehensive modification strategy that combines multiple methods, including multi-element doping and bulk structure design, to effectively improve electrode material performance indicators such as energy density, long-term cycle stability, and ion transport kinetics. This review systematically summarizes recent achievement in high-entropy strategies for modification of layered oxide cathode materials for SIB. The intrinsic correlation and modification mechanism between high-entropy effect and improved electrochemical performance are analyzed. Furthermore, future directions for high-entropy strategy are prospected, providing new insight for the design and synthesis of high-performance layered cathode material for future sodium-ion batteries.

The visualization and extraction of latent fingerprints is a key technology in forensic science. Traditional methods have many limitations in terms of visualization efficiency, tertiary feature clarity, applicable object range, and biocompatibility. Aggregation-induced emission (AIE) materials, offering unique optical properties, have provided new perspectives for this field. This review systematically summarizes the luminescence mechanisms of AIEgens and their application progress in the optical visualization of latent fingerprints. It encompasses the development of laser gain materials covering the 350—750 nm wavelength range and the practical implementation of micro-mesh nebulization technology. The review highlights the AIE-based visualization mechanism grounded in the restriction of intramolecular motion. It further critically assesses the current application status from three key aspects: the underlying interaction mechanisms, luminescence modes, and visualization methodologies. Concurrently, limitations in current research are analyzed. Future development trends are also prospected, including the establishment of standardized fingerprint evaluation systems, enhancement of visualization performance, and innovation in technical approaches. This work aims to provide theoretical and technical foundations for the in-situ visualization of latent fingerprints, trace substance detection, and non-destructive extraction of biological evidence.

With the development of industry, the safety problem of liquefied petroleum gas storage is becoming more and more important. The leakage of spherical oil tanks is mainly boiling liquid expanding vapor explosion (BLEVE), which seriously affects the safety of workers. Therefore, it is very crucial to study boiling process on different curved surfaces and quickly reduce the heat transfer coefficient (HTC). The influence of four different curved surfaces on boiling was investigated, and the heat transfer and dynamics of bubbles were discussed. The results show that except for the surface with a curvature of 47^-1 mm^-1, the heat transfer coefficient of the remaining surfaces increases with the increase of curvature. Compared with plane boiling, curved surface boiling realizes directional transport of bubbles and accelerates the renewal rate of surface bubbles, thereby increasing the critical heat flux (CHF) and heat transfer coefficient during boiling. Among them, the CHF at the center angle of 0° of curved surface with a curvature of 47^-1 mm^-1 is the highest, which is 138.8 W/cm², an increase of 26.2% compared with the smooth plane surface, and the corresponding surface temperature is 111.4℃.

In this paper, the crystallization kinetics of ammonium dihydrogen phosphate(MAP) in water-ethylene glycol system was experimentally discussed, the nucleation mechanism of MAP crystallization was studied by using classical nucleation theory, and the nucleation induction time of MAP at different temperatures and different supersaturation ratios was measured. The influence laws of temperature and supersaturation ratio on critical nucleation free energy (ΔG^* ), crystal interfacial free energy (γ), critical nucleation molecule number (i^* ), and critical nucleation radius (r^* ) were studied, and the growth mechanism was revealed according to nucleation parameters. In addition, the effects of stirring rate (N_P) and supersaturation ratio (S) on the crystallization process were explored. Based on the kinetic data, the nucleation and growth kinetics equations of MAP were fitted by least square method, and Canning-Randolph(C-R) and Abegg-Stevens-Larson(ASL) models fitted the linearly correlated growth kinetics model, revealing the synergistic regulation mechanism of solvent composition on crystallization kinetics. The results showed that when the temperature and supersaturation ratio increased, i^*, r^*, ΔG^* and induction time all decreased, while the primary nucleation rate increased. When the supersaturation ratio was 1.08 and above, homogeneous nucleation became the dominant mechanism, and when the supersaturation ratio was 1.06 and below, heterogeneous nucleation was the main nucleation mode. The surface entropy factor values were all less than 1, and the crystal crystallization mechanism was a continuous growth mechanism. When evaluating different linearly correlated growth models, it was found that the ASL model had higher accuracy in describing the crystal growth behavior. It can be seen from the order of the kinetic model that the supersaturation ratio has the greatest impact on the nucleation growth rate. This study elucidates the response law of MAP crystallization in water-ethylene glycol system, providing a theoretical basis for crystal size control based on mixed solvent design and industrial crystallization process optimization.

As server power consumption continues to rise, traditional air cooling technology is becoming increasingly limited due to drawbacks such as high energy consumption, high noise, and insufficient cooling capacity. Single-phase immersion cooling has consequently emerged as a focal point of research, owing to its superior heat-transfer coefficient, markedly lower energy requirement, and negligible noise generation. First, the physical properties of three typical single-phase immersion coolants—mineral oil, silicone oil, and fluorocarbon fluid—were compared and analyzed. The results show that the density of oil-based coolants (mineral oil and silicone oil) is approximately half that of fluorocarbon fluid, and their specific heat capacity and thermal conductivity are nearly twice that of fluorocarbon fluid. However, their viscosity is one to two orders of magnitude higher, resulting in a significant increase in boundary layer thickness. Second, computational fluid dynamics (CFD) simulations were performed on a canonical server configuration to quantify the cooling efficacy of each fluid, and a novel heat dissipation coefficient (HDC) was introduced as a comprehensive performance metric. The HDC analysis reveals that the SS-110 coolant delivers exceptional flow-boiling performance, a benefit primarily attributable to its ultra-low kinematic viscosity. Finally, a dedicated single-phase immersion cooling testbed was designed and commissioned to experimentally validate the thermal performance of mineral oil. At a volumetric flow rate of 1080 L/h, the system successfully removed 1600 W of heat; nevertheless, a non-uniform flow distribution produced a maximum temperature difference of 9.8℃ among heated patches mounted on different epoxy substrates. Additionally, it was observed that thermal grease partially dissolves when exposed to silicone oil, rendering it unsuitable for immersion systems employing silicone oil as the working fluid.

To address the thermal management needs of high-heat-flux electronic devices, this study simulates subcooled flow boiling in Z-shaped and wedge-shaped manifold microchannels (MMCs) using HFE7100 and silicon as the working fluid and solid material. The effects of wedge-shaped MMCs with different wedge angle configurations on flow distribution uniformity, total pressure drop and pressure drop distribution uniformity, chip temperature, and phase volume fraction are discussed. The results show that wedge-shaped MMC can significantly improve flow distribution uniformity. Specifically, the Taper-200-50 reduces the standard deviation of flow distribution by up to approximately 50.9%. In addition, wedge-shaped MMCs can substantially reduce total pressure drop and its fluctuations, effectively improving the uniformity of pressure drop distribution and thereby improving flow stability during the flow boiling process. Specifically, the Taper-200-50 configuration reduces the total pressure drop by 57.3% to 60.0%, the standard deviation of pressure drop fluctuations by 75.3% to 85.1%, and the standard deviation of pressure drop distribution by 81.2% to 84.3%. In terms of heat transfer performance, the average chip temperature in wedge-shaped MMCs is similar to that of the conventional Z-shaped structure. Taper-150-75 and Taper-200-50 exhibit better heat transfer performance, while Taper-250-25 shows the poorest performance, indicating that an excessively large wedge angle may hinder heat transfer. Under the considered operating conditions, the Taper-200-50 achieves a coefficient of performance (COP) of up to 27713 and a performance evaluation criterion (PEC) of up to 1.4, demonstrating excellent potential for thermal management applications.

In direct-contact latent heat storage systems, phase change material (PCM) directly contacts the heat transfer fluid (HTF), enabling higher storage density and rate. However, forming convective channels during melting takes time, and particle shape and size affect channel structure and heat storage performance. This study investigates the solidification of molten polyethylene glycol droplets falling into an oil pool through experiments and simulations. The effects of drop height, oil pool depth, and droplet diameter were analyzed using a high-speed camera and electron microscope. The results show that exceeding a critical falling height causes droplet splashing and collisions. Oil depth and droplet size significantly affect solidification before bottom contact, influencing particle formation. A semi-analytical and empirical model suggests optimal shaping occurs when the solid layer thickness is about 7.67% of the droplet radius. A surface tension correction model was proposed, and when σ = 0.1, simulation results matched experimental data well. Simulations also reveal non-uniform heat transfer: the top cools fastest due to backflow disturbance, while side heat transfer is weaker. Additionally, droplet diameter and fluid temperature exhibit nonlinear effects on the critical oil depth.

Quasi-direct numerical simulations (Q-DNS) were performed using the OpenFOAM platform to investigate planar jets involving isothermal reversible elementary reactions (A+BC). A Lagrange coordinate system was established at the turbulent/non-turbulent interface (T/NTI) to analyze the production, transport, and consumption processes of the chemical species near the interface under four working conditions characterized by different ratios of the reverse-to-forward reaction rate constants (n=0, 0.1, 1, 10). As n increases, chemical reactions near the T/NTI gradually approach equilibrium. At n=10, the contribution of chemical reaction source terms to the unsteady terms of reactants A and B becomes negligible, whereas the positive correlation between the unsteady term of product C and chemical reaction source terms significantly enhances with increasing n. At the irrotational boundary of T/NTI, the diffusive fluxes of components A and C surpass their fluxes by relative motions, whereas the diffusive flux of component B constitutes a smaller proportion of the total flux. The ratio of the diffusion flux to the relative motion flux of each component decreases to varying degrees with increasing n.

Ultrafine powders are widely used due to their unique physical and chemical properties. Consequently, preparation of ultrafine powders with narrow and fine particle sizes is crucial to improve product performance. Without increasing energy consumption or equipment complexity, a double-layer rotor cage is designed and its effects on the flow field distribution and classification performance of the pneumatic classifier are investigated through numerical simulations and powder classification experiments. Simulation results show that the gravity-induced classification effect of the double-layered cage's induction cone causes the airflow in the annular zone to move downward near the outer edge of the cage, reducing radial velocity. This improves powder dispersion in the annular zone and reduces fine powder particle size. Classification experiments confirmed that the dual-layer rotor cage significantly reduces the fine particle size. Moreover, with increasing the length of the diversion cone, the fines exhibit smaller particle sizes, narrower size distribution, and more pronounced secondary classification effect.

In the high-speed operation of mechanical seals, the cross-scale lubricating film flow transitions into a turbulent state. Turbulence effects significantly influence the viscous heat generation and cavitation flow patterns within the liquid film. To reveal this influence mechanism, a thermo-hydrodynamic lubrication numerical model was developed for Rayleigh step-type mechanical seals under both turbulent and laminar flow regimes. A comparative analysis was conducted on the cooling mechanisms and flow behavior of the liquid film under different flow states. The results demonstrate that turbulent flow promotes cavitation formation in the reverse step grooves while weakening vortex motion in the liquid film region. Under laminar flow conditions, where turbulent kinetic energy is absent, a flow stagnation zone forms at the groove root, leading to a temperature trough. Both liquid film and seal face temperatures being notably lower than those under turbulence. As rotational speed increases, the temperature difference between the two regimes becomes more pronounced, reaching up to 25 K. Conversely, turbulent flow creates a larger cavitation area, resulting in better cooling of the liquid film and end faces. This also enhances the cavitation suction effect, reducing leakage by approximately 46%. However, the increased negative hydrodynamic pressure effect reduces the opening force by approximately 6%. These findings indicate that turbulence alters the flow and heat transfer processes of the lubricating medium within the sealing gap, thereby influencing seal face temperature, pressure distribution, cavitation area, and overall sealing performance.

Photocatalytic coenzyme regeneration holds great significance for bio-redox reactions. Porous TiO₂-60 was prepared via sol-gel method. After calcined at 300℃, TiO₂-300 was obtained and then mixed with melamine and calcined again to get a porous TiO₂/g-C₃N₄ heterojunction. The effects of TiO₂ calcination and melamine dosage on the structure and performance of catalyst were studied, and the catalyst dosage was optimized. The results showed that TiO₂ calcination engendered the crystal phase to transform from rutile to anatase. The as-prepared TiO₂/g-C₃N₄ featured high specific surface area, broad absorption edge, narrow band gap, and better charge separation efficiency. With increasing melamine dosage, the specific surface area and pore volume first increase and then decreased, while the light absorption and charge separation properties first increase and then decreased. After optimization, the catalytic activity and yield reached 4.8 mmol/(L·g·min) and 72% respectively, about 7.4 and 5.3 times those of g-C₃N₄. Moreover, the catalyst showed stable performance over five cycles.

Hydrodeoxygenation of phenolics is a key reaction for the conversion of lignin into renewable liquid fuels and aromatic chemicals. In this study, non-precious Ni and VO _x species were loaded onto an inert SiO₂ support to produce a series of NiV/ SiO₂ catalysts. Raman, X-ray diffraction (XRD), H₂-temperature programed reduction (H₂-TPR), and ammonia-temperature programed desorption (NH₃-TPD) were used to characterize the structure and physicochemical properties of these catalysts, and m-cresol was used as a lignin model compound to investigate the catalytic performance of different active sites in hydrodeoxygenation of phenolic compounds. Research has found that Ni metal mainly catalyzes the hydrogenation and C—C bond cleavage of m-cresol, with low selectivity for the target product toluene. There is a strong interaction between VO _x species and Ni metal, and the introduction of an appropriate amount of VO _x can reduce the particle size of Ni metal, enrich the Ni-VO _x interface sites, and significantly improve the selective hydrodeoxygenation of m-cresol to toluene. Based on the investigation of process conditions and the probe reaction of methyl cyclohexanol, it was revealed that the main mechanism of m-cresol hydrodeoxygenation at the Ni-VO _x interface is direct deoxygenation, providing a certain theoretical basis for the development of efficient phenolic deoxygenation catalysts.

Electrocatalytic CO₂ reduction under acidic conditions has attracted significant attention due to its ability to enhance CO₂ utilization and suppress carbonate formation. However, the elevated H⁺ concentration in acidic environments intensifies the competing hydrogen evolution reaction (HER), thereby imposing higher requirements on catalyst stability and selectivity. Herein, we report an Ag-Sn bimetallic catalyst that exhibits outstanding CO₂RR performance in an acidic membrane electrode assembly (MEA) at pH=2. Under a current density of 400 mA/cm², the catalyst achieves a CO selectivity of up to 99.4%, and even at 1 A/cm², the CO Faraday efficiency (FE_CO) remains at 83.5%, with a maximum CO partial current density reaching 834.8 mA/cm². The study found that the introduction of a small amount of Sn can adjust the electronic structure of Ag, thereby accelerating the activation of CO₂ and the transformation to *COOH intermediates. This work provides a new strategy for developing highly efficient and stable CO₂RR catalysts suitable for operation under acidic conditions.

In this study, a hierarchical Bi/PANI/CeO₂ photocatalytic system was successfully constructed via electrospinning combined with a solvothermal method. This system forms a unique S-scheme heterojunction structure through in-situ loading of Bi nanoparticles and CeO₂ nanocubes on PANI nanofibers. Multidimensional characterization results demonstrate that Bi/PANI/CeO₂ exhibits superior CO₂ reduction performance under simulated sunlight: after 3 h of irradiation, CO and CH₄ production rates reached 12.38 μmol·g^-¹·h^-¹ and 4.86 μmol·g^-¹·h^-¹, respectively, significantly surpassing pure PANI nanofibers(CO: 0.48 μmol·g^-¹·h^-¹; CH₄: 0.54 μmol·g^-¹·h^-¹) with 26-fold and 9-fold enhancements. The catalyst retained 90% of its initial activity after fifteen cycles. The material achieves efficient photogenerated carrier separation via S-scheme band alignment, while surface plasmon resonance(SPR) of Bi nanoparticles synergistically activates electrons and induces active sites, providing dual driving forces for CO₂ reduction. This research not only offers a novel strategy for designing high-efficiency photocatalysts but also provides critical theoretical support and technical references for mitigating the greenhouse effect and advancing the “dual carbon” goal through CO₂ resource utilization pathways.

Using the lumped kinetics concept and the chain growth probability model, combined with industrial single-tube experimental data, a composite lumped macrokinetic model for cobalt-based Fischer-Tropsch synthesis, including the syngas consumption rate and lumped component selectivity model, was established. Research results indicate that the CO single-pass conversion calculated by the established macroscopic lumping kinetic model aligns well with experimental values, and the calculated space-time yields of lump components such as methane, C₃ hydrocarbons, C₁₂ hydrocarbons, and C₂₉ hydrocarbons also show good agreement with experimental values under corresponding operating conditions, with maximum relative deviations usually <15%. Furthermore, the hybrid lumping macroscopic kinetic model was applied to modeling and simulation of the entire industrial single-tube unit process, it is demonstrated good performance in calculating the flow rates of wax oil and water, as well as the single-pass and overall CO conversion rates under different operating conditions. The hybrid lumping macroscopic kinetic model and its full-process modeling method for the cobalt-based Fischer-Tropsch synthesis proposed in this paper have the advantages of a moderate number of undetermined parameters and the ability to simultaneously simulate syngas conversion rate and lump component generation rates, showing good application value and academic significance. The presented hybrid lumping model could be extended to other similar reaction systems.

This paper investigates the combustion characteristics of gangue and low-calorific-value coalbed methane. By using the co-combustion mode of gangue and coalbed methane in a circulating fluidized bed (CFB) boiler, and using chemical reaction kinetics, we optimize the pyrolysis reaction of the co-combustion of gangue and coalbed methane in the fluidized bed and derive a chemical reaction kinetics optimization combustion model. The simulation results are compared with experimental data to verify the correctness and reliability of the model. The key parameters of the chemical reaction rate of gangue and coal bed methane in the efficient mixing and burning in circulating fluidized bed boiler are analyzed and discussed; the changes and effects of different chemical reaction kinetics parameters on the chemical reaction rate are simulated. The results show that the optimized model can reduce the error of chemical reaction rate in the combustion region of the furnace, and the optimized simulation is especially critical for the combustion/reaction conditions and emission control; and the optimized group has significant advantages in the main reaction region, which can help to further improve the combustion efficiency, accurately predict the product concentration, and reduce the waste of energy and pollutant generation. Reflecting the fact that the internal conditions of the furnace are more sensitive to the optimization model, it is demonstrated that the applicability and accuracy of the model over the full height range can be further improved through optimization.

Phosphorylated sugars are important biopharmaceuticals and key intermediates in carbohydrate synthesis. In multi-enzyme catalytic preparation systems for sugars, the continuous generation of phosphorylated sugars will result in the accumulation of inorganic phosphate (Pi). Since high concentrations of Pi inhibit enzyme activity, the efficient removal of Pi is critical for the implementation of carbohydrate synthesis technology. However, the separation of phosphorylated sugars/Pi presents a significant difficulty due to their highly similar physicochemical properties. This study investigated the separation efficiency of phosphorylated sugars/Pi in a simulated solution, specifically examining the influence of total concentration, pH and solution composition. Comparative analysis of multiple nanofiltration membranes revealed that NF4 and NF7 exhibit superior separation selectivity under high-salinity conditions. Through rinsing, the removal rate of Pi reached over 80%. This performance robustly confirmed the feasibility of separating phosphorylated sugars from Pi in high-salt solutions. Furthermore, the separation mechanism was analyzed using the Donnan Steric Pore Model with Dielectric Exclusion (DSPM-DE). The analysis revealed that steric hindrance and dielectric exclusion are the key mechanisms underpinning the selective separation of these two solutes under high-salt conditions. This study successfully demonstrated efficient separation of phosphorylated sugars from Pi in high-salt systems by nanofiltration. The approach simultaneously mitigates potential enzyme inhibition in catalytic systems caused by high salinity, enabling long-term stable operation. These findings lay the groundwork for industrial implementation of phosphorylated sugars production technology.

In view of the low surface porosity of 2D MoS₂ nanosheets, the long interlayer stacking mass transfer path and the poor compatibility in polymers, it is difficult to simultaneously improve the selectivity and permeance of their mixed matrix membrane. In this paper, vacancy- and defect-rich MoS₂ (P- MoS₂) was first prepared by ion imprinting technology, and 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole (AHMT) was used to modify P- MoS₂ to prepare hybrid materials (AHMT- MoS₂). Then, AHMT-MoS₂ was added to polyether block polyamide (Pebax) to prepare cast film solution and then coated on polysulfone (mPSf) support to prepare mixed matrix composite membranes (Pebax/AHMT-MoS₂). Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and N₂ adsorption and desorption were used to characterize the chemical, morphological and pore structures of the materials and membranes. The effects of the preparation and testing conditions of the materials on gas separation were investigated. The results showed that Pebax/AHMT-MoS₂ exhibited CO₂ permeance of 818 GPU and CO₂/N₂ selectivity of 56. This was attributed to the construction of the defects on the surface of MoS₂ by ion imprinting strategy, which increased the CO₂ affinity; its surface pores could provide diffusion channels for CO₂. In addition, introduction of amino and hydrazine groups enhances the reaction selectivity of CO₂ and significantly improves the separation. Due to excellent gas separation performance and low cost, it makes as-prepared mixed matrix composite membranes highly potential for the application in CO₂ separation.

Zeolite exhibits great potential for CO adsorption due to its well-organized pore structure and tunable chemical composition. However, numerous influencing factors hinder the design and optimization of adsorbents using traditional experimental methods and theoretical calculations. In this paper, a machine learning strategy of combining the structural characteristics of molecular sieve adsorbents with experimental data was proposed, and a comprehensive data set was constructed to express the structure-activity relationship between molecular sieve structure and CO adsorption performance by integrating literature data and zeolite structure information. Four integrated learning algorithms, gradient enhanced decision tree, random forest, extreme random tree and extreme gradient lifting (XGB), were used to predict CO adsorption, and nested cross validation was used to ensure the prediction accuracy of the evaluation model. The results show that XGB model performs best and shows excellent prediction accuracy. The fragmentation analysis of molecular sieve structure characteristics showed that triangular crystal system, Fd\overline{\mathrm{3}}m space group, near circular pores and interconnected cage structure were conducive to CO adsorption. The alkaline earth metals such as Ca²⁺ and Ba²⁺ in the framework of molecular sieve are conducive to the adsorption of CO. In the metal ion modified molecular sieve, the Cu(Ⅰ) loading has the most significant effect on the CO adsorption performance, and the optimal loading is 13%—15% by weight. When the specific surface area of the adsorbent is 230—400 m²/g and the total pore volume is 0.10—0.15 cm³/g, the adsorbent has the best performance. Its limited pore size is around 4.5 Å and the maximum pore size is in the range of 5.0—5.5 Å, showing relatively good CO adsorption performance. This study provides scientific guidance for the rational design and efficient screening of molecular sieve based co adsorbents.

Catalytic reforming is an important refining process for improving gasoline octane number and producing high-value-added aromatics and hydrogen. Studying the molecular-level reactions and material transformations in the catalytic reforming conversion process is of great significance. This study developed a molecular-level model for catalytic reforming process by molecular reconstruction and comprehensive reaction network construction method, with calculated product mass fractions within ±1% absolute error across the measured temperature and pressure ranges. Based on this, the substance flow analysis method was presented. First, molecular and kinetic information in the reaction network was converted into structure matrix. And then a system of linear equations was established to quantitatively describe transformation of substance through reactions. Patterns of molecule transformation were analyzed in terms of single reaction, key components and grouped types of reaction and molecules. And roles of these parts were examined in the complete catalytic reforming reaction system. A visualization method combining the multi-scale network structure figure with the reaction-substance flow Sankey figure was presented. The transformation relationships and importance comparison of substance flows between key components, as well as between different types of hydrocarbons and reactions, were clearly and intuitively presented and analyzed. Furthermore, this work investigated the variation trends in substance flow within catalytic reforming reaction system under different temperatures and pressures, explaining influence of operating conditions on product composition from the perspective of molecular-level reaction. Substance flow analysis method established a connection between microscopic substance flow and macroscopic reaction mechanisms. This study focused on key information of reaction network, and provided reliable support for investigation of reaction mechanisms and optimization of industrial processes.

Traditional optimization design methods for work and heat exchange networks often first determine the pressure adjustment processes and then conduct heat exchanger network design. Superstructure-based simultaneous optimization methods for work and heat networks can achieve better overall system performance because they can consider the coupling and interactions between work and heat. However, this type of simultaneous optimization model is usually highly non-convex and non-linear, leading to solution difficulties, especially when facing large-scale industrial problems. To address this difficulty, this study proposes a deterministic optimization design method based on a dynamic transportation model. This method leverages the characteristics of the transportation model to efficiently determine the pressure operating path and heat exchange matching scheme under optimal work and heat integration. It ensures linear constraints for the heat integration model and provides guidance for the detailed design of the work and heat exchange network. A case study of power and heat integration involving 14 heat exchange streams was conducted. The proposed method generated a new pressure operating path and corresponding heat exchange matching within 1000 s. The total cost target for this solution was 8761480.49 USD·a^-1, which is highly close to the cost-optimal solution found in the literature, validating the accuracy and effectiveness of the proposed method.

Traditional deep learning-based soft sensor modeling methods lack online updating mechanisms, and are susceptible to information redundancy as the network depth increases, thereby limiting further improvement in model prediction performance. To address these issues, a deep extended variational autoencoder with just-in-time learning (JITL-DE-VAE) is proposed, which consists of an offline training stage and an online updating stage. First, to mitigate the accumulation of reconstruction errors in multi-layer VAEs during the offline phase and impaired prediction performance caused by excessive invalid information in feature extraction, a key variable-guided feature constraint mechanism is introduced and an extended variational autoencoder (E-VAE) is constructed to improve feature extraction accuracy. Second, a deep extended variational autoencoder (DE-VAE) is proposed on the basis of E-VAE, which utilizes both the input and hidden features from the previous layer as inputs to the next layer, significantly enhancing the feature utilization efficiency through cross-layer information integration strategy. Moreover, a just-in-time learning strategy is introduced during the online updating stage to enhance model adaptability to time-varying processes, which calculates the weighted Euclidean distance metric based on the maximum information coefficient to retrieve similar samples from the historical database, and updates the model via a dynamically weighted loss function according to sample similarity. Finally, ablation experiments and comparative experiments were conducted using data from an industrial butane removal tower and sulfur recovery process. The results validate the effectiveness and superiority of the proposed method.

To evaluate the potential of large language models (LLM) in assisting the modeling and prediction of the pulsed column extraction process for spent fuel reprocessing, this study designed five case studies of progressively increasing complexity to assess four mainstream LLM. Model outputs were obtained through structured prompt engineering and quantitatively scored across multiple dimensions via a double-blind evaluation by three domain experts. The results indicate that while all LLM demonstrated excellent performance in instruction adherence, their capabilities declined significantly when addressing diagnostic problems involving complex physicochemical coupling or ambiguous information, lacking the analytical depth to diagnose critical engineering issues precisely. The study concludes that the most suitable role for current LLM is as “intelligent research assistants” to domain experts, jointly forming a highly efficient “human-computer collaborative” research paradigm, rather than acting as independent decision-makers. This paradigm can reduce days of modeling preparation to half an hour. However, all model outputs must undergo rigorous expert review and revision to avoid potential risks such as factual illusions.

To address seal failure caused by face contact during start-stop phases of non-contact mechanical seals under unstable operating conditions, a fluid-solid-thermal-wear coupled model was established based on the 3D fractal characterization of micro-asperities and Archard's adhesive wear theory. The model calculates wear rate and volume of the seal faces, and its accuracy was validated experimentally. A systematic analysis was conducted on how operating pressure, temperature, rotational speed, and spiral groove structural parameters during the start-stop phase influence the contact characteristics, thermal behavior, and frictional wear of the seal faces. The results show that rotational speed and pressure significantly affect wear, while temperature influences it indirectly via thermal deformation of the seal rings. Lowering the operating pressure and temperature during the start-stop phase, starting and stopping at speeds greater than 1500 r·min^-1, and adjusting the speed in increments greater than 1000 r·min^-1 all help reduce friction and wear during the start-stop phase of the friction pair. Considering both start-stop and steady-state performance, the optimal spiral groove parameters are: dam ratio 0.7—0.8, weir ratio 0.4—0.6, spiral angle 16°—18°, 10—12 grooves, and groove depth of 6—8 μm.

This study designed a half-oily liquid hydrogel (HOLH). The silicone oil molecules in HOLH can escape from the emulsion droplets and, after photocuring polymerization and gelation, freely infiltrate into the hydrogel with composed of amphiphilic cross-linkable organic polysiloxanes. This emulsion gel achieves achieved a sebum-like secretion function and a lubricating surface layer through uniformly distributed immiscible and mobile silicone oil molecules. Compared with traditional hydrogels, HOLH exhibits a lower water evaporation rate (the relative weight increases from 45% to around 75% when exposed to air for 7 d) and excellent liquid repellency (sliding angle <10°), effectively blocking complex liquids such as water, oils, and blood. In addition, the polyaniline nanoparticles dispersed in the emulsion gel skeleton give HOLH excellent pressure sensitivity, making it have both antifouling properties and sensing functions. This strategy provides new ideas for regulating the interactions between hydrogel components and silicone oil molecules, and for designing interfacial functions and biomimetic materials.

Mixed anionic/cationic Gemini surfactant systems exhibit significant synergistic effects in improving foam stability, yet their underlying mechanism has not been fully elucidated. Herein, through a combined approach of surface tension measurements and molecular dynamics simulations, the self-assembly behavior of different mixed anionic/cationic Gemini surfactant systems at the air/water interface and their interfacial properties were systematically investigated. The results show that electrostatic interaction and geometric conformational adaption effect between the amine group and anionic polar group, ensures the compact configuration of the polar group region. Meanwhile, conformational optimization and length compatibility between tails promote ordered packing in the hydrophobic tail region. These intermolecular synergistic effects cooperatively cause the mixed surfactants to form a dense and highly ordered adsorption layer at the air/water interface, and significantly enhance the hydration of the polar groups. The resulting enhanced hydration layer and interfacial structure retard the drainage rate of foam films, which in turn endows the foam with superior mechanical strength and resistance to perturbations, thereby significantly improving its macroscopic stability.

Butenyl spinosyns are new green biopesticides produced by Saccharopolyspora pogona. However, due to their complex metabolic network, unclear genetic background and inadequately analyzed regulatory mechanisms, their synthesis efficiency is low and it is difficult to meet actual needs. In this study, comparative transcriptomics analysis of S. pogona ASAGF58 (wild-type) and its high-yielding mutant ASAGF40 led to the identification of LysR family transcriptional regulators associated with secondary metabolism and butenyl-spinosyn biosynthesis. Engineered strains were subsequently constructed to validate their regulatory roles. Among them, RS18275 significantly enhanced butenyl-spinosyn production to 67.1 mg/L, achieving a yield 2.3-fold higher than the parental strain ASAGF58, accompanied by a 30.63% enhancement in biomass and accelerated glucose consumption. Comparative transcriptomic analysis demonstrated that RS18275 promotes precursor supply (e.g., acetyl-CoA) by regulating primary metabolic pathways and increases product biosynthetic flux by upregulating the expression of key genes involved in the butenyl-spinosyn biosynthetic pathway. Based on comparative transcriptomics analysis and verification, the physiological mechanism of RS18275 as a global regulatory factor to achieve efficient synthesis of target compounds by regulating primary metabolism and secondary metabolism was preliminarily analyzed, providing theoretical and engineering strategies for the subsequent efficient synthesis of butenyl spinosad.

Cryogenic liquid hydrogen is a crucial chemical product and has garnered significant attention as a key carrier for future low-carbon energy. Precooling of liquid hydrogen pipelines is a critical step in ensuring efficient liquid hydrogen transportation. This study establishes a comprehensive one-dimensional liquid hydrogen flow model by incorporating a radial high-vacuum multilayer insulation heat transfer scheme, applying appropriate empirical correlations for pressure drop and heat transfer, and designing a staged precooling strategy suitable for large-diameter liquid hydrogen pipelines. In the simulation of the precooling process for a 300 m horizontal pipe with a nominal diameter of 314, the vapor cooling stage exhibits a gradual temperature reduction, with an inner metal pipe wall heat flux below 1 kW/m², taking 37 h to complete. During the liquid cooling phase, the cooling rate initially increased rapidly and then decreased, with the maximum two-phase wall heat flux reaching approximately 9.4 kW/m². The cooling process took approximately 0.45 h, reducing liquid hydrogen mass consumption by 55% compared to conventional constant-flow pre-cooling schemes. The maximum pressure drop inside the pipe reaches 60 kPa, displaying dynamic pulsating fluctuations that stabilize at 40 kPa as the flow becomes steadier. The findings of this study provide theoretical support for the development of efficient precooling technologies for long-distance liquid hydrogen transportation.

In this work, a life cycle assessment (LCA) methodology was applied to access the carbon emission and potential environment impacts of the integrated gasification combined cycle (IGCC) power plant with pre-combustion carbon capture. The assessment was carried out by SimaPro software modeling. The global warming potential (GWP), terrestrial acidification potential (TAP), carcinogenic human toxicity potential (HTPc), non-carcinogenic human toxicity potential (HTPnc), terrestrial ecotoxicity potential (TETP), freshwater ecotoxicity potential (FETP), freshwater eutrophication potential (FEP) and the related contributors were investigated and compared for the IGCC power plants with/without carbon capture and storage (CCS). The results showed that compared to the power plant without carbon capture, flue gas carbon emissions decreased by 88% after carbon capture, while the GWP caused by coal and chemical supply and auxiliary power consumption increased by 18% and 20%, respectively. The GWP of the CCS process was 39.02 kg CO₂-eq, and the total life-cycle GWP of the power plant was 257 kg CO₂-eq, with a reduction of 72%. Besides the sharp drop in GWP, the potential environmental impact of the plant, including TAP, HTPc, HTPnc, TETP, FETP and FEP, increased to 119%—170% compared to the benchmark plant without CCS. The increase in coal and chemical supply was the primary contributor to the rise in HTPc. The CCS unit was the primary contributor to the increase of potential environmental impact except HTPc, and the CCS unit accounted for 15%—34% of the potential environmental impact of the plant.

Pumped thermal energy storage (PTES) is a large-scale, long-duration physical energy storage technology for achieving stable operation of high-proportional renewable energy power systems, while advancing the large-scale application of efficient energy storage and enhancing the deep peak regulation capability of thermal power plants are vital pathways for both maximizing renewable energy integration and facilitating the low-carbon transition of coal-fired power. To this end, a novel multi-pressure supercritical CO₂ PTES system integrated with waste heat recovery is developed. This system achieves efficient recovery and utilization of low-grade flue gas waste heat from thermal power plants. Furthermore, by incorporating a multi-stage thermal storage topology and distributed regenerative devices, it significantly mitigates irreversible losses caused by temperature glide during heat exchange processes within the PTES system. Consequently, the proposed system enhances the flexible peak shaving capability of thermal power units and ensures the secure grid integration of renewable energy sources. Based on the establishment of thermodynamic and economic models, sensitivity analysis was employed to study the influence of key operating parameters on the system's thermodynamic and economic performance. Furthermore, a genetic algorithm was applied to conduct thermo-economic multi-objective optimization. The results show that the performance indicators of the system under the design condition are exergy efficiency of 53.83% and levelized cost of energy(LCOE) of 2063.26 CNY·MWh⁻¹. Among the key parameters, the isentropic efficiency of the discharge expander has the most significant impact on the thermodynamic performance, while the isentropic efficiency of the charging turbine has the most significant impact on economic performance. According to the TOPSIS method, the optimal exergy efficiency obtained in the Pareto optimal frontier solution set is 58.20% and the levelized cost of electricity is 1142.24 CNY·MWh⁻¹, which are 8.12% higher and 44.64% lower than the design condition, respectively.

Oil and gas field produced water, as a by-product of oil, natural gas, and shale gas extraction, urgently needs to be recycled. The lithium it contains has high development potential, but its complex composition, low lithium content, and high development difficulty are significant. Based on this, the purification and concentration process of electrochemical adsorption-selective electrodialysis was proposed to ultimately realize the acquisition of lithium carbonate products from oil and gas field produced water. The effects of characteristic impurity ions (Ca²⁺, Sr²⁺, Ba²⁺) on the performance of electrochemical adsorption for lithium extraction from oil and gas field produced water were investigated, and the operating conditions were optimized. Under the simulated oil and gas field produced water system, the purity of lithium increased from 0.066% to 44.991%, and the lithium content increased from 50 mg·L^-1 to 124.35 mg·L^-1. Coupled with selective electrodialysis, the Li⁺ concentration in the concentrate was enriched to 5.68 g·L^-1, and after impurity removal-precipitation-washing and drying, lithium carbonate (Li₂CO₃) products with a purity of 99.06% can be obtained. The total cost calculated from both energy consumption and raw material consumption for the coupling process was about 3200—3350 CNY·t^-1 Li₂CO₃. The results of the study provide theoretical guidance and technical references for the extraction/recovery of lithium with low content in oil and gas field produced water.

In order to improve the thermal conductivity of phase change materials, activated carbonized peach gum was prepared by a one-step chemical activation method using peach gum as the carbon source and potassium hydroxide as the activator. KOH-activated peach gum carbon (CPGK) and unactivated peach gum carbon (CPG) were added to a palmitic acid (PA)-stearic acid (SA) binary mixture, respectively. The mechanism of the activation treatment on improving the thermal properties of the binary mixture was investigated. The results show that there is only a physical bond between the additive and the PCMs. When the mass fraction of additives is 5%, the thermal conductivity of CPGK on the composite phase change material is more obvious, and the thermal conductivity of PA-SA/CPGK is 0.3528 W·m^-1·K^-1 was 0.92% and 22.46% higher than that of PA-SA/CPG and PA-SA, respectively, because the pore structure of CPGK could provide more heat conduction paths. Compared with the PA-SA mixture, the melting time of PA-SA/CPGK was shortened by 53.64% and the solidification time was shortened by 11.39%. PA-SA/CPGK has a better thermal and shape stability, the mass loss of PA-SA/CPGK was reduced by 2.37% compared with that of PA-SA/CPG under the same test conditions, and the complete leakage time of PA-SA/CPGK was extended by 5.26% compared with that of PA-SA/CPG. The prepared composite phase change materials have good thermal properties and have broad application prospects in the fields of solar thermal utilization and thermal energy storage.

To construct surface microstructures with high emissivity and improve their radiative cooling performance, this study investigated the optimization of the atmospheric window emissivity of a radiative cooling microstructure with periodic tetrahedral features. Firstly, based on the finite-difference time-domain (FDTD) method, the spectral characteristics under different geometric parameter conditions are calculated. Then, based on a large amount of data, a machine-learning model for emissivity prediction using the neural network method is established. Finally, by combining with the adaptive particle swarm optimization (APSO) algorithm, the emission performance is optimized, the optimal combination of geometric parameters is obtained, and the influence of different structural parameters on the average emissivity in the atmospheric window is analyzed. The results show that the machine-learning model based on the FDTD calculation results and neural network algorithms can achieve high-precision emissivity prediction for such structures. Different geometric parameters have different impacts on the emissivity. Under the optimal combination of structural parameters, the average emissivity of this type of microstructure in the atmospheric window is close to 1, indicating strong radiative cooling ability.

To address the issues of lengthy preparation process and difficult removal of chemical residues in traditional chemical reduction-electrochemical reduction methods for preparing 3.5-valent vanadium electrolyte, this study proposes an innovative process involving NH₃ gas-phase reduction of NH₄VO₃, (NH₄)₂V₆O₁₆ and V₂O₅ precursors to directly obtain 3.5-valent vanadium oxides, followed by dissolution to prepare 3.5-valent vanadium electrolyte. Both thermodynamic calculations and experimental results demonstrate that the NH₃ reduction of NH₄VO₃, (NH₄)₂V₆O₁₆ and V₂O₅ follows a stepwise reduction mechanism: V⁵⁺V₆O₁₃VO₂V₄O₇V₂O₃. Enhanced vanadium reduction was achieved by increasing reaction temperature, NH₃ flow rate, and prolonging reaction duration. Optimal conditions were established as: 50 min reaction time, 100 ml/min NH₃ flow rate, and 480℃ for NH₄VO₃ reduction, 520℃ for (NH₄)₂V₆O₁₆ reduction, and 490℃ for V₂O₅ reduction. These conditions yielded electrolytes with vanadium concentrations exceeding 1.75 mol/L and valence states of 3.5±0.1. Notably, NH₄VO₃ and (NH₄)₂V₆O₁₆ precursors achieved vanadium concentrations above 1.90 mol/L. Analysis of the performance of the electrolyte obtained after the reduction of the three raw materials showed that the conductivity of ammonium metavanadate as the raw material was the best (ionic conductivity 19.17 S/m), which was 49.4% and 74.0% higher than that of vanadium pentoxide (12.83 S/m) and ammonium polyvanadate (11.02 S/m), respectively. This novel process eliminates organic/chemical reductant residues in electrolyte preparation, providing technical support for short process development of vanadium redox flow battery electrolyte production technologies.

The deep application of lithium-ion batteries and the development trend toward high-capacity and high-energy systems have drawn increasing attention to the performance evolution of batteries under non-uniform heat transfer conditions. In this study, a 20 Ah pouch-type lithium iron phosphate battery was investigated by establishing a three-dimensional electrochemical-thermal coupled model of a single cell, considering 48 parallel electrode layers. The model was used to explore the thermal behavior, electrochemical behavior, and electrochemical characteristics of the cell under varying conditions of heat transfer area, convective heat transfer coefficient, and temperature gradient. The study revealed that under different heat transfer areas, at a 4C discharge rate, the temperature gradient varied significantly under different heat dissipation conditions, with a maximum temperature difference reaching 8.54℃ under certain conditions, and under 10C discharge, the temperature difference reached as high as 30℃. However, the temperature differences between the three heat transfer conditions were relatively small and were less affected by the heat transfer area. When varying the convective heat transfer coefficient, single-sided forced convection can effectively controlled overall temperature rise but exacerbated temperature non-uniformity in the thickness direction. At a 10C discharge rate, the cross-sectional temperature difference could reach 5.05℃, which was 1.64 times that under single-sided natural convection. Under different temperature gradients, the solid-phase lithium concentration at the anode during 10C discharge was 6.1 times that at 1C, and the peak anode overpotential increased by 91%. The research work has revealed the evolution law of the internal behavior of batteries under differential heat exchange conditions, providing a reference for the thermal management and safety design of high-rate and large-capacity batteries.

The application of CO₂ two-stage compression heat pump technology with inter-stage injection significantly enhances the low-temperature performance of air-source heat pump systems. During actual operation, CO₂ two-stage compression heat pumps with interstage injection often suffer from excessively high exhaust temperatures and compressor burnout due to imperfect system control strategies. This study aims to optimize the control strategy of CO₂ two-stage compression heat pump systems to increase their operational reliability and practical viability. The research investigates the injection ratio (R_inj) and volume ratio (R_v), focusing on their effects on discharge temperature (T_dis,H), coefficient of performance (COP), and other performance metrics across different operating conditions. A simulation model of a CO₂ transcritical two-stage compression heat pump with inter-stage injection was developed using Dymola software to analyze the system's injection and capacity matching behavior. Subsequently, the effects of R_inj and R_v on COP and heating capacity (Q_H) were assessed using response surface methodology and analysis of variance. The results indicate that as R_inj increases, both COP and Q_H initially rise rapidly and then decline gradually, while T_dis,H initially decrease slowly, followed by a more rapid decline. At an evaporating temperature (Tₑ) of -20℃, within the rapid COP growth region, increasing R_inj from 0 to optimal injection ratio (R_inj,opt) enhances COP by 18.4% and Q_H by 29.1%, with T_dis,H decreasing by 3℃ for every 0.05 increment in R_inj. Beyond R_inj,opt, as R_inj approaches maximum injection ratio (R_inj,max), COP and Q_H decrease by 2.6% and 2.3%, respectively, while T_dis,H decreases by 7℃ per 0.05 increment in R_inj. These injection characteristics are attributed to the dynamic response of flow and heat transfer dynamics, as well as variations in intermediate pressure (Pₘ) with changing injection ratios. Furthermore, sensitivity analysis reveals that R_inj has a greater influence on COP, while R_v has a more significant effect on Q_H.

In this study, the anaerobic/aerobic/anoxic/aerobic simultaneous nitrification, endogenous denitrification, and phosphorus removal (AOAO-SNEDPR) system was constructed to investigate the nitrogen and phosphorus removal performance under varying influent phosphorus concentrations. By combining measurements of sludge denitrifying phosphorus removal activity and microbial community structure analysis, the mechanisms of enhanced nitrogen and phosphorus removal via denitrifying phosphorus removal were elucidated. The experimental results demonstrated that under a 6 h operational cycle with influent COD and \mathrm{N}{\mathrm{H}}_{\mathrm{4}}^{+}-N concentrations of 312.05 mg/L and 52.37 mg/L, respectively, the system maintained stable treatment efficiency as the influent \mathrm{P}{\mathrm{O}}_{\mathrm{4}}^{\mathrm{3}-}-P concentration was incrementally increased from 3 to 14.94 mg/L. The average effluent concentrations of COD, TN, and \mathrm{P}{\mathrm{O}}_{\mathrm{4}}^{\mathrm{3}-}-P were 33.47, 7.14 and 0.31 mg/L, respectively. Nitrogen removal was primarily achieved through exogenous denitrification in the anaerobic phase, endogenous denitrification in the aerobic phase, and denitrifying phosphorus removal in the anoxic phase, while phosphorus removal was accomplished via aerobic phosphorus uptake and denitrifying phosphorus uptake. As the influent \mathrm{P}{\mathrm{O}}_{\mathrm{4}}^{\mathrm{3}-}-P concentration increased, the proportions of TN and \mathrm{P}{\mathrm{O}}_{\mathrm{4}}^{\mathrm{3}-}-P removal in the anoxic phase relative to the total removal across all phases rose to 17.39% and 7.85%, respectively. Under high phosphorus conditions, the average carbon storage rate in the anaerobic phase reached 93.84%, with polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs) contributing approximately 67.14% and 32.86% to the internal carbon storage, respectively. The abundances of the denitrifying phosphate-accumulating organisms (DPAOs) Dechloromonas and Candidatus_Accumulibacter reached 2.69% and 2.49%, respectively, while the abundance of the denitrifying glycogen-accumulating organism (DGAOs) Candidatus_Competibacter reached 3.34%.

Water pollution caused by the diffusion of tetracycline hydrochloride (TC-HCl) has seriously endangered human beings and the environment. CoFe₂O₄/CeO₂ composites with different CeO₂ contents were prepared by the sol-gel-combustion method. And it was used as an activator of peroxymonosulfate (PMS) to promote the degradation rate of tetracycline (TC-HCl). The results show that the degradation rate of 10 mg/L TC-HCl can reach 91.94% within 40 min, and it has a good removal effect on TC-HCl within a wide pH range (3—9). Active species capture experiments, electron paramagnetic resonance spectroscopy, and high-valent metal probe analysis confirmed the presence of free radicals (\mathrm{S}{\mathrm{O}}_{\mathrm{4}}^{-}· and ·OH) and non-radicals (¹O₂ and high-valent metal oxygen species) in the catalytic degradation of TC-HCl. The degradation intermediates were analyzed by liquid chromatography-mass spectrometry. Combined with the XPS before and after the CoFe₂O₄/CeO₂ reaction, the degradation pathway and reaction mechanism of TC-HCl were proposed. Through cyclic experiments, inorganic anion interference experiments and degradation experiments on other pollutants, it is demonstrated that CoFe₂O₄/CeO₂ has good stability and practicability. This work aims to improve the performance of PMS activated spinel-type ferrite materials and provide a reference for solving the treatment of antibiotics in the real environment.

As the core technology for biomass reburning denitrification, improving its efficiency is crucial for achieving rapid NO reduction. Aiming at the lack of theoretical support for the targeted design of existing denitrification biochar, this study constructed models of pristine and oxygen-deficient pretreated biochars (BCraw and BCoxy), respectively. It analyzed the influence mechanism of oxygen-deficient pretreatment on biochar reduction of NO from a microscopic perspective. The research found that the reduction of NO by BCraw is primarily composed of four processes: NO adsorption and dissociation, hydrogen atom migration, cleavage and recombination of aromatic rings, and N₂ desorption. Compared to BCraw, the conjugation effect of phenolic hydroxyl groups in BCoxy optimized the NO reduction pathway, reducing the energy barrier (Gap value) for N₂ desorption from 546.65 kJ/mol to 409.40 kJ/mol. Temperature-programmed reduction (TPR) experiments on biochar showed that the NO reduction capability of BCoxy is 1.04 times that of BCraw, further validating the reliability of the simulation results. These findings elucidate the mechanism by which oxygen-deficient pretreatment influences biochar reduction of NO, providing a theoretical foundation for the design of highly efficient biochar-based denitrification materials.

Silicon, as a new generation anode material for high-energy-density lithium-ion batteries, is a key technological path for its commercial application by combining it with carbon materials to construct core-shell silicon-carbon materials. Achieving precise control over the morphology of silicon grains is one of the challenges in the current industrial-scale mass production of silicon-carbon materials. Silicon was uniformly deposited into a porous carbon matrix via chemical vapor deposition (CVD), followed by modulating the crystallinity of silicon through controlled carbon encapsulation temperatures. Systematic characterization revealed that Raman spectroscopy exhibits superior sensitivity and accuracy over X-ray diffraction in quantifying silicon crystallinity. The carbon encapsulation temperature was found to exert a significant influence on the crystallinity of silicon, with elevated crystallinity levels markedly degrading the overall electrochemical performance. Specifically, elevation of carbon encapsulation temperature from 550℃ to 800℃ induced a 55.7% capacity loss (1599→709 mAh·g^-1) and 10.65% efficiency decay (91.62%→80.97%) in initial cycling, quantitatively demonstrating the crystallinity-dependent degradation mechanism in silicon-carbon anodes. These findings confirm that Raman spectroscopy serves as a precise diagnostic tool for optimizing CVD process parameters, enabling high-precision consistency control in the mass production of high-performance, low-crystallinity silicon-carbon anodes.

High-entropy oxides (HEOs) have attracted much attention in the field of energy storage due to their excellent cycle stability and high theoretical specific capacity, but their low intrinsic conductivity limits their application. In this study, the Cu content in La(Cr_0.2Fe_0.2Mn_0.2Ni_0.2Cu _x □_0.2-x )O_3-δ (x=0, 0.1 and 0.2) was systematically modulated to optimize cation/oxygen vacancies, synergistically improving the microstructure and electronic structure while stabilizing the perovskite framework. This optimization enhanced both electron/ion transport kinetics and electrochemical performance. The results demonstrate that La(Cr_0.2Fe_0.2Mn_0.2Ni_0.2Cu_0.1□_0.1)O_3-δ exhibits outstanding high-rate lithium storage performance: a specific capacity of 1174.3 mAh·g^-1 after 250 cycles at 200 mA·g^-1, representing a 1.3-fold improvement over the x = 0.2 sample. Even at a high current density of 3000 mA·g^-1, it maintains a specific capacity of 200.1 mAh·g^-1 (49.6% capacity retention relative to 100 mA·g^-1), with a fourfold enhancement in rate capability. By strategically regulating cation/oxygen vacancy defects, this study effectively improves the electrochemical performance of perovskite-type HEOs, offering a novel design strategy for developing high-performance HEO anode materials.

Based on density functional theory (DFT), the effects of sulfur (S) functionalization on the structural stability, electronic properties and sodium storage performance of M₂N MXene (M=Sc, Ti, V, Zr, Nb) were systematically investigated. The results demonstrate that sulfur functionalization significantly enhances multilayer adsorption capacity by inducing charge redistribution and strengthening sodium ion adsorption. Specifically, the theoretical capacities of Sc₂NS₂ and Zr₂NS₂ reach 968 mAh/g and 617 mAh/g, respectively, substantially exceeding those of non-functionalized Sc₂N (515 mAh/g) and conventional hard carbon materials (300—400 mAh/g). The migration energy barriers of S-functionalized M₂NS₂ materials (e.g, 0.168 eV for Sc₂NS₂ and 0.165 eV for Zr₂NS₂) are notably lower than those of hard carbon (0.25 eV). Differential charge density and electron localization function (ELF) analyses reveal that sulfur incorporation enhances charge transfer between sodium ions and the material surface, as well as localized electronic interactions, thereby providing additional active sites for multilayer adsorption. This work establishes a theoretical foundation for designing high-capacity, fast-charging sodium-ion battery anodes and highlights the promising application potential of S-functionalized M₂N-type MXenes in energy storage systems.

Zn₃Ga₂Ge₂O₁₀ (ZGGO) is considered a near-infrared (NIR) long-afterglow matrix material with excellent performance and is widely used in new technologies such as night vision, anti-counterfeiting, optical recording, and bioimaging. ZGGO: Cr³⁺, Pr³⁺ nanometer phosphor materials were prepared by citric acid sol-gel method. XRD results show that the crystal structure does not change with the inclusion of impurities, and the sample purity is high. The SEM results show that the particle size of the sample is about 500 nm. PL results show that the sample can be efficiently excited by X-ray and 410 nm blue light, and the characteristic emission wavelength is located at 700 nm and 715 nm, corresponding to transitions from the ²E and ⁴T₂(4F) energy levels to the ⁴A₂. TL3D results show that the sample has high thermoluminescence sensitivity under X-ray irradiation, and its main luminescent peak temperature is 389 K. TL results show that the thermoluminescence intensity of ZGGO: Cr³⁺, Pr³⁺ was significantly higher than that of ZGGO: Cr³⁺. DFT results show that ZGGO: Cr³⁺, Pr³⁺ has narrower band gaps and significantly denser bands than ZGGO: Cr³⁺, indicating that double-doped samples are more conducive to electron transfer. The XEL results show that the radiation luminescence increases with the increase of X-ray dose rate, and the relationship is linear. Therefore, ZGGO: Cr³⁺, Pr³⁺ long-afterglow nano-phosphors have the potential of real-time dose rate measurement, and have important reference significance in dosimetry research and application.

Hierarchical porous biomass carbon materials (ACPSCs) were prepared using Catalpa chinensis pods as the carbon source and KOH as the activator. The pore structure and properties of the porous carbons were tunable by varying the KOH ratio. Structural characterization and performance testing results indicated that the ACPSC-1∶1 sample, obtained at a mass ratio of catalpa pod shells to KOH of 1∶1, exhibited the highest specific surface area (1140.8 m²·g⁻¹) and electrochemical performance (a specific capacitance of 271 F·g⁻¹ at a current density of 1 A·g⁻¹). Under a high mass loading of 13 mg·cm⁻², ACPSC-1∶1 had gravimetric and areal specific capacitances of 125 F·g⁻¹ and 1392.3 mF·cm⁻², respectively. The assembled symmetric supercapacitor exhibited an energy density of 7.84 Wh·kg⁻¹ at a power density of 664 W·kg⁻¹; even at an ultrahigh power density of 12.9 kW·kg⁻¹, the energy density still reached 6.07 Wh·kg⁻¹. These results fully demonstrate its great potential for high-power and high-mass-loading supercapacitor applications.

As a clean and efficient halon-alternative fire extinguishing agent, perfluorohexanone has garnered significant attention in fire prevention. To quantitatively evaluate its physicochemical fire suppression mechanisms for optimized system design, this study assessed the physical and chemical extinguishing effects by comparing perfectly stirred reactor (PSR) model results with enhanced cup-burner experimental data. PSR simulations revealed that chemical inhibition dominates when heat absorption in the combustion core zone is below 20% of its latent heat absorption capacity; physical and chemical effects become comparable between 20% and 30%; and physical effects prevail when exceeding 30% of latent heat absorption, reducing the critical extinguishing concentration by over 50%. Cup-burner tests comparing gaseous perfluorohexanone with its liquid mist (about 2 μm droplet size) demonstrated that the mist effectively mitigates the gas-phase combustion-promoting effect, lowering critical extinguishing concentrations for ethanol from 6.06% to 5.06% (16.5% reduction) and for n-heptane from 4.51% to 3.79% (16.0% reduction). Compared with the PSR simulation results, it is estimated that under experimental conditions, the heat absorption of perfluorohexanone in the core combustion zone utilized only 5% of its latent heat. Changing the perfluorohexanone droplet size can enhance its physical effect.