Due to the ability of cocatalysts to form heterojunctions on the surface in contact with g?C3N4, promoting the migration of photo generated electrons and enhancing the photocatalytic performance of g?C3N4, the introduction of cocatalysts plays a significant role in improving the photocatalytic activity of g?C3N4. Common co?catalysts can be broadly categorized into three groups: transition metal?based cocatalysts (non?precious?metal co?catalysts), precious metal based co?catalysts, and non?metal cocatalysts. Among them, transition metal?based cocatalysts have attracted widespread attention due to their low cost and strong ability to capture electrons. This article focuses on the composite methods, mechanisms of action, and their effects on the photocatalytic performance of various transition metal based cocatalysts (such as metal oxides, sulfides, phosphides, etc.) with g?C3N4, aiming to provide comprehensive theoretical and practical guidance for the design and development of efficient g?C3N4 based photocatalysts.
With Methyl acetoacetate (MAA) and Neopentyl glycol diacrylate (NPGDA) as raw materials, a linear polymer, Poly (Methyl acetoacetate?Neopentyl glycol diacrylate) (P(MAA?NPGDA)),was prepared via a base?catalyzed Michael addition reaction to extend the molecular chain. The synthesized samples were characterized and analyzed by Fourier transform infrared spectroscopy (FTIR),proton nuclear magnetic resonance spectroscopy （1H NMR）,differential scanning calorimetry（DSC）,high?performance liquid chromatography （HPLC） and gel permeation chromatography（GPC）. The effects of different catalysts on the relative molecular weight growth, heat release rate, and double bond conversion rate of monomers during the reaction were investigated at various temperatures. Furthermore, by using 1,8?Diazabicyclo[5.4.0]undec?7?ene (DBU) as the catalyst, the impacts of varying reaction temperatures, catalyst concentrations, and the ratio of n(MAA) to n(NPGDA) on the molecular weight growth of linear polymers were examined. Under the tested conditions, in a reaction temperature range of 30-40 ℃ with a DBU mass fraction of 2%, and a MAA?to?NPGDA monomer ratio of 1.00∶1.00, the growth rate of P(MAA?NPGDA) molecular weight was relatively stable, and the polymer ultimately reaches a relatively high relative molecular weight.
The regulation of metal cations in zeolites via ion exchange to enhance CO2 adsorption performance holds significant potential for the efficient industrial capture of CO2. To investigate the correlation between metal cation exchange time and CO2 adsorption performance of zeolites, four adsorbent samples (e.g. Ca?LTA?30) were prepared with exchange time as the independent variable. The textural properties, thermal stability, CO2 temperature?programmed desorption (CO2?TPD), and CO2 adsorption performance of these samples were characterized. Furthermore, the IAST (Ideal Adsorbed Solution Theory) selectivity of these samples for CO2/N2 gas mixtures with different volume ratios (20∶80, 50∶50, 80∶20) was compared. The results indicate that the CO2 adsorption performance of LTA can be increased from 5.02 mmol/g to 6.05 mmol/g, while the SCO
ZnCu?BDC, a new MOFs material, was successfully synthesized by solvothermal method, with copper acetate and zinc nitrate as the metal centers and terephthalic acid (BDC) as the organic ligand. The structure, morphology, specific surface area and thermal stability of the materials were systematically characterized by scanning electron microscopy, X?ray polycrystalline powder diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption and thermogravimetric?differential thermal analyzer. The catalytic performance of ZnCu?BDC in naphthalene?containing simulated oil was investigated by using naphthalene as the aromatic hydrocarbon model compound in simulated oil. The results show that the ZnCu?BDC material has the same particle size, smooth surface, good thermal stability, complete decomposition at 450 ℃, a large number of micropores, and a nitrogen adsorption?desorption curve with the characteristics of H3 curve. Under the optimal conditions obtained after the investigation (n(Cu)/n(Zn) is 1.0∶2.0, reaction time 6 h, reaction temperature 70 ℃, pH=5), the removal efficiency of ZnCu?BDC material for aromatic hydrocarbon model compounds in simulated oil can reach 91%.
The heterogeneity of the Tahe fractured?vuggy reservoir is strong, and the fluid flow state is complex. The flow and waterflooding mechanisms of high?asphaltene heavy oil remain poorly understood, posing significant challenges to the effective implementation of water injection strategies. Based on a visualization model of fractured?vuggy reservoirs, experimental investigations were carried out on the flow and displacement behavior of heavy oil with different viscosities. The relationship between the flow resistance coefficient of asphaltene containing heavy oil and the viscosity and flow rate was established, and dynamic quantification of oil saturation in different vuggys was achieved through image recognition. The characteristics of waterflooding of high asphaltene heavy oil in fractured?vuggy reservoirs and the influence mechanisms of heavy oil viscosity, fractures, and water injection rate were clarified. The results indicate that the viscosity of heavy oil increased from 59 mPa
This study investigates the microscopic properties of water?in?oil (W/O) emulsions, focusing on their stability and the formation patterns of liquid holdup. Through emulsification experiments and microscopic observation, the effects of water content, shear rate, and carbon dioxide (CO2) treatment on emulsion droplet size distribution and stability were systematically studied. Based on experimental data, a liquid holdup rate model was developed for the MH oil sample. The results indicate that the shear rate significantly affects the droplet size distribution and emulsion stability. A moderate shear rate (6 000~9 600 s-1) promotes emulsion stability and yields a uniform droplet distribution. When water content is below 30%, increasing the water content reduces the droplet size; however, high water content can show phase separation. CO2 saturation treatment can reduce interfacial tension and improve emulsion stability, but excessive CO2 release may destabilize the oil?water interface and promote droplet coalescence. Rational control of shear rate, water content, and CO2 concentration can effectively optimize pipeline transportation performance, reduce bottom liquid accumulation, and enhance the operational stability of the oilfield gathering and transportation system. This study provides theoretical support for the control of liquid holdup in CO2?driven gathering pipelines and holds significant engineering application value for oilfield production management.
Metal diaphragms serve as key functional materials widely used in aerospace, microelectronics, chemical engineering, and other fields. As the core sensitive element in diaphragm pressure?reducing valves, their mechanical properties directly determine the valve's pressure regulating precision, stability, and service life. This paper systematically investigates the influence of key geometric parameters of the diaphragm and material properties on its mechanical performance under typical operating conditions. A mathematical model was established to analyze force distribution at the equilibrium position, where loads and constraints were applied, followed by the application of loads and constraints were applied, and the relationship between load and deflection was verified using the large deflection theory of corrugated diaphragms. A precise 3D parametric model of the diaphragm was built using SolidWorks software. The study employed the Finite Element Analysis (FEA) method, utilizing ANSYS software to conduct static structural simulation analysis on the diaphragm's geometric structure, parameters (width, height, thickness), and material properties. The results show that: the geometric structure of large arc corrugations is superior to sinusoidal corrugations; increasing the width of the outer corrugations increases the deformation, stress, and strain of the diaphragm, thus enhancing its sensitivity; increasing the corrugation height causes the diaphragm's elastic characteristics to first decrease and then increase; smaller diaphragm thickness results in better elastic characteristics; the elastic modulus of the diaphragm material is the dominant factor affecting its stiffness and deformation response?higher elastic modulus reduces deformation but increases stress, while materials with lower elastic modulus exhibit the opposite effect. Material selection requires balancing sensitivity, strength, and service life requirements. This research reveals the influence of the diaphragm's geometric structure, parameters, and material properties on its mechanical performance, providing an important theoretical basis and design guidance for the structural optimization design and high?performance material selection of diaphragms in diaphragm pressure?reducing valves.
Aiming to achieve noise isolation and vibration damping in engineering applications with simple and aesthetic structures, this paper designs a novel four?oscillator chiral phononic crystal.By incorporating helical scatterer branches as oscillators, the design breaks the inherent symmetry of conventional phononic crystals.Finite element simulation is first used to analyze the bandgap of the unit cell, followed by validation of the infinite periodic bandgap range through finite periodic arrangement. Further investigation into the effects of scatterer material parameters and the number of oscillators on the bandgap characteristics was conducted through parametric analysis. The results indicate that the chiral phononic crystal structure exhibits a total band gap widths of up to 642.12 Hz below 1 000 Hz, demonstrating excellent performance in low frequency noise isolation.
In transformer fault diagnosis accuracy, addressing the limitations of traditional neural networks such as insufficient interpretability and weak temporal feature extraction capabilities, this study proposes a novel diagnostic model,LKAN which integrates Long Short?Term Memory (LSTM) with Kolmogorov?Arnold Network (KAN). The model first employs LSTM to model time?series data from transformer operations, extracting hidden states as temporal features. These features are then fed into the KAN layer, where B?spline functions enable nonlinear mapping and function decomposition, thereby enhancing both the model's expressiveness and interpretability. Experimental results on real?world power transformer datasets demonstrate that the LKAN model achieves a diagnostic accuracy of 98.80%, outperforming LSTM, Convolutional Neural Network（CNN）, Gated Recurrent Unit（GRU）, and single KAN models.Meanwhile, it exhibits strong generalization ability and stability. The LKAN model effectively integrates the temporal modeling capability of LSTM and the interpretability advantage of KAN. It provides a technical path with high accuracy and strong interpretability for intelligent fault diagnosis of transformers, and has good engineering promotion value.
To address the challenges of slow convergence, susceptibility to local optima and path redundancy in the path planning of concrete pouring robots in complex construction environments, an improved ant colony algorithm?based path planning optimization method for concrete robots is proposed. First, a new pheromone update mechanism is formulated and the hindsight experience replay (HER) algorithm is applied to define pseudo?target points, thereby addressing the slow convergence and local optimum entrapment issues of conventional ant colony algorithm (ACO). Second, a new obstacle heuristic factor is designed to improve the obstacle avoidance ability of the traditional ant colony algorithm.Third, to solve the limitation of path redundancy in the traditional ant colony algorithm, a curve smoothing function is introduced to eliminate redundant nodes and improve the path quality. Simulation experiments show that the algorithm proposed in this paper has good effectiveness and stability in terms of the shortest path length, the number of turning points and iteration efficiency.
This paper proposes a distributed coordinated optimization method for multi?microgrid systems based on the Alternating Direction Method of Multipliers (ADMM). The proposed model comprehensively accounts for generation costs, energy storage operation, and inter?microgrid interactions, while employing second?order cone relaxation techniques to address nonlinear power flow constraints. By optimizing the ADMM iteration process and parameter selection, the method significantly improves computational efficiency while protecting data privacy through its distributed architecture. Case studies demonstrate that the method converges within only five iterations, achieves a 76.7% improvement in computational efficiency compared with centralized optimization, and maintains a solution accuracy within a 0.34% deviation from the global optimum. Compared to linear programming methods, the ADMM enhances voltage regulation performance by 40.0% and reduces line losses by 15.5%. The method exhibits excellent scalability with computational complexity increasing linearly with the number of microgrids, is applicable to various network topologies, and requires sharing only boundary interaction information, thus providing effective technical support for multi?microgrid coordination optimization.
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