Asia-Pacific Journal of Chemical Engineering最新文献

Self-excited thermoacoustic instability (SETAI) is a dangerous phenomenon in combustion equipment. While it is widely acknowledged that SETAI behavior is determined by the couple between pressure and heat release oscillation, their phase difference is difficult to predict, which impedes the development of SETAI control technology. With the aim of passive control technology development, this paper conducted experiment on a premixed hedge combustor to explore the mechanism whereby premixed chamber length (L_P) and equivalence ratio (φ) collaboratively influence SETAI behavior. Results showed L_P mainly affects the pressure mode shape within premixed chamber and consequently alters the phase difference between pressure and flowrate oscillation at combustion chamber inlet. Changing φ gives rise to different reaction time-lag (τ), thus altering the phase difference between flowrate and reaction heat release oscillation. By introducing this flowrate oscillation, how L_P and φ collaboratively determine phase difference between pressure oscillation and heat release oscillation was clarified. The mechanisms identified in this study are consistent with the emerging rationalization of the factors contributing to SETAI, and also provides better understanding on Rayleigh criterion and guidance for SETAI control. With further work on heat release and flow rate measurement, as well as the development on τ description, SETAI can be better predicted and controlled.

Due to excellent performance, hydrogen is treated as the most promising energy carrier. However, during the storage of liquid hydrogen, there are still some thorny issues that need to be addressed urgently, such as fluid thermal stratification and sloshing phenomenon. To efficiently grasp fluid sloshing mechanical characteristics, a simple visual sloshing experiment rig was established by using a rectangle transparent water vessel. The variations of the interface shape and the impact force during sloshing were monitored and analyzed. The effects of sloshing frequency, horizontal acceleration, and initial liquid height on fluid sloshing mechanical mechanism were investigated. The results show that when the external sloshing excitation is close to the first order natural frequency, obvious interface fluctuation and large amplitude sloshing force variation are observed. The present work is of significance to strengthen the understanding of fluid sloshing mechanical performance and may lay a solid foundation for fluid sloshing suppression and long-term storage of cryogenic fuels.

Deep eutectic solvents (DESs) are increasingly recognized as sustainable alternatives suitable for a range of industrial applications. A precise comprehension of their properties is important for progress in science and engineering. In this study, we synthesized four novel ternary DESs using mandelic acid and measured their densities and viscosities at temperatures ranging from 298 to 353 K. Subsequently, an artificial neural network model was developed to predict DES density and viscosity based on temperature, critical properties, acentric factor, and molar ratio. The neural network parameters were optimized using experimental data from synthesized DESs and literature sources, both collectively over 500 data points for density and viscosity. Additionally, we investigated the influence of input parameters on model accuracy and assessed their significance. The results show that the average percentage relative error was 0.501 for density and 4.81 for viscosity. This research helps advance science and engineering applications of DESs.

High expansion (Hi-Ex) foam is recommended to suppress the leakage and diffusion of cryogenic liquid due to its light weight and large volume. However, the disadvantages of low stability and high break rate under environmental conditions are all limited the further application in vapor mitigation and fire extinguishing. So that, this paper focus on the effect and mechanism of nanoparticles in stabilizing Hi-Ex foam. Three kinds of nanoparticles with different concentration were selected to evaluate the effect of foam half-life and the mechanism of particles on improving the foam stability. The results indicated that different particle concentrations can improve the foam stability to a specific extent, and the maximum improving of half-life can increase by 95.4% in the presence of the hydrophilic SiO₂ at .5 wt%. Meanwhile, the hydrophilicity, size, and morphology of the particles have a specific impact on the foam stability. The foam expansion rate first increased and then decreased. From the microscopic point of view, the bubble size gradually increases with time by two processes of ripening and coalescence and satisfied in a logarithmic distribution. While, the liquid film thickness remarkably decreases due to foam drainage without particles and the adsorption and accumulation of nanoparticles on foam lamella can provide a spatial barrier for the film thinning and the inter bubble diffusion. Finally, the microscopic interaction mechanism on improving the foam stability has been further explored and revealed in these two aspects.

Sonochemistry is a fascinating field that has drawn considerable interest from researchers across different disciplines. One of the key challenges in this field is the accurate characterization of the sonochemical field, which is crucial for understanding the underlying mechanisms and optimizing the process. To address this challenge, researchers have developed various monitoring methods that allow them to measure key parameters such as the intensity, frequency, and distribution of acoustic waves in the sonoreactor. In this review, we focus on the chemical dosimetry techniques that are commonly used for sonochemical monitoring. These techniques have been extensively studied in the literature and are known for their reliability and accuracy. However, as we will see, the performance of these techniques can vary depending on the chemical nature of the probing species and the experimental conditions, highlighting the need for a careful selection and calibration of the monitoring method. We begin by discussing the principles of chemical dosimetry in sonochemistry and how these methods can be used to measure key sono-acoustic parameters. We then provide a detailed analysis of the various dosimetry techniques, including their advantages, limitations, and applicability under different operating conditions. In summary, our review serves as a valuable resource for researchers seeking to optimize their sonochemical experiments and contribute to the advancement of this fascinating field.

This study focuses on enhancing the properties of kaolin (Kao) clay by incorporating Zinc oxide nanoparticles (ZnO NPs) and further functionalizing with agar biopolymer, resulting in the formation of Agar/Kao@ZnO nanocomposite (NC). The synthesized material underwent comprehensive composition, structure, surface, and optical properties analysis to confirm the formation. The material was evaluated as a photocatalyst for the degradation of 2,4-dinitrophenol (DNP) under visible light irradiation. The optimized conditions for the photocatalytic degradation of DNP were determined as irradiation time 50 minutes, pH 4, catalyst dose 20 mg, and DNP concentration of 25 mg L⁻¹, resulting in degradation efficiency of 99.63%. Trapping experiment validated the significant role of hydroxyl (^•OH) radicals as reactive oxidant species (ROS) in the degradation of DNP in the presence of visible light. Through four consecutive cycles of reusability experiments, it was confirmed that the synthesized material is highly stable and efficient for DNP degradation.

This study aims to enhance the liquid water distribution within electrodes by innovatively designing a microporous layer (MPL) featuring orderly gradient perforations. Utilizing a multi-component multi-phase lattice Boltzmann model (LBM), which has been rigorously validated through contact angle measurements, Laplace pressure tests, grid independence checks, and comparisons with experimental data to ensure high predictive accuracy. The research systematically analyzes the governing liquid water transport in orderly gradient perforation MPLs. Leveraging this reliable modeling platform, the study conducts an exhaustive optimization analysis of gradient direction, gradation counts, and perforation geometry under constant porosity conditions. Findings reveal that negative gradient perforation designs significantly outperform positive gradient and conventional straight perforations, enhancing dry pore retention by at least 10.8%. Within the gradation counts, the ternary gradient structure further boosts channel retention by an additional minimum of 14.9% compared to quinary and continuous gradient structures. Moreover, cylindrical perforations demonstrate a substantial decrease surpassing spherical and square designs by at least 13.8% for liquid water saturation. Critically, the optimized model effectively inhibit the formation of saturation-induced blockages in localized thickness regions. In conclusion, the investigation offers a robust basis for advancing MPL design strategies, targeting improved electrochemical processes and battery performance.

The application of industrial solid waste coal gangue (CG) in gas explosion suppression is explored, which opens up a new way for the resource utilization of CG. Two modified CG anti-explosion agents, first-grade modified CG (RCG) and second-grade modified CG (MCG), were prepared by roasting activation and acid–base synergistic excitation. The explosion suppression performance of CG, RCG, and MCG was investigated through a 2.5 L semi-closed explosion pipe. The experimental results were compared and analyzed, and their pyrolysis characteristics, phase composition, and particle size were analyzed to reveal their explosion suppression mechanism. It was proved that MCG had the best explosion suppression effect. Under the condition of 9.5% methane–air, it was found that the explosion suppression effect was most significant when the powder mass of the three powders was 300, 360, and 360 mg, respectively. The peak explosion overpressure is reduced by 10.51%, 21.96%, and 32.66%, respectively, and the peak arrival time of flame velocity is extended by .14 times, .20 times, and 1.15 times, respectively. MCG can effectively inhibit methane explosion utilizing physical and chemical synergistic heat absorption, porous structure formation barrier, heat isolation, oxygen dilution, adsorption, and capture of free radicals.

The dynamic operation and deep peak-shaving of power-generating units cause significant fluctuations in flue gas flowrate, thus affecting the accuracy of CO₂ emissions measured by continuous emission monitoring systems (CEMS). This study established a long short-term memory network with an attention mechanism (LSTM-AM) for the soft measurement of the flue gas flowrate in real-time. First, flue gas flowrate data and continuous operation parameters over 25 days were sampled from a typical 660 MW coal-fired boiler in China. Then, a carbon balance model was established to verify the data reliability. The LSTM-AM model was trained and testified at the 660 MW coal-fired boiler. Results show that the LSTM-AM model significantly surpassed the pristine LSTM model without attention, the convolutional neural network (CNN) with LSTM, and the static support vector regression (SVR) model in the real-time prediction of flue gas flowrate. Finally, the LSTM-AM model was generalized to a 630 MW coal-fired power unit via transfer learning, which was further demonstrated to outperform the model re-trained from scratch. This work manifests the feasibility of deep learning for the soft measurement of flue gas flowrate, which is promising to solve data-lagging issues when measuring CO₂ emissions from coal-fired power plants.