Asia-Pacific Journal of Chemical Engineering最新文献

In this study, nonisothermal gasification experiments of lignite (SC) at different O₂ concentrations were conducted using TG to analyze the effects of heating rate and O₂ concentration on the kinetics and thermodynamics of SC. The FWO, KAS, CR, and integral master-plot methods were used to determine the kinetic and thermodynamic parameters. The results indicated that SC gasification proceeded in three distinct stages. At an O₂ flow rate of 1.5 mL/min, the average activation energies for SC gasification calculated using the CR (n = 1), FWO, and KAS methods were 79.99, 177.95, and 173.84 kJ/mol, respectively. At an O₂ flow rate of 3 mL/min, the corresponding values were 76.81, 128.28, and 126.81 kJ/mol. The gasification mechanism function of SC was determined as 𝑓(α) = (1−α)^𝑛, with the (𝑛) being 2.7 and 2 at O₂ flow rates of 1.5 and 3 mL/min, respectively. Thermodynamically, the gasification process was endothermic in both atmospheres, with positive values for Δ𝐻 and ΔG. The ΔS was negative at an O₂ flow rate of 1.5 mL/min and positive at an O₂ flow rate of 3 mL/min, likely due to the increased oxygen content intensifying the gasification reaction.

This study established an optimized ultrasound-assisted reverse micelle extraction (UARME) method for the simultaneous extraction of protein and oil from pigeon pea seeds, using sodium bis(2-ethylhexyl) sulfosuccinate (AOT)/n-hexane reverse micelles. Key factors in extraction processes were optimized to maximize extraction efficiency. The physicochemical and functional properties of the extracted pigeon pea seed protein (PPSP) and pigeon pea seed oil (PPSO) were comprehensively analyzed. The UARME achieved a protein extraction efficiency of 86.06%, significantly higher than the 73.13% obtained by the conventional alkaline soluble acid precipitation (ASAE) method. UARME-extracted PPSP differed significantly from ASAE-extracted PPSP in molecular weight, microstructure, and secondary structure. Meanwhile, UARME enabled the concurrent extraction of PPSO rich in linoleic acid with an efficiency of 49.78%. The PPSP obtained by UARME exhibited better solubility, oil-holding capacity, emulsifying activity, and stability, as well as foaming capacity and stability compared to that from ASAE. This indicates its great potential as an excellent protein source. Overall, UARME is a promising technology for the simultaneous extraction of protein and oil from pigeon pea seeds, providing a theoretical basis for their utilization in the food industry.

This study explores the conversion of plastic into NaOH and HNO₃ activated carbon (NHAC and HNAC) and ceria-impregnated activated carbon prepared using microwave and hydrothermal methods (Ce-M + AC and Ce-H + AC) for environmental applications. The focus is on the catalytic oxidation of phenolic compounds and adsorption of methylene blue dye. FTIR analysis confirmed the presence of functional groups critical for adsorption. SEM and BET analyses revealed that HNAC had the lowest surface area (0.735 m²/g) and largest particle size (88.64 μm), and Ce-H + AC shows the highest surface area (442.71 m²/g) and smallest particle size (14.73 μm). In catalytic wet oxidation of phenol, Ce-H + AC achieved a degradation efficiency of 99.6% due to better surface properties and metal functionality; however, HNAC (97.65%) was less effective due to its limited surface properties. In the case of methylene blue adsorption, Ce-H + AC shows again the highest performance with 99.92% adsorption, and HNAC shows the lowest adsorption performance with 14.54% adsorption. Adsorption kinetics followed the pseudo–second-order model, with most samples showing high R² values, except the HNAC sample. This research highlights the potential of repurposing plastic waste into effective adsorbents for environmental remediation.

In this work, the concept of optimal linearization is explored to develop computationally proficient model predictive control (MPC) algorithms for multi-input multi-output (MIMO) nonlinear processes. The algorithms use Laguerre filters and pruned least square support vector machine (LSSVM)–based Wiener model for predictions. Taylor's series–based model linearization is predominantly used to improve the computational efficiency of nonlinear MPCs. This approach gives good control performance at many times. However, certain processes exhibit significant nonlinearity and experience large set point variations. In such cases, the closed-loop control accuracy obtained through above (Taylor's series based) approach is very poor and demands an alternative solution. In this paper, instead of Taylor series–based linearization, an optimization-based solution is derived to determine linearizing coefficients' matrix. Based on the optimally linearized model, a classical MPC and explicit MPC algorithms are proposed. The proposed algorithms are tested for the multivariable control of polymerization reactor. The optimal linearization–based proposed explicit algorithm is found to be 6.25 times computationally faster than the nonlinear MPC. When compared with Taylor series linearization–based MPC, the proposed algorithm provides 3 times (for monomer concentration) and 15 times (for reactor temperature) better control accuracy.

A novel self-solidifying polymeric ionic liquid (P-[DMT-PS][PHSA]) was synthesized via phenolic condensation and applied as a recyclable acidic catalyst for biodiesel production. The catalyst demonstrated high acidity (4.68 mmol/g), excellent thermal stability, and effective catalytic performance, achieving 98.19% oleic acid conversion under optimized conditions. Notably, P-[DMT-PS][PHSA] is soluble during the esterification, allowing it to act as a homogeneous catalyst, and re-precipitates upon methanol evaporation for easy recovery. Even after 10 cycles, the catalyst maintained 97.0% oleic acid conversion, highlighting its stability and reusability. Additionally, P-[DMT-PS][PHSA] exhibits remarkable substrate adaptability, effectively catalyzing the esterification of a range of substrates. This study presents a simple and mild synthesis method for polymeric ionic liquids and showcases P-[DMT-PS][PHSA] as a promising alternative to conventional catalysts for biodiesel production.

The injection of dechlorination adsorbents into the flue gas of coal-fired power plants is a reliable and effective method for mitigating the enrichment of Cl ions in wet flue gas desulfurization (WFGD) systems for the purpose of reducing desulfurization wastewater generation and discharge. However, the flue gas dechlorination efficiency varies depending on both the performance of the dechlorination adsorbent and the arrangement of the injection apparatus. This work focuses on the optimization of injection parameters for flue gas HCl removal of a 300-MW coal-fired power plant, utilizing a high-performance ethanol-hydrated CaO dechlorination adsorbent. A detailed evaluation of critical parameters, including injection velocity, injection height, and the Ca/Cl molar ratio, was conducted to elucidate their impacts on HCl removal efficiency. The results suggest that the Ca/Cl molar ratio is the most fundamental influencing factor. The injection velocity can alter the uniformity and spatial coverage of the dechlorination adsorbent. The injection height changes residence time, thus significantly affecting the dechlorination efficiency. The optimization strategy based on the CFD simulation provides a solid foundation and guidance for the industry application of the coal-fired flue gas HCl removal technology.

Hydrogen energy, as a green and clean energy source of the 21st century, boasts numerous advantages including excellent combustion performance, no pollution, diverse storage methods, and significant development potential. However, the safety risks associated with hydrogen's combustibility and explosive nature cannot be overlooked. Hydrogen leaks during production and storage pose a serious threat when encountered with an ignition source. To gain a deeper understanding of hydrogen leakage patterns, hydrogen leakage accidents involving alkaline liquid entrainment in typical scenarios of hydrogen production are simulated using the CFD program and analyzed in conjunction with jet theory. The results indicate that the impact of alkaline liquid on hydrogen leakage is primarily in dilution and promotion of dispersion. The concentration of pure hydrogen leakage is generally higher than that of leakage involving alkaline liquid. Under the same break velocity, the range of the combustible zone for leakage involving alkaline liquid is consistent with pure hydrogen leakage in the vertical direction, yet significantly larger in the horizontal direction. Hydrogen leakage involving alkaline liquid also exhibits distinctly different flow patterns at various flow rates. At higher velocities, the overall characteristics are dominated by the momentum jet of hydrogen, presenting a positive buoyant jet flow pattern, whereas at lower velocities, the scenario is dominated by the alkaline liquid, exhibiting a negative buoyant jet flow. The characteristic effects of alkaline liquid on hydrogen also vary with changes in velocity.

Depth understanding on the pollutant dispersion mechanism in large scale industrial buildings is significant for improving the air quality and supplying technique references on ventilation system design. Although a large amount of researches on ventilation system have been conducted, the effect of the intermittent ventilation mode on the pollutant diffusion with multiple release sources is still unclear. In the present study, the dispersion performance of hydrogen sulfide in an actual rubber processing plant was comprehensively investigated by model test and numerical simulation. The hybrid natural ventilation with mechanical exhaust was designed and used for the removal of hydrogen sulfide. A model test rig was established to measure the pollutant distribution in a transparent glass chamber with substitutive fluid sulfur hexafluoride. The numerical model of pollutant dispersion was built with considerations of temperature stratification and concentration diffusion. Compared against the test data, the prediction deviation of the numerical model was limited within 10%. The influence of the intermittent ventilation modes on the hydrogen sulfide dispersion was investigated and analyzed in detail. Some findings were obtained finally. This study could enrich the ventilation design on hydrogen sulfide dispersion in actual industrial plants and may supply some new insights on the dispersion mechanism of pollutants.

The deactivation of V₂O₅-WO₃/TiO₂ (V-W/TiO₂) catalysts in NH₃-selective catalytic reduction (SCR) due to potassium (K) species from coal-fired power plant emissions has garnered significant attention, though the underlying mechanisms remain unclear. This study explores these deactivation mechanisms by introducing K poisoning through incipient wetness impregnation (IWI) and solid-state diffusion methods. Comprehensive analyses, including characterization techniques and density functional theory (DFT) simulations, revealed that increased KCl loading and longer diffusion times of calcination significantly reduce the catalyst's denitration activity. The interaction of KCl with the V₂O₅ component leads to a reduction in surface acidity and promotes K₂O formation, which causes agglomeration on catalyst surface and reduces the surface area. Both methods of poisoning also diminish the redox properties of the catalyst due to an increased presence of low-valent vanadium (V⁴⁺, V³⁺) species. These results provide a detailed understanding of the deactivation process, offering a foundation for developing strategies to enhance the alkali metal poisoning resistance of commercial SCR catalysts.