Canadian Journal of Chemical Engineering最新文献

This study presents a hydrogen transfer reaction of 1,2-butanediol (BDO) to nitrobenzene for the simultaneous production of 1-hydroxy butanone and aniline over Cu/SiO₂ catalysts. A series of Cu supported SiO₂ catalysts with Cu loading up to 25 wt.% were prepared by the wet impregnation method. The prepared catalysts were further characterized by various characterization techniques such as X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) surface area, Fourier transform infrared (FTIR), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and temperature-programmed reduction (TPR). The transfer hydrogenation of nitrobenzene through the dehydrogenation of BDO was effectively accomplished rather than hydrogenation of nitrobenzene via external hydrogen due to well dispersed copper nanoparticle on the surface of SiO₂. The present strategy enables the production of two industrially important chemicals in a single step with stoichiometric amount of hydrogen source. Among the series of catalysts, 20 wt.% Cu/SiO₂ catalyst exhibited excellent catalytic performance (89% conversion of BDO and 85% conversion of nitrobenzene). The catalyst also shows very good stability for 9 h during the time-on-stream.

To mitigate global warming, it is crucial to reduce CO₂ emissions from the combustion of fossil fuels. CO₂ separation plays a key role in this process. Deep eutectic solvents (DESs) have demonstrated significant advantages and are considered promising liquid absorbents. In this study, DESs were chosen as absorbents for CO₂ separation from various CO₂ streams, including flue gas, lime kiln gas, bio-syngas, and biogas by thermodynamic analysis. Based on the criteria of the amount of absorbents required and energy use, several DESs including N,N-dimethylethanolammonium chloride/urea (1:1), choline chloride/urea (2:3), choline chloride/urea (2:5) were selected for the four CO₂ streams. Meanwhile, choline chloride/lactic acid (1:5) was selected for flue gas, tetrabutylammonium bromide/lactic acid (1:3) was selected for lime kiln gas, and N,N-dimethylethanolammonium chloride/urea (1:1) was selected for bio-syngas and biogas. It is revealed that the selected DESs exhibit a lower amount of absorbents required and lower energy use than those of other DESs and their aqueous solutions. The relationship among the absorption pressure, the energy use, the physical properties, and the critical properties of DESs are established for the four CO₂ streams. It is shown that the absorption pressure of the DESs can be fitted with the physical properties, which are density and heat capacity, with average relative deviations lower than 5%, while the energy use can be fitted with the critical properties, which are critical temperature and critical pressure, with average relative deviations below 1%. It suggests that the selected DESs have potential for further applications.

Two-phase flow pattern prediction is essential in predicting liquid holdup, pressure gradient, and flow assurance risks in various applications in the chemical, nuclear, and petroleum industries. Recent studies of flow pattern model evaluation in high liquid viscosity two-phase flow in vertical upward pipe flow revealed discrepancies in all transition boundaries, specifically the intermittent (IN)/annular (AN) flow transition. Therefore, this study aims to investigate the effect of liquid viscosity on IN/AN flow pattern transition and to improve the existing models. Specifically, Taitel et al.'s IN/AN transition model is improved by incorporating the liquid viscosity effect on liquid droplet fallback and liquid film thickness. Furthermore, sensitivity analyses on Barnea's IN/AN flow pattern transition model revealed that the interfacial friction factor (f_i) and liquid entrainment (f_E) closure relationships are crucial in the film bridging and film instability mechanisms of the flow transition. Therefore, a comprehensive evaluation of the performance of the f_i and f_E closure relationships is carried out, revealing that Pan and Hanratty's f_E correlation and Ishii and Grolmes' f_i correlation is the best combination with the least prediction error over a wide range of liquid viscosity. A validation study against an extensive experimental high liquid viscosity flow pattern database with liquid viscosity ranging from 4 to 1600 mPa·s showed high prediction performance for the proposed improved Taitel et al. and Barnea IN/AN flow pattern transition models.

Coal-fired power plants remain a major source of global CO₂ emissions, posing urgent challenges for climate mitigation. This study proposes an AI-enabled optimal control strategy for solvent-based post-combustion CO₂ capture (PCC), aiming to reduce energy consumption and enhance environmental performance. A deep learning model combining convolutional neural networks and long short-term memory (CNN-LSTM) is developed to predict multi-step CO₂ capture rates. This model is integrated with a multi-objective grey wolf optimizer (MOGWO)-based economic model predictive controller (EMPC), which dynamically adjusts key operating variables. Simulation results demonstrate that the proposed control scheme achieves a 12.4% reduction in capture cost and a 10.6% decrease in energy consumption, while maintaining a high CO₂ capture efficiency of 95.3%. These improvements not only optimize process economics while significantly lowering the environmental impact of carbon capture systems. These improvements contribute directly to carbon mitigation, offering a promising pathway for cleaner and more sustainable operation of coal-based power generation under dynamic industrial conditions.

The present study focuses on the production of biodiesel through the transesterification process and investigates the physicochemical properties of grape seed and Kusum oils methyl ester. Optimization of key process parameters, including molar ratio, catalyst concentration, reaction time, and temperature, was conducted for both oils. The effects of these factors on biodiesel production and conversion efficiency were analyzed. A 3 × 3 × 3 completely randomized design asymmetrical factorial approach was used to optimize reaction conditions. A total of 54 experiments were conducted to assess the effect of various parameters on ester recovery efficiency and kinematic viscosity. For grape seed oil methyl ester, optimal conditions were determined to be 0.5 wt.% KOH catalyst, 4:1 molar ratio, a reaction temperature of 60°C, and a reaction time of 60 min, resulting in a yield of 99% grape seed oil methyl ester with a viscosity of 4.25 cSt. In contrast, the optimal conditions for Kusum oil methyl ester included an 8:1 molar ratio, 1.5 wt.% KOH catalyst, a reaction temperature of 60°C, and 60-min reaction time, achieving 95.58% yield of Kusum oil methyl ester with a viscosity of 9.53 cSt. The results indicate that grape seed oil methyl ester is a superior choice compared to Kusum oil methyl ester in terms of biodiesel yield and kinematic viscosity. The physicochemical properties of both esters, including kinematic viscosity, density, flash and fire points, cloud and pour points, and calorific value, met the ASTM D6751 and EN 14214 standards, confirming their suitability as alternative fuels for diesel engines.

Development of novel desalination technologies is driven by the global need for efficient, sustainable water treatment solutions amid increasing water and energy demands. Zinc–air desalination batteries (ZADBs) offer a dual advantage by both desalinating brackish water and generating energy, positioning them as promising alternatives to traditional methods. This study evaluated a ZADB for brackish water treatment, focusing on its desalination performance under varying salinity, composition, current, and catholyte concentrations. The ZADB setup included a zinc anode, anion and cation exchange membranes, and an air cathode. Results showed a salt rejection rate of 98.5% at 2500 ppm of NaCl solution, which decreases to 59.7% at 7500 ppm, indicating that high salinity challenges the desalination process due to ion interactions. Increasing the current from 1 mA to 2 mA improved salt removal rates, particularly at higher salinities. Testing different catholyte concentrations revealed no adverse effect on the desalination performance, maintaining high salt rejection and stable charge efficiency. Moreover, the results showed that the system can desalinate solutions other than NaCl (i.e., LiCl and Na₂SO₄). Furthermore, the use of oxygen nanobubbles in the catholyte led to an approximate 12% improvement in salt rejection, attributed to the elevated dissolved oxygen concentration (~ 36 ppm) compared to the baseline condition (8.6 ppm). The study highlights the ZADB's potential for treating saline water, with optimized conditions improving energy conversion and salt removal efficiency, supporting its viability for sustainable desalination applications.

Development of novel desalination technologies is driven by the global need for efficient, sustainable water treatment solutions amid increasing water and energy demands. Zinc–air desalination batteries (ZADBs) offer a dual advantage by both desalinating brackish water and generating energy, positioning them as promising alternatives to traditional methods. This study evaluated a ZADB for brackish water treatment, focusing on its desalination performance under varying salinity, composition, current, and catholyte concentrations. The ZADB setup included a zinc anode, anion and cation exchange membranes, and an air cathode. Results showed a salt rejection rate of 98.5% at 2500 ppm of NaCl solution, which decreases to 59.7% at 7500 ppm, indicating that high salinity challenges the desalination process due to ion interactions. Increasing the current from 1 mA to 2 mA improved salt removal rates, particularly at higher salinities. Testing different catholyte concentrations revealed no adverse effect on the desalination performance, maintaining high salt rejection and stable charge efficiency. Moreover, the results showed that the system can desalinate solutions other than NaCl (i.e., LiCl and Na₂SO₄). Furthermore, the use of oxygen nanobubbles in the catholyte led to an approximate 12% improvement in salt rejection, attributed to the elevated dissolved oxygen concentration (~ 36 ppm) compared to the baseline condition (8.6 ppm). The study highlights the ZADB's potential for treating saline water, with optimized conditions improving energy conversion and salt removal efficiency, supporting its viability for sustainable desalination applications.

Canned motor pumps are widely used in chemical and nuclear industries for transporting hazardous fluids. There are few studies on the effects of structural changes to the rear wear ring and balance hole on leakage and axial force in canned motor pumps, and the mechanisms for improving rear pump chamber flow have not been revealed. This paper modifies the rear wear ring and balance hole to reveal mechanisms of their impact on rear pump chamber flow and demonstrates that the improved designs reduce axial force, minimize leakage, and enhance operational stability. The results show that increasing the rear wear ring clearance width stabilizes the axial force, reaching equilibrium when the clearance is 0.4 mm ($��b�$ = 0.4 mm). The inverted trapezoid rear wear ring exhibits the lowest leakage, averaging a 15.97% reduction across flow rates. Changes to the rear wear ring clearance structure are found to reduce leakage and rear pump chamber pressure while slightly improving efficiency. Adjusting the balance hole diameter reduces the leakage backflow interference on the impeller internal flow and promotes the vortex structure development within the balance hole. Changes to radial position of the balance hole effectively reduce leakage. When balance holes radial position is 59 mm ($��r�$ = 59 mm), the vortex structure can be utilized to control impact of leakage flow on the mainstream within impeller. This paper provides certain theoretical reference for the design, optimization, and application of canned motor pumps.

The flexible operation of coal-fired power plants under deep peak-shaving conditions imposes significant challenges on accurate NOx prediction for SCR systems. Given the inherent complexities of the SCR denitrification process, characterized by dynamic nonlinearity, temporal variability, and multivariable coupling in nitrogen oxide emissions, this study proposes a convolutional neural network-gated recurrent unit (CNN-GRU) hybrid model integrated with multi-head attention (MA) mechanisms to address these system-specific characteristics for precise NOx prediction. The model combines the local feature extraction capability of CNNs, the long-term temporal dependency modelling strength of GRUs, and the adaptive feature weighting functionality of MA mechanisms, achieving dynamic weight allocation across feature channels and temporal scales to enhance robustness and feature representation. Furthermore, a sparrow search algorithm (SSA) is introduced to optimize model parameters adaptively, improving prediction accuracy and generalization performance. Experimental validation using real operational data demonstrates the model's superior performance, with mean absolute error (MAE) below 0.5 mg/m³ and mean absolute percentage error (MAPE) below 2%. Ablation experiments confirm the effectiveness of the proposed architecture, showing over 28% prediction accuracy improvement compared to Transformer-based models while maintaining enhanced generalization capability.

This study investigates the impact of incorporating an internal vortex finder in the hydrocyclone overflow to enhance performance in terms of oil concentration using computational fluid dynamics (CFD) techniques. A three-factor Box–Behnken design was employed to evaluate the influence of the internal overflow pipe diameter and the external overflow and underflow diameters. The optimal hydrocyclone configuration, designated as HC-05, features an internal overflow diameter of 10 mm, an external overflow diameter of 17.5 mm, and an underflow diameter of 20 mm. This configuration achieves an overall total efficiency ($��E_T^{\prime }�$) of 90.4% while producing a more concentrated volumetric oil stream from the internal overflow and capturing 99.9% of all sand particles in the underflow.