Pub Date : 2026-03-01Epub Date: 2026-01-22DOI: 10.1016/j.cherd.2026.01.047
Abeer A. Rajhi , Amal S. Basaleh , Naif S. Aljohani , Ahmed Shawky , Mostafa E. Salem , Reda M. Mohamed
The progress of highly efficient and robust photocatalysts is essential for addressing the global challenge of heavy metal water contamination. In this work, a novel ternary nanocomposite was constructed by impregnating trace amounts of palladium(II) oxide (PdO) nanoparticles onto a silica-supported molybdenum trioxide (MoO3/SiO2) framework via a facile sol-gel method. The resulting PdO/MoO3/SiO2 heterostructures were thoroughly characterized to improve their photocatalytic performance. The heterostructure with an optimal loading of 4.0 wt% PdO verified superior properties, including relatively higher specific surface area of 150.19 m2g–1, a significantly lessened optical bandgap of 2.11 eV, and distinctly improved charge carrier separation. Under visible-light exposure, this adjusted photocatalyst displayed outstanding activity, achieving the complete photoreduction of aqueous Hg(II) ions in an faster timeframe of 45 min. The reaction tracked pseudo-first-order kinetics, with a high initial rate of 29.06 µM min–1. The catalyst also exhibits extraordinary stability, preserving 96 % of its initial efficiency after five recycles. These findings indicate the PdO/MoO3/SiO2 nanocomposite as a capable, high-performance photocatalyst for real application in environmental remediation.
{"title":"PdO-sensitized MoO3/SiO2 S-scheme heterojunction as a highly efficient and reusable photocatalyst for visible-light driven Hg(II) remediation","authors":"Abeer A. Rajhi , Amal S. Basaleh , Naif S. Aljohani , Ahmed Shawky , Mostafa E. Salem , Reda M. Mohamed","doi":"10.1016/j.cherd.2026.01.047","DOIUrl":"10.1016/j.cherd.2026.01.047","url":null,"abstract":"<div><div>The progress of highly efficient and robust photocatalysts is essential for addressing the global challenge of heavy metal water contamination. In this work, a novel ternary nanocomposite was constructed by impregnating trace amounts of palladium(II) oxide (PdO) nanoparticles onto a silica-supported molybdenum trioxide (MoO<sub>3</sub>/SiO<sub>2</sub>) framework via a facile sol-gel method. The resulting PdO/MoO<sub>3</sub>/SiO<sub>2</sub> heterostructures were thoroughly characterized to improve their photocatalytic performance. The heterostructure with an optimal loading of 4.0 wt% PdO verified superior properties, including relatively higher specific surface area of 150.19 m<sup>2</sup>g<sup>–1</sup>, a significantly lessened optical bandgap of 2.11 eV, and distinctly improved charge carrier separation. Under visible-light exposure, this adjusted photocatalyst displayed outstanding activity, achieving the complete photoreduction of aqueous Hg(II) ions in an faster timeframe of 45 min. The reaction tracked pseudo-first-order kinetics, with a high initial rate of 29.06 µM min<sup>–1</sup>. The catalyst also exhibits extraordinary stability, preserving 96 % of its initial efficiency after five recycles. These findings indicate the PdO/MoO<sub>3</sub>/SiO<sub>2</sub> nanocomposite as a capable, high-performance photocatalyst for real application in environmental remediation.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 120-129"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-27DOI: 10.1016/j.cherd.2026.01.056
Muhammad Usman Farid , Laura Unger , Dyrney Araújo dos Santos , Andreas Bück
Fine aggregates are considered as essential elements in the production of a wide range of food, pharmaceutical as well as other chemical products. In process industry, mixing of such particles is a crucial operation which controls the quality, texture and attributes of the final product. However, mixing becomes quite challenging while dealing with cohesive particles because of strong inter particulate forces, mostly van der Waals or capillary forces. A strong external force is required to overcome the cohesive forces and eventually, to agitate and mix such aggregates. With several advantages, mixing of such aggregates can be carried out in gas phase regime using fluidized bed systems. However, gas-solid environment yields to turbulence multiphase flow dynamics which needs to be investigated for optimum performance. In the current study, a two-way coupled Euler-Lagrange CFD model has been developed for the investigation of hydrodynamics and mixing of multiphase flows in an opposed jets fluidized bed. In total two phases were selected including air as a gas phase whereas TiO2 was considered as the solid phase. Particles were placed in the domain at known quantity and different streams of air jet were injected with the help of three nozzles mounted in the bottom and side walls of the apparatus. As a result, fluid dynamically different zones were formed such as stressing zone and mixing zone. Increasing air flow rate, the suspension and mixing of particles is improved. However, very high air injections results in formation of wall bounded layer of particles which negatively effects the mixing. High particle concentration was found near the wall in case of air flow rate injected at a flow rate of 0.003 kg/s. Further investigations are planned in order to further explore effect of dynamic classifier, particle size distribution and mass loading.
{"title":"Numerical study of multiphase mixing of micron sized aggregates in opposed jets fluidized bed","authors":"Muhammad Usman Farid , Laura Unger , Dyrney Araújo dos Santos , Andreas Bück","doi":"10.1016/j.cherd.2026.01.056","DOIUrl":"10.1016/j.cherd.2026.01.056","url":null,"abstract":"<div><div>Fine aggregates are considered as essential elements in the production of a wide range of food, pharmaceutical as well as other chemical products. In process industry, mixing of such particles is a crucial operation which controls the quality, texture and attributes of the final product. However, mixing becomes quite challenging while dealing with cohesive particles because of strong inter particulate forces, mostly van der Waals or capillary forces. A strong external force is required to overcome the cohesive forces and eventually, to agitate and mix such aggregates. With several advantages, mixing of such aggregates can be carried out in gas phase regime using fluidized bed systems. However, gas-solid environment yields to turbulence multiphase flow dynamics which needs to be investigated for optimum performance. In the current study, a two-way coupled Euler-Lagrange CFD model has been developed for the investigation of hydrodynamics and mixing of multiphase flows in an opposed jets fluidized bed. In total two phases were selected including air as a gas phase whereas TiO<sub>2</sub> was considered as the solid phase. Particles were placed in the domain at known quantity and different streams of air jet were injected with the help of three nozzles mounted in the bottom and side walls of the apparatus. As a result, fluid dynamically different zones were formed such as stressing zone and mixing zone. Increasing air flow rate, the suspension and mixing of particles is improved. However, very high air injections results in formation of wall bounded layer of particles which negatively effects the mixing. High particle concentration was found near the wall in case of air flow rate injected at a flow rate of 0.003 kg/s. Further investigations are planned in order to further explore effect of dynamic classifier, particle size distribution and mass loading.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 223-233"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-27DOI: 10.1016/j.cherd.2026.01.053
Ayse Elif Ates , Sinan Ates , Serdar Aydın , Gamze Varank
The treatment of real pharmaceutical wastewater remains a major challenge due to its highly complex composition, strong matrix effects, and associated toxicity. In this study, a real industrial pharmaceutical wastewater was treated using electrocatalytic oxidation (ECO) and photo electrocatalytic oxidation (PECO) processes employing Zn/TiO2-coated stainless-steel electrodes. The performance of the two processes was systematically evaluated and compared under identical operating conditions. Response Surface Methodology (RSM) was applied to optimize key operational parameters, including initial pH, applied current density, reaction time, and temperature. The developed models successfully predicted COD and UV254 removal efficiencies with high accuracy (R2>0.98), revealing strong interaction effects among operational variables. Principal Component Analysis (PCA) was further employed to elucidate multivariate relationships, identifying COD, UV254, and current density as the dominant contributors to process variability. Among the tested configurations, the PECO system using a Zn/TiO2-TiO2 electrode pair exhibited superior performance, achieving maximum removal efficiencies of 78.78 % COD and 71.75 % UV254. Acute toxicity assessment using Daphnia magna demonstrated a substantial improvement in effluent quality, with immobilization decreasing from 97 % to 28 % after PECO treatment. A strong correlation between UV₂₅₄ reduction and toxicity abatement was observed, indicating that UV254 may serve as a useful indicative parameter for tracking ecotoxicity changes within this specific system. This study presents a comparative and integrated evaluation of ECO and PECO processes for real pharmaceutical wastewater, combining advanced electrode design, statistical optimization, multivariate analysis, and ecotoxicological assessment. The results highlight the critical role of photo-assisted electrocatalysis and process optimization in achieving effective pollutant removal and toxicity reduction under realistic industrial conditions.
{"title":"Performance comparison of electrocatalytic and photoelectrocatalytic oxidation processes for the treatment of real pharmaceutical wastewater: Mechanistic insights and acute toxicity assessment","authors":"Ayse Elif Ates , Sinan Ates , Serdar Aydın , Gamze Varank","doi":"10.1016/j.cherd.2026.01.053","DOIUrl":"10.1016/j.cherd.2026.01.053","url":null,"abstract":"<div><div>The treatment of real pharmaceutical wastewater remains a major challenge due to its highly complex composition, strong matrix effects, and associated toxicity. In this study, a real industrial pharmaceutical wastewater was treated using electrocatalytic oxidation (ECO) and photo electrocatalytic oxidation (PECO) processes employing Zn/TiO<sub>2</sub>-coated stainless-steel electrodes. The performance of the two processes was systematically evaluated and compared under identical operating conditions. Response Surface Methodology (RSM) was applied to optimize key operational parameters, including initial pH, applied current density, reaction time, and temperature. The developed models successfully predicted COD and UV<sub>254</sub> removal efficiencies with high accuracy (R<sup>2</sup>>0.98), revealing strong interaction effects among operational variables. Principal Component Analysis (PCA) was further employed to elucidate multivariate relationships, identifying COD, UV<sub>254</sub>, and current density as the dominant contributors to process variability. Among the tested configurations, the PECO system using a Zn/TiO<sub>2</sub>-TiO<sub>2</sub> electrode pair exhibited superior performance, achieving maximum removal efficiencies of 78.78 % COD and 71.75 % UV<sub>254</sub>. Acute toxicity assessment using <em>Daphnia magna</em> demonstrated a substantial improvement in effluent quality, with immobilization decreasing from 97 % to 28 % after PECO treatment. A strong correlation between UV₂₅₄ reduction and toxicity abatement was observed, indicating that UV<sub>254</sub> may serve as a useful indicative parameter for tracking ecotoxicity changes within this specific system. This study presents a comparative and integrated evaluation of ECO and PECO processes for real pharmaceutical wastewater, combining advanced electrode design, statistical optimization, multivariate analysis, and ecotoxicological assessment. The results highlight the critical role of photo-assisted electrocatalysis and process optimization in achieving effective pollutant removal and toxicity reduction under realistic industrial conditions.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 204-222"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-28DOI: 10.1016/j.cherd.2026.01.058
Mrudul Nilesh Shroff, Supriyo Kumar Mondal, Sandhya R. Shewale
Sunflower seeds (Helianthus annuus L.) are well-known for their high protein and oil content, which are particularly abundant in monounsaturated and polyunsaturated fatty acids (MUFA and PUFA). Traditionally, oil extraction from these seeds involves pre-pressing and the use of solvents like n-hexane. However, these method has certain disadvantages, including solvent toxicity and prolonged processing times. To mitigate these issues, the three phase partitioning (TPP) technique has been introduced as an alternative, allowing for the efficient extraction of both oil and high-quality protein from sunflower seed residue. The TPP technique was used to extract oil from sunflower seeds, optimizing parameters such as ammonium sulphate concentration (45% w/v), slurry to t-butanol ratio (1:2 v/v), temperature (28 ± 2 °C), and solid to aqueous ratio (1:10 w/v). The study also includes a comparison of two types of ultrasound assisted TPP study. Ultrasound pre-treatment followed by TPP and simultaneous ultrasound-assisted TPP, both yielding 48.3% and 48% oil extraction. Extraction kinetics for conventional method, ultrasound-assisted three phase partitioning (UTPP), and ultrasound pre-treatment-assisted three phase partitioning (UPTPP) conformed to Peleg’s model.
{"title":"A study of three phase partitioning and ultrasound assisted three phase partitioning method to extract sunflower oil","authors":"Mrudul Nilesh Shroff, Supriyo Kumar Mondal, Sandhya R. Shewale","doi":"10.1016/j.cherd.2026.01.058","DOIUrl":"10.1016/j.cherd.2026.01.058","url":null,"abstract":"<div><div>Sunflower seeds (<em>Helianthus annuus L.</em>) are well-known for their high protein and oil content, which are particularly abundant in monounsaturated and polyunsaturated fatty acids (MUFA and PUFA). Traditionally, oil extraction from these seeds involves pre-pressing and the use of solvents like n-hexane. However, these method has certain disadvantages, including solvent toxicity and prolonged processing times. To mitigate these issues, the three phase partitioning (TPP) technique has been introduced as an alternative, allowing for the efficient extraction of both oil and high-quality protein from sunflower seed residue. The TPP technique was used to extract oil from sunflower seeds, optimizing parameters such as ammonium sulphate concentration (45% w/v), slurry to t-butanol ratio (1:2 v/v), temperature (28 ± 2 °C), and solid to aqueous ratio (1:10 w/v). The study also includes a comparison of two types of ultrasound assisted TPP study. Ultrasound pre-treatment followed by TPP and simultaneous ultrasound-assisted TPP, both yielding 48.3% and 48% oil extraction. Extraction kinetics for conventional method, ultrasound-assisted three phase partitioning (UTPP), and ultrasound pre-treatment-assisted three phase partitioning (UPTPP) conformed to Peleg’s model.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 234-242"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-27DOI: 10.1016/j.cherd.2026.01.031
Yao Shi, Ming Xiao, Zhe Wu
Traditional Lyapunov-based model predictive control (LMPC) using machine learning models typically involves three sequential steps: developing a machine learning (ML) model, designing a Lyapunov function for stability guarantees, and constructing the model predictive controller (MPC). However, these steps are inherently interdependent, and improper design in one component, such as the ML model or the Lyapunov function, can adversely affect controller design and closed-loop performance. To overcome these challenges, we propose an end-to-end machine learning-based Lyapunov-stable MPC (E2E-MLMPC) framework that simultaneously learns the Lyapunov function and MPC policy for nonlinear systems directly from data. Given a pre-trained ML model, a stabilizing control policy is learned within a unified computational graph that integrates the ML-based dynamics, system constraints, and Lyapunov stability conditions. The neural policy parameters are optimized via automatic differentiation, enabling end-to-end training with explicit stability certification. A rigorous theoretical analysis is provided to establish the closed-loop stability of the resulting controller. Furthermore, since the learned controller is implemented as a neural network, it substantially reduces online computation time compared with traditional ML-based MPC schemes. Simulation studies demonstrate that the proposed E2E-MLMPC framework achieves stable and efficient control performance in a chemical reactor example.
{"title":"End-to-end machine learning of Lyapunov-stable MPC for nonlinear systems with unknown dynamics","authors":"Yao Shi, Ming Xiao, Zhe Wu","doi":"10.1016/j.cherd.2026.01.031","DOIUrl":"10.1016/j.cherd.2026.01.031","url":null,"abstract":"<div><div>Traditional Lyapunov-based model predictive control (LMPC) using machine learning models typically involves three sequential steps: developing a machine learning (ML) model, designing a Lyapunov function for stability guarantees, and constructing the model predictive controller (MPC). However, these steps are inherently interdependent, and improper design in one component, such as the ML model or the Lyapunov function, can adversely affect controller design and closed-loop performance. To overcome these challenges, we propose an end-to-end machine learning-based Lyapunov-stable MPC (E2E-MLMPC) framework that simultaneously learns the Lyapunov function and MPC policy for nonlinear systems directly from data. Given a pre-trained ML model, a stabilizing control policy is learned within a unified computational graph that integrates the ML-based dynamics, system constraints, and Lyapunov stability conditions. The neural policy parameters are optimized via automatic differentiation, enabling end-to-end training with explicit stability certification. A rigorous theoretical analysis is provided to establish the closed-loop stability of the resulting controller. Furthermore, since the learned controller is implemented as a neural network, it substantially reduces online computation time compared with traditional ML-based MPC schemes. Simulation studies demonstrate that the proposed E2E-MLMPC framework achieves stable and efficient control performance in a chemical reactor example.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 130-141"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of an efficient valorisation of waste-activated sludge (WAS) from wastewater treatment plants (WWTPs) is a sustainable solution to bioresource and bioenergy exploitation. The use of hydrothermal treatment (HT) integrated with anaerobic digestion (AD) to enhance the efficiency of bioresource and bioenergy generation from WAS is the focal area of this research. The HT process was designed under a central composite design, while detoxification via adsorption, precipitation of struvite and biogas production under the AD process were further exploited to enhance the recovery of nutrients and biogas yields. The study has shown improvement in the solubilisation of organic matter after HT, phosphorus recovery, and biogas generation. Consequently, this integration approach offers an optimistic perspective on developing a novel strategy for improving resource recovery from WWTPs. A temperature of 220°C and a residence time of 20 min were found as optimum operating conditions for the HT, and effectively solubilised organics with reported soluble chemical oxygen demand (SCOD) from 613 mg/L to 8474 mg/L. The adsorption using magnetic biochar in the hydrothermally treated sludge was capable of reducing phenolic compounds by 37.9 % and heavy metals - copper, manganese, and nickel by 60.4, 73.5 and, 56.2 %, respectively. This process was also associated with a loss of phosphate and ammonium by 50.3 % and 47.2 %, respectively, through adsorption. The struvite precipitation process resulted in a high overall phosphorus recovery efficiency of 70.52 % and moderate ammonium removal efficiency of 35.71 % under the optimised condition of pH of 9.24 and the addition of 14.2 mL/L of magnesium chloride. The biogas yield was enhanced greatly in hydrothermally treated and detoxified sludge, highlighting the synergy between HT and AD with cumulative methane yields for WAS, HT, adsorption and precipitation streams of 2.3, 72.7, 58.6 and 32.4 mL/g-VS, respectively. Furthermore, the obtained hydrochar with a heating value of 17.8 MJ/kg makes it a viable biofuel source.
{"title":"Valorisation of sewage sludge for sustainable bioresources and bioenergy recovery through hydrothermal treatment","authors":"Boldwin Mutsvene , Manimagalay Chetty , Faizal Bux , Sheena Kumari","doi":"10.1016/j.cherd.2026.02.051","DOIUrl":"10.1016/j.cherd.2026.02.051","url":null,"abstract":"<div><div>The development of an efficient valorisation of waste-activated sludge (WAS) from wastewater treatment plants (WWTPs) is a sustainable solution to bioresource and bioenergy exploitation. The use of hydrothermal treatment (HT) integrated with anaerobic digestion (AD) to enhance the efficiency of bioresource and bioenergy generation from WAS is the focal area of this research. The HT process was designed under a central composite design, while detoxification via adsorption, precipitation of struvite and biogas production under the AD process were further exploited to enhance the recovery of nutrients and biogas yields. The study has shown improvement in the solubilisation of organic matter after HT, phosphorus recovery, and biogas generation. Consequently, this integration approach offers an optimistic perspective on developing a novel strategy for improving resource recovery from WWTPs. A temperature of 220°C and a residence time of 20 min were found as optimum operating conditions for the HT, and effectively solubilised organics with reported soluble chemical oxygen demand (SCOD) from 613 mg/L to 8474 mg/L. The adsorption using magnetic biochar in the hydrothermally treated sludge was capable of reducing phenolic compounds by 37.9 % and heavy metals - copper, manganese, and nickel by 60.4, 73.5 and, 56.2 %, respectively. This process was also associated with a loss of phosphate and ammonium by 50.3 % and 47.2 %, respectively, through adsorption. The struvite precipitation process resulted in a high overall phosphorus recovery efficiency of 70.52 % and moderate ammonium removal efficiency of 35.71 % under the optimised condition of pH of 9.24 and the addition of 14.2 mL/L of magnesium chloride. The biogas yield was enhanced greatly in hydrothermally treated and detoxified sludge, highlighting the synergy between HT and AD with cumulative methane yields for WAS, HT, adsorption and precipitation streams of 2.3, 72.7, 58.6 and 32.4 mL/g-VS, respectively. Furthermore, the obtained hydrochar with a heating value of 17.8 MJ/kg makes it a viable biofuel source.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 855-865"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-09DOI: 10.1016/j.cherd.2026.02.014
Fengcheng Jiang , Songyan Zhang , Xixi Feng , Chuanbing Zhang , Qiao Han , Junya Man , Mingshi Wang
Optimizing reaction parameters is essential for improving the degradation performance of recalcitrant pollutants. A central composite design response surface methodology was applied to evaluate the influence of four reagent dosages on phenol degradation in a Cu2+/cysteine (Cys)-assisted Fe3+/H2O2 system. The experimental data were used to construct a second-order polynomial regression model and a backpropagation (BP) neural network. To enhance model performance, a genetic algorithm (GA) was employed to optimize the structure and parameters of the BP network. The GA-optimized BP neural network demonstrated superior predictive accuracy over the polynomial regression model. The optimal concentrations of Fe3+, Cu2+, Cys, and H2O2 were 105.17 μM, 68.97 μM, 93.97 μM, and 8.16 mM, respectively. Under the optimal conditions, the experimental phenol degradation efficiency reached 96.95 %, closely aligned with the predicted value of 95.33 %, corresponding to a relative error of only 1.62 %. The coefficient of determination (R2) for the training and test sets was 0.9937 and 0.9898, respectively, indicating excellent model fitting and generalization performance. Validation experiments with biologically treated coking wastewater confirmed that the optimized reagent dosage strategy remained effective and practically applicable under realistic water matrix conditions. These findings confirm that integrating response surface methodology based on a central composite design with a genetic algorithm and BP neural networks provides an effective strategy for optimizing multi-component advanced oxidation systems, which is of positive significance for the development of high-efficiency pollutant removal technologies.
{"title":"Optimization of phenol degradation in Cys/Fe3 + /Cu2+/H2O2 systems using a genetic algorithm–enhanced BP neural network","authors":"Fengcheng Jiang , Songyan Zhang , Xixi Feng , Chuanbing Zhang , Qiao Han , Junya Man , Mingshi Wang","doi":"10.1016/j.cherd.2026.02.014","DOIUrl":"10.1016/j.cherd.2026.02.014","url":null,"abstract":"<div><div>Optimizing reaction parameters is essential for improving the degradation performance of recalcitrant pollutants. A central composite design response surface methodology was applied to evaluate the influence of four reagent dosages on phenol degradation in a Cu<sup>2+</sup>/cysteine (Cys)-assisted Fe<sup>3+</sup>/H<sub>2</sub>O<sub>2</sub> system. The experimental data were used to construct a second-order polynomial regression model and a backpropagation (BP) neural network. To enhance model performance, a genetic algorithm (GA) was employed to optimize the structure and parameters of the BP network. The GA-optimized BP neural network demonstrated superior predictive accuracy over the polynomial regression model. The optimal concentrations of Fe<sup>3+</sup>, Cu<sup>2+</sup>, Cys, and H<sub>2</sub>O<sub>2</sub> were 105.17 μM, 68.97 μM, 93.97 μM, and 8.16 mM, respectively. Under the optimal conditions, the experimental phenol degradation efficiency reached 96.95 %, closely aligned with the predicted value of 95.33 %, corresponding to a relative error of only 1.62 %. The coefficient of determination (R<sup>2</sup>) for the training and test sets was 0.9937 and 0.9898, respectively, indicating excellent model fitting and generalization performance. Validation experiments with biologically treated coking wastewater confirmed that the optimized reagent dosage strategy remained effective and practically applicable under realistic water matrix conditions. These findings confirm that integrating response surface methodology based on a central composite design with a genetic algorithm and BP neural networks provides an effective strategy for optimizing multi-component advanced oxidation systems, which is of positive significance for the development of high-efficiency pollutant removal technologies.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 707-717"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-16DOI: 10.1016/j.cherd.2026.02.033
María Teresa Melo Parra , Nelson Anibal Pinzón Casallas , José Luiz Francisco Alves , Rodrigo Battisti , Cintia Marangoni , Ricardo Antonio Francisco Machado
This research proposed the novel configuration of multiple energetically intensified falling film distillation columns to minimize the high energy requirement in these processes. Specifically, the study aimed to assess the energy efficiency of a series configuration of falling film distillation columns with a two-phase closed thermosyphon heating system for separating the ethanol-water binary mixture. The process achieved substantial enrichment from 10 wt% to 87.2 wt% ethanol in the third column through experiments with three units in series. A theoretical model, implemented using Wolfram Mathematica® software, was developed and experimentally validated, showing good agreement. This model provided insight into the energy requirements of the proposed series configuration. Additionally, the model and simulations enabled the evaluation of temperature profiles within the column heights, which cannot be easily experimentally collected, possibly serving as a valuable data acquisition tool for future scale-ups of the unit. The multiple falling film unit configuration demonstrated higher energy efficiency, representing savings of about 29.5 % compared to a conventional tray distillation unit.
{"title":"A novel energy-saving configuration of falling film distillation columns in series: Modeling and experimental validation for ethanol-water binary system","authors":"María Teresa Melo Parra , Nelson Anibal Pinzón Casallas , José Luiz Francisco Alves , Rodrigo Battisti , Cintia Marangoni , Ricardo Antonio Francisco Machado","doi":"10.1016/j.cherd.2026.02.033","DOIUrl":"10.1016/j.cherd.2026.02.033","url":null,"abstract":"<div><div>This research proposed the novel configuration of multiple energetically intensified falling film distillation columns to minimize the high energy requirement in these processes. Specifically, the study aimed to assess the energy efficiency of a series configuration of falling film distillation columns with a two-phase closed thermosyphon heating system for separating the ethanol-water binary mixture. The process achieved substantial enrichment from 10 wt% to 87.2 wt% ethanol in the third column through experiments with three units in series. A theoretical model, implemented using Wolfram Mathematica® software, was developed and experimentally validated, showing good agreement. This model provided insight into the energy requirements of the proposed series configuration. Additionally, the model and simulations enabled the evaluation of temperature profiles within the column heights, which cannot be easily experimentally collected, possibly serving as a valuable data acquisition tool for future scale-ups of the unit. The multiple falling film unit configuration demonstrated higher energy efficiency, representing savings of about 29.5 % compared to a conventional tray distillation unit.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 768-778"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-17DOI: 10.1016/j.cherd.2026.02.041
Yajun Wu , Zongqing Guo , Xin Liu , Jingyu Lei , Xinglian Ye , Xizhong An , Hao Zhang
In the manufacturing process of lithium-ion battery electrodes, the coating process is a critical step for ensuring uniform slurry distribution and forming a stable coating layer. Slot-die coating plays an important role in electrode manufacturing because of its advantages of controllable coating thickness and suitability for large-scale continuous production. In this study, numerical models of the internal flow channels and the external structure of the slot-die head are established, and the coating process is systematically simulated. The results show that optimizing the structure of the downstream coating lip and properly matching the process parameters can significantly expand the coating window and improve process stability. At the same time, the uniformity of the slurry flow field can be effectively improved by adding a second uniform cavity. In addition, a prediction correlation between structural parameters and outlet velocity uniformity is developed using the response surface methodology, enabling quantitative evaluation of process conditions and providing a reliable basis for parameter optimization. This study provides theoretical support and a design basis for the large-scale and stable production of high-performance lithium-ion batteries.
{"title":"Numerical modelling and process optimisation of slot-die coating for lithium-ion battery electrodes","authors":"Yajun Wu , Zongqing Guo , Xin Liu , Jingyu Lei , Xinglian Ye , Xizhong An , Hao Zhang","doi":"10.1016/j.cherd.2026.02.041","DOIUrl":"10.1016/j.cherd.2026.02.041","url":null,"abstract":"<div><div>In the manufacturing process of lithium-ion battery electrodes, the coating process is a critical step for ensuring uniform slurry distribution and forming a stable coating layer. Slot-die coating plays an important role in electrode manufacturing because of its advantages of controllable coating thickness and suitability for large-scale continuous production. In this study, numerical models of the internal flow channels and the external structure of the slot-die head are established, and the coating process is systematically simulated. The results show that optimizing the structure of the downstream coating lip and properly matching the process parameters can significantly expand the coating window and improve process stability. At the same time, the uniformity of the slurry flow field can be effectively improved by adding a second uniform cavity. In addition, a prediction correlation between structural parameters and outlet velocity uniformity is developed using the response surface methodology, enabling quantitative evaluation of process conditions and providing a reliable basis for parameter optimization. This study provides theoretical support and a design basis for the large-scale and stable production of high-performance lithium-ion batteries.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 821-836"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-06DOI: 10.1016/j.cherd.2026.01.062
M.C.F. Silva , J.B.L.M. Campos , J.D.P. Araújo
This study focuses on understanding the 3D flow pattern of a Taylor bubble during the transition from a vertical to an inclined tube. Through Computational Fluid Dynamics (CFD) simulations, two cases are analyzed with distinct fluid properties, inducing different Eötvös and Morton numbers, allowing to explore how viscous and gravitational forces determine bubble shape, velocity, and stability of the flow. In Case A, which represents a lower-viscosity system, the bubble undergoes significant deformation, with noticeable asymmetry and a recirculating wake developing at the bubble’s tail. The bubble rising velocity, as well as the bubble length, fluctuates significantly during the passage in the transition region. In contrast, Case B, which has a higher viscosity, exhibits a more stable flow with less pronounced bubble deformation, resulting in a more constant bubble rising velocity and a more uniform bubble length throughout the transition region. These findings demonstrate the critical role of fluid properties in determining slug flow behavior in non-linear geometries.
{"title":"Numerical study of Taylor bubble dynamics across a vertical–inclined transition in stagnant liquid","authors":"M.C.F. Silva , J.B.L.M. Campos , J.D.P. Araújo","doi":"10.1016/j.cherd.2026.01.062","DOIUrl":"10.1016/j.cherd.2026.01.062","url":null,"abstract":"<div><div>This study focuses on understanding the 3D flow pattern of a Taylor bubble during the transition from a vertical to an inclined tube. Through Computational Fluid Dynamics (CFD) simulations, two cases are analyzed with distinct fluid properties, inducing different Eötvös and Morton numbers, allowing to explore how viscous and gravitational forces determine bubble shape, velocity, and stability of the flow. In Case A, which represents a lower-viscosity system, the bubble undergoes significant deformation, with noticeable asymmetry and a recirculating wake developing at the bubble’s tail. The bubble rising velocity, as well as the bubble length, fluctuates significantly during the passage in the transition region. In contrast, Case B, which has a higher viscosity, exhibits a more stable flow with less pronounced bubble deformation, resulting in a more constant bubble rising velocity and a more uniform bubble length throughout the transition region. These findings demonstrate the critical role of fluid properties in determining slug flow behavior in non-linear geometries.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 665-676"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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