Kamel Landolsi, F. Echouchene, Ines Chouaieb, Mona A. Alamri, A. Bajahzar, H. Belmabrouk
The study focuses on the efficiency of hexaamminecobalt (III) chloride (HACo, [Co(NH3)6]Cl3) immobilized on activated carbon for removing methylene blue (MB) from water solutions. The primary objective of this study was to assess the sorption performance of HACo immobilized on activated carbon in removing MB from water solutions. Additionally, predictive models were developed to optimize the MB removal percentage. Lastly, the study aimed to determine the optimal conditions for achieving maximum MB removal. Samples were characterized using scanning electron microscopy. Batch sorption experiments were conducted to analyze the impact of MB concentration, adsorbent mass, pH, temperature, and contact time. Predictive models were built using multiple linear regression and neural network techniques, specifically artificial neural networks (ANN) and hybrid ANN–particle swarm optimization (ANN‐PSO). The PSO‐ANN model with a single hidden layer of eight neurons trained using the Levenberg–Marquardt algorithm demonstrated high accuracy in predicting MB removal percentage, with mean absolute percentage error (MAPE) = 0.083788, root mean square error (RMSE) = 0.11441, and R2 = 0.99693. The MB adsorption process followed a mono‐layer with one energy model and a pseudo‐first‐order kinetic model. Optimization using the genetic algorithm revealed that the maximum MB removal percentage of 99.56% is achievable at an MB concentration of 9.36 mg/L, adsorbent mass of 15.72 mg, and temperature of 311.2 K. The study confirms the effectiveness of HACo immobilized on activated carbon for MB removal. The PSO‐ANN predictive model proved superior in accuracy compared to empirical models. Optimization results provide the optimal conditions for maximizing MB removal, offering valuable insights for practical applications.
{"title":"Computational intelligence for empirical modelling and optimization of methylene blue adsorption phenomena utilizing an activated carbon‐supported [Co(NH3)6]Cl3 complex","authors":"Kamel Landolsi, F. Echouchene, Ines Chouaieb, Mona A. Alamri, A. Bajahzar, H. Belmabrouk","doi":"10.1002/cjce.25363","DOIUrl":"https://doi.org/10.1002/cjce.25363","url":null,"abstract":"The study focuses on the efficiency of hexaamminecobalt (III) chloride (HACo, [Co(NH3)6]Cl3) immobilized on activated carbon for removing methylene blue (MB) from water solutions. The primary objective of this study was to assess the sorption performance of HACo immobilized on activated carbon in removing MB from water solutions. Additionally, predictive models were developed to optimize the MB removal percentage. Lastly, the study aimed to determine the optimal conditions for achieving maximum MB removal. Samples were characterized using scanning electron microscopy. Batch sorption experiments were conducted to analyze the impact of MB concentration, adsorbent mass, pH, temperature, and contact time. Predictive models were built using multiple linear regression and neural network techniques, specifically artificial neural networks (ANN) and hybrid ANN–particle swarm optimization (ANN‐PSO). The PSO‐ANN model with a single hidden layer of eight neurons trained using the Levenberg–Marquardt algorithm demonstrated high accuracy in predicting MB removal percentage, with mean absolute percentage error (MAPE) = 0.083788, root mean square error (RMSE) = 0.11441, and R2 = 0.99693. The MB adsorption process followed a mono‐layer with one energy model and a pseudo‐first‐order kinetic model. Optimization using the genetic algorithm revealed that the maximum MB removal percentage of 99.56% is achievable at an MB concentration of 9.36 mg/L, adsorbent mass of 15.72 mg, and temperature of 311.2 K. The study confirms the effectiveness of HACo immobilized on activated carbon for MB removal. The PSO‐ANN predictive model proved superior in accuracy compared to empirical models. Optimization results provide the optimal conditions for maximizing MB removal, offering valuable insights for practical applications.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":" 908","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natalia Pazin Almeida, Cláudio Roberto Duarte, Mikel Tellabide, Idoia Estiati, Martin Olazar, Marcos Antonio de Souza Barrozo
This study proposes an efficient and sustainable process for annatto powder production using a fountain confined spouted bed. With widespread applications in industries such as food, pharmaceuticals, and cosmetics, conventional extraction methods face environmental and economic challenges. Our study explores a solvent‐free and eco‐friendly approach using mechanical attrition within a fountain confined spouted bed, offering a cost‐effective solution for annatto cultivation. We systematically investigated the impact of four parameters—fountain confiner position and length, draft tube diameter, and airflow velocity—employing experimental design, multiple regression analysis, particle swarm optimization, and computational fluid dynamics–discrete element method (CFD‐DEM) simulations. The proposed optimization condition shows significantly higher collision intensity, improving annatto powder production compared to other central composite design tests. This study contributes to developing of a sustainable and economically viable method for dye production, with potential implications for annatto‐producing regions globally.
{"title":"Sustainable dye extraction: Annatto powder production in a fountain confined spouted bed","authors":"Natalia Pazin Almeida, Cláudio Roberto Duarte, Mikel Tellabide, Idoia Estiati, Martin Olazar, Marcos Antonio de Souza Barrozo","doi":"10.1002/cjce.25292","DOIUrl":"https://doi.org/10.1002/cjce.25292","url":null,"abstract":"This study proposes an efficient and sustainable process for annatto powder production using a fountain confined spouted bed. With widespread applications in industries such as food, pharmaceuticals, and cosmetics, conventional extraction methods face environmental and economic challenges. Our study explores a solvent‐free and eco‐friendly approach using mechanical attrition within a fountain confined spouted bed, offering a cost‐effective solution for annatto cultivation. We systematically investigated the impact of four parameters—fountain confiner position and length, draft tube diameter, and airflow velocity—employing experimental design, multiple regression analysis, particle swarm optimization, and computational fluid dynamics–discrete element method (CFD‐DEM) simulations. The proposed optimization condition shows significantly higher collision intensity, improving annatto powder production compared to other central composite design tests. This study contributes to developing of a sustainable and economically viable method for dye production, with potential implications for annatto‐producing regions globally.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zefan Yan, Lin Jiang, Yu Tian, Rongzheng Liu, Youlin Shao, Bing Liu, Malin Liu
Fluidized bed‐chemical vapour deposition (FB‐CVD) is a kind of key technology used widely in many application fields, such as semiconductors, nuclear energy, energy storage, and catalysts. In recent years, it has drawn much attention in the preparation of nuclear fuel coated particles (CP). It also has long played a crucial role in the preparation of high‐temperature gas‐cooled reactor (HTGR) fuel pebbles. The multi‐scale study of FB‐CVD technology has paid attention to the industrial fabrication of nuclear fuel particles at a large scale. In this paper, the recent FB‐CVD studies of different application fields are summarized first. Then, the recent works of our group in the field of FB‐CVD process in nuclear fuel particle fabrication are summarized. The FB‐CVD process in nuclear fuel particle fabrication and the multi‐scale study of the FB‐CVD process are overviewed in detail. Molecular dynamics (MD) simulation is used to study the CVD process of preparing the coating layer at the micro‐scale. Computational fluid dynamics–discrete element model (CFD‐DEM) simulation is used to study the high‐density particle fluidization, mixing particle fluidization, and particle coating process at the particle scale. Process simulation is used to study the entire FB‐CVD production line at the macro scale. Finally, the great application potential of the multi‐scale coupling study of the FB‐CVD process in the industrial fabrication of nuclear fuel particles is revealed. This paper is helpful to develop the academic research field of fluidized beds. It also has inspiration and reference significance for the expansion of other industrial applications of FB‐CVD.
{"title":"Multi‐scale study of fluidized bed‐chemical vapour deposition process in nuclear fuel coated particle fabrication for high‐temperature gas‐cooled reactor: A review","authors":"Zefan Yan, Lin Jiang, Yu Tian, Rongzheng Liu, Youlin Shao, Bing Liu, Malin Liu","doi":"10.1002/cjce.25297","DOIUrl":"https://doi.org/10.1002/cjce.25297","url":null,"abstract":"Fluidized bed‐chemical vapour deposition (FB‐CVD) is a kind of key technology used widely in many application fields, such as semiconductors, nuclear energy, energy storage, and catalysts. In recent years, it has drawn much attention in the preparation of nuclear fuel coated particles (CP). It also has long played a crucial role in the preparation of high‐temperature gas‐cooled reactor (HTGR) fuel pebbles. The multi‐scale study of FB‐CVD technology has paid attention to the industrial fabrication of nuclear fuel particles at a large scale. In this paper, the recent FB‐CVD studies of different application fields are summarized first. Then, the recent works of our group in the field of FB‐CVD process in nuclear fuel particle fabrication are summarized. The FB‐CVD process in nuclear fuel particle fabrication and the multi‐scale study of the FB‐CVD process are overviewed in detail. Molecular dynamics (MD) simulation is used to study the CVD process of preparing the coating layer at the micro‐scale. Computational fluid dynamics–discrete element model (CFD‐DEM) simulation is used to study the high‐density particle fluidization, mixing particle fluidization, and particle coating process at the particle scale. Process simulation is used to study the entire FB‐CVD production line at the macro scale. Finally, the great application potential of the multi‐scale coupling study of the FB‐CVD process in the industrial fabrication of nuclear fuel particles is revealed. This paper is helpful to develop the academic research field of fluidized beds. It also has inspiration and reference significance for the expansion of other industrial applications of FB‐CVD.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140832220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. R. Souza, Fabiana Fregonesi, Wanderley P. Oliveira
The work aims to develop and optimize a powdered phytopharmaceutical product from the stem bark of Hymenaea courbaril L. (jatobá) by the spouted bed drying. The study commenced with the extraction of bioactive compounds present in the plant raw material by dynamic maceration using ethanol/water 70% (v/v) at a temperature of 50°C for 60 min, for the ratio stem bark: solvent mass of 1:10 (w/w). The extract quality was assessed by quantifying chemical markers via spectrophotometry (total polyphenols and tannins) and through antioxidant activity by 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) assay. The extractive solution was concentrated, added with drying adjuvant, and submitted to spouted bed drying. Product quality was evaluated by moisture content (Xp), water activity (aW), powder diameter, total polyphenols, and tannins content (PT and TT), and antioxidant activity, expressed as the extract concentration needed to reduce 50% of the DDPH radical (IC50). Spouted bed drying performance was evaluated through the drying yield (REC), product accumulation (Ac), and thermal efficiency (η). The optimal processing conditions were: inlet gas temperature, Tgi: 150°C, the ratio of the mass feed flow rate of the concentrated extract to the evaporation capacity of the dryer, Ws/Wmax: 45%, and the drying gas flow rate relative to minimum spouting, Q/Qms: 1.85. Under these conditions, it is predicted to obtain a dried extract with Xp = 4.9% w/w, PT = 26.0% w/w, REC = 77.7% w/w, η = 44.3%, and Ac = 10% w/w, with adequate values of aW, TT, and high antioxidant activity.
{"title":"Bioactive dry extract production from Hymenaea courbaril L. bark via spouted bed drying","authors":"C. R. Souza, Fabiana Fregonesi, Wanderley P. Oliveira","doi":"10.1002/cjce.25286","DOIUrl":"https://doi.org/10.1002/cjce.25286","url":null,"abstract":"The work aims to develop and optimize a powdered phytopharmaceutical product from the stem bark of Hymenaea courbaril L. (jatobá) by the spouted bed drying. The study commenced with the extraction of bioactive compounds present in the plant raw material by dynamic maceration using ethanol/water 70% (v/v) at a temperature of 50°C for 60 min, for the ratio stem bark: solvent mass of 1:10 (w/w). The extract quality was assessed by quantifying chemical markers via spectrophotometry (total polyphenols and tannins) and through antioxidant activity by 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) assay. The extractive solution was concentrated, added with drying adjuvant, and submitted to spouted bed drying. Product quality was evaluated by moisture content (Xp), water activity (aW), powder diameter, total polyphenols, and tannins content (PT and TT), and antioxidant activity, expressed as the extract concentration needed to reduce 50% of the DDPH radical (IC50). Spouted bed drying performance was evaluated through the drying yield (REC), product accumulation (Ac), and thermal efficiency (η). The optimal processing conditions were: inlet gas temperature, Tgi: 150°C, the ratio of the mass feed flow rate of the concentrated extract to the evaporation capacity of the dryer, Ws/Wmax: 45%, and the drying gas flow rate relative to minimum spouting, Q/Qms: 1.85. Under these conditions, it is predicted to obtain a dried extract with Xp = 4.9% w/w, PT = 26.0% w/w, REC = 77.7% w/w, η = 44.3%, and Ac = 10% w/w, with adequate values of aW, TT, and high antioxidant activity.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"56 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140677385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gustavo Petroli, Vitória Brocardo de Leon, Michele Di Domenico, Fernanda Batista de Souza, Claiton Zanini Brusamarello
Adsorption isotherms are valuable tools for describing the interaction between adsorbate and adsorbent since they demonstrate the equilibrium relationship. The Langmuir and Freundlich models are the most commonly used isotherm models to describe these relationships; still, they cannot consistently deliver efficient results due to the assumptions of the model not predicting more complex situations as occurs in biosorption. Artificial neural networks (ANN) are a set of algorithms modelled loosely after the human brain and are designed to recognize patterns. The ANN tool can overcome problems isotherm models have in describing the interactions mentioned and help define the best conditions for a given adsorption process. This paper reports the application of ANNs for predicting the removal efficiency of textile dye Neolan Black WA (Acid Black 52) using orange peel and sugarcane bagasse as biosorbents. The Freundlich, Langmuir, pseudo‐first‐order, and pseudo‐second‐order models were applied and compared to the ANN model. The parameters evaluated were initial dye concentration (10–600 mg/L), final dye concentration (0–83.44 mg/L), biosorbent mass (1.5 g), pH (2), and contact time of dye (0.167–24 h). Two classes of ANNs, Elman and feed‐forward networks, were tested with a mean square error of 0.0212 and 0.7274 for the isotherm and kinetics, respectively. Compared to the conventional isotherm and kinetic models, the Elman network predicted the amount adsorbed by the biosorbents with higher precision, acquiring a determination coefficient of 0.9998 and a mean square error of 8.75 × 10−5.
吸附等温线是描述吸附剂和吸附剂之间相互作用的重要工具，因为它们展示了平衡关系。朗缪尔模型和弗伦德里希模型是描述这些关系最常用的等温线模型；然而，由于模型的假设条件无法预测生物吸附中出现的更复杂情况，因此它们无法始终提供有效的结果。人工神经网络（ANN）是一套仿照人脑设计的算法，用于识别模式。人工神经网络工具可以克服等温线模型在描述上述相互作用时存在的问题，并帮助确定特定吸附过程的最佳条件。本文报告了应用 ANN 预测以橘皮和甘蔗渣为生物吸附剂的纺织染料 Neolan Black WA（酸性黑 52）的去除效率。应用了 Freundlich、Langmuir、伪一阶和伪二阶模型，并与 ANN 模型进行了比较。评估的参数包括初始染料浓度（10-600 毫克/升）、最终染料浓度（0-83.44 毫克/升）、生物吸附剂质量（1.5 克）、pH 值（2）和染料接触时间（0.167-24 小时）。测试了 Elman 和前馈网络两类 ANN，等温线和动力学的均方误差分别为 0.0212 和 0.7274。与传统的等温线和动力学模型相比，Elman 网络预测生物吸附剂吸附量的精度更高，其确定系数为 0.9998，均方误差为 8.75 × 10-5。
{"title":"Application of artificial neural networks and Langmuir and Freundlich isotherm models to the removal of textile dye using biosorbents: A comparative study among methodologies","authors":"Gustavo Petroli, Vitória Brocardo de Leon, Michele Di Domenico, Fernanda Batista de Souza, Claiton Zanini Brusamarello","doi":"10.1002/cjce.25271","DOIUrl":"https://doi.org/10.1002/cjce.25271","url":null,"abstract":"Adsorption isotherms are valuable tools for describing the interaction between adsorbate and adsorbent since they demonstrate the equilibrium relationship. The Langmuir and Freundlich models are the most commonly used isotherm models to describe these relationships; still, they cannot consistently deliver efficient results due to the assumptions of the model not predicting more complex situations as occurs in biosorption. Artificial neural networks (ANN) are a set of algorithms modelled loosely after the human brain and are designed to recognize patterns. The ANN tool can overcome problems isotherm models have in describing the interactions mentioned and help define the best conditions for a given adsorption process. This paper reports the application of ANNs for predicting the removal efficiency of textile dye Neolan Black WA (Acid Black 52) using orange peel and sugarcane bagasse as biosorbents. The Freundlich, Langmuir, pseudo‐first‐order, and pseudo‐second‐order models were applied and compared to the ANN model. The parameters evaluated were initial dye concentration (10–600 mg/L), final dye concentration (0–83.44 mg/L), biosorbent mass (1.5 g), pH (2), and contact time of dye (0.167–24 h). Two classes of ANNs, Elman and feed‐forward networks, were tested with a mean square error of 0.0212 and 0.7274 for the isotherm and kinetics, respectively. Compared to the conventional isotherm and kinetic models, the Elman network predicted the amount adsorbed by the biosorbents with higher precision, acquiring a determination coefficient of 0.9998 and a mean square error of 8.75 × 10<jats:sup>−5</jats:sup>.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Solid particles may experience different kinds of cohesive forces, which cause them to form agglomerates and affect their flow in multiphase systems. When such systems are simulated through computational fluid dynamics (CFD) programs, appropriate modelling tools must be included to reproduce this feature. In this review, these strategies are addressed for various systems and scales. After an introduction of the different forces (van der Waals, electrostatic, liquid bridge forces, etc.), the modelling approaches are categorized under three methodologies. For diluted slurries of very fine particles, many researchers succeeded with pseudo‐single phase approaches, employing a model for the non‐Newtonian rheology. This was especially popular for sludges in anaerobic digestions or certain types of soils. In other cases, continuum‐based approaches seem to be more adequate, including cohesiveness in the kinetic theory of granular flows or the restitution coefficient. Geldart‐A particles experiencing van der Waals forces are the primary focus of such studies. Finally, when each particle is modelled as a discrete element, the cohesive force can be directly specified; this is especially widespread for the wet fluidization case. For each of these approaches, a general overview of the main strategies, achievements, and limits is provided.
{"title":"Cohesive particle–fluid systems: An overview of their CFD simulation","authors":"Filippo Marchelli, Luca Fiori, Renzo Di Felice","doi":"10.1002/cjce.25269","DOIUrl":"https://doi.org/10.1002/cjce.25269","url":null,"abstract":"Solid particles may experience different kinds of cohesive forces, which cause them to form agglomerates and affect their flow in multiphase systems. When such systems are simulated through computational fluid dynamics (CFD) programs, appropriate modelling tools must be included to reproduce this feature. In this review, these strategies are addressed for various systems and scales. After an introduction of the different forces (van der Waals, electrostatic, liquid bridge forces, etc.), the modelling approaches are categorized under three methodologies. For diluted slurries of very fine particles, many researchers succeeded with pseudo‐single phase approaches, employing a model for the non‐Newtonian rheology. This was especially popular for sludges in anaerobic digestions or certain types of soils. In other cases, continuum‐based approaches seem to be more adequate, including cohesiveness in the kinetic theory of granular flows or the restitution coefficient. Geldart‐A particles experiencing van der Waals forces are the primary focus of such studies. Finally, when each particle is modelled as a discrete element, the cohesive force can be directly specified; this is especially widespread for the wet fluidization case. For each of these approaches, a general overview of the main strategies, achievements, and limits is provided.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fine particles possess remarkable characteristics including extensive surface-to-weight ratios and diverse morphologies. Consequently, through the use of fluidization techniques, they have become favoured in various industrial processes, especially with continuous production. This review paper offers a comprehensive exploration of the integration of fine particle applications with fluidization technologies, with a specific focus on the Geldart Group C particles sized <25–40 μm. Although there are challenges with processing fine particles such as the strong cohesion in fluidized beds, recent progress, including the nanoparticle modulation method, has demonstrated potential solutions. These advancements render these cohesive particles applicable to industrial applications in different fields, including gas-phase catalytic reactions, gas–solid fluidized bed coal beneficiation, ultrafine powder coating (UPC), pharmaceuticals, environmental sustainability, energy storage, and food processing. However, further research is needed to obtain a better understanding of fine particle fluidization in industrial settings in order to achieve larger-scale implementation. In summary, this review provides a comprehensive overview of fine particle utilization integrated with fluidization technologies, demonstrating the potential in large-scale industrial processes, and enabling significant advancements in practical applications.
细颗粒具有显著的特性，包括广泛的表面重量比和多样化的形态。因此，通过使用流化技术，它们在各种工业流程中，尤其是在连续生产中受到青睐。本综述论文全面探讨了细颗粒应用与流化技术的结合，重点关注尺寸为 25-40 μm 的 Geldart C 组颗粒。尽管在处理细颗粒方面存在挑战，例如流化床中的强内聚力，但包括纳米颗粒调制方法在内的最新进展已经证明了潜在的解决方案。这些进步使这些内聚微粒适用于不同领域的工业应用，包括气相催化反应、气固流化床选煤、超细粉末涂层（UPC）、制药、环境可持续发展、能源储存和食品加工。然而，为了更好地了解工业环境中的细颗粒流化，以实现更大规模的实施，还需要进一步的研究。总之，本综述全面概述了与流化技术相结合的细颗粒利用技术，展示了其在大规模工业流程中的潜力，并在实际应用中取得了重大进展。
{"title":"A review on applications of fine particles integrated with fluidization technologies","authors":"Yue Song, Yue Yuan, Jesse Zhu","doi":"10.1002/cjce.25260","DOIUrl":"https://doi.org/10.1002/cjce.25260","url":null,"abstract":"Fine particles possess remarkable characteristics including extensive surface-to-weight ratios and diverse morphologies. Consequently, through the use of fluidization techniques, they have become favoured in various industrial processes, especially with continuous production. This review paper offers a comprehensive exploration of the integration of fine particle applications with fluidization technologies, with a specific focus on the Geldart Group C particles sized <25–40 μm. Although there are challenges with processing fine particles such as the strong cohesion in fluidized beds, recent progress, including the nanoparticle modulation method, has demonstrated potential solutions. These advancements render these cohesive particles applicable to industrial applications in different fields, including gas-phase catalytic reactions, gas–solid fluidized bed coal beneficiation, ultrafine powder coating (UPC), pharmaceuticals, environmental sustainability, energy storage, and food processing. However, further research is needed to obtain a better understanding of fine particle fluidization in industrial settings in order to achieve larger-scale implementation. In summary, this review provides a comprehensive overview of fine particle utilization integrated with fluidization technologies, demonstrating the potential in large-scale industrial processes, and enabling significant advancements in practical applications.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi‐walled carbon nanotubes (MWCNTs) are an excellent hydrate promoter, with their own Brownian motion of nanoparticles effectively shortening hydrate nucleation and accelerating hydrate formation. In this work, the properties of methane hydrate formation in a complex system of MWCNTs, sodium dodecyl sulphate (SDS) and NaCl were investigated. It was shown that the compounding system effectively enhanced the kinetics of methane hydrate formation, and the gas consumption of the reaction reached 0.38 MPa at 100 ppm MWCNTs, an increase of 865.8% compared to the pure water system, effectively promoting methane hydrate. In the complexed system, NaCl significantly enhanced the dispersion of MWCNTs, with 1000 ppm NaCl showing the best kinetic promotion effect. SDS not only increases the gas–liquid contact area through the wall attachment effect, but also enhances the dispersion of MWCNTs by adsorbing on the surface of carbon nanotubes and forming an electronic layer with NaCl. MWCNTs not only improve the mass transfer of the system through Brownian motion, but their large heat transfer coefficients can also effectively conduct the heat generated by the system. However, MWCNTs become agglomerated with increasing concentration, making the kinetic promotion effect weaker and the solution less stable, resulting in shorter shelf life. This study confirmed the effective promotion of hydrate formation by MWCNTs under the ultrasonic compounding system, and also provided a reference for related studies on the compounding of MWCNTs with NaCl.
{"title":"Promotion of hydrate formation by multi‐walled carbon nanotubes in ultrasonic compounding system","authors":"Xianghan Du, Husheng Jiang, Liyan Shang","doi":"10.1002/cjce.25213","DOIUrl":"https://doi.org/10.1002/cjce.25213","url":null,"abstract":"Multi‐walled carbon nanotubes (MWCNTs) are an excellent hydrate promoter, with their own Brownian motion of nanoparticles effectively shortening hydrate nucleation and accelerating hydrate formation. In this work, the properties of methane hydrate formation in a complex system of MWCNTs, sodium dodecyl sulphate (SDS) and NaCl were investigated. It was shown that the compounding system effectively enhanced the kinetics of methane hydrate formation, and the gas consumption of the reaction reached 0.38 MPa at 100 ppm MWCNTs, an increase of 865.8% compared to the pure water system, effectively promoting methane hydrate. In the complexed system, NaCl significantly enhanced the dispersion of MWCNTs, with 1000 ppm NaCl showing the best kinetic promotion effect. SDS not only increases the gas–liquid contact area through the wall attachment effect, but also enhances the dispersion of MWCNTs by adsorbing on the surface of carbon nanotubes and forming an electronic layer with NaCl. MWCNTs not only improve the mass transfer of the system through Brownian motion, but their large heat transfer coefficients can also effectively conduct the heat generated by the system. However, MWCNTs become agglomerated with increasing concentration, making the kinetic promotion effect weaker and the solution less stable, resulting in shorter shelf life. This study confirmed the effective promotion of hydrate formation by MWCNTs under the ultrasonic compounding system, and also provided a reference for related studies on the compounding of MWCNTs with NaCl.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"7 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. K. Singh, Deb Mukhopadhyay, D. Khakhar, J. B. Joshi
Turbulent mixing within sub‐channels plays a crucial role in understanding the thermal hydraulics of reactor channels. It serves as an empirical parameter in sub‐channel analysis and has long been a challenge in the nuclear industry. Conducting experiments in this context is challenging due to the stringent requirement of maintaining pressure balance among sub‐channels to prevent convection effects. Fortunately, direct numerical simulation (DNS) is emerging as an invaluable tool for addressing this persistent issue. DNS enables the direct computation of turbulent mixing by analyzing fluctuating lateral velocities, offering a more profound understanding of the underlying phenomena. In this study, DNS was conducted at six Reynolds numbers ranging from 17,640 to 1.5 × 105 in pressurized water reactor (PWR) geometry to investigate the lateral mixing driven by turbulence. By studying intricate mechanisms governing the turbulent mixing, the valuable insights into reactor thermal performance and safety are provided. Furthermore, a correlation for turbulent mixing of energy based on the DNS data has been derived, enhancing our ability to model and predict this critical aspect of reactor behaviour. Additionally, this paper explores temperature fluctuations occurring at the fuel rod surface due to turbulence. A probabilistic distribution for temperature fluctuation under specific reactor conditions is presented.
{"title":"Estimation of turbulent energy mixing factor in PWR sub‐channel by DNS","authors":"R. K. Singh, Deb Mukhopadhyay, D. Khakhar, J. B. Joshi","doi":"10.1002/cjce.25204","DOIUrl":"https://doi.org/10.1002/cjce.25204","url":null,"abstract":"Turbulent mixing within sub‐channels plays a crucial role in understanding the thermal hydraulics of reactor channels. It serves as an empirical parameter in sub‐channel analysis and has long been a challenge in the nuclear industry. Conducting experiments in this context is challenging due to the stringent requirement of maintaining pressure balance among sub‐channels to prevent convection effects. Fortunately, direct numerical simulation (DNS) is emerging as an invaluable tool for addressing this persistent issue. DNS enables the direct computation of turbulent mixing by analyzing fluctuating lateral velocities, offering a more profound understanding of the underlying phenomena. In this study, DNS was conducted at six Reynolds numbers ranging from 17,640 to 1.5 × 105 in pressurized water reactor (PWR) geometry to investigate the lateral mixing driven by turbulence. By studying intricate mechanisms governing the turbulent mixing, the valuable insights into reactor thermal performance and safety are provided. Furthermore, a correlation for turbulent mixing of energy based on the DNS data has been derived, enhancing our ability to model and predict this critical aspect of reactor behaviour. Additionally, this paper explores temperature fluctuations occurring at the fuel rod surface due to turbulence. A probabilistic distribution for temperature fluctuation under specific reactor conditions is presented.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"138 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139859678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Process monitoring is pivotal in process system engineering for abnormal situation management and ensuring process safety. This paper presents a review of Professor Khan's works on process monitoring. It examines (i) the number of publications, (ii) the type of publications, (iii) key sources, (iv) focused areas and their evolvement, and (v) the research impact by Professor Khan in process monitoring. The results suggest that journals are the primary sources he has used to disseminate research results. Over the years, his research focus evolved from detection to root cause diagnosis, fault propagation pathway analysis, and failure prognosis. Professor Khan has immensely impacted his peers, evidenced by his theoretical contributions, a higher number of recognitions by other researchers, and diversified workforce development.
{"title":"A review of Faisal Khan's contribution to process monitoring","authors":"Md. Tanjin Amin, Yutian Qian","doi":"10.1002/cjce.25206","DOIUrl":"https://doi.org/10.1002/cjce.25206","url":null,"abstract":"Process monitoring is pivotal in process system engineering for abnormal situation management and ensuring process safety. This paper presents a review of Professor Khan's works on process monitoring. It examines (i) the number of publications, (ii) the type of publications, (iii) key sources, (iv) focused areas and their evolvement, and (v) the research impact by Professor Khan in process monitoring. The results suggest that journals are the primary sources he has used to disseminate research results. Over the years, his research focus evolved from detection to root cause diagnosis, fault propagation pathway analysis, and failure prognosis. Professor Khan has immensely impacted his peers, evidenced by his theoretical contributions, a higher number of recognitions by other researchers, and diversified workforce development.","PeriodicalId":501204,"journal":{"name":"The Canadian Journal of Chemical Engineering","volume":"64 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139799986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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