Alejandro Romero, Joe Villa-Medina, Jorge Ropero, Néstor Cubillán
{"title":"Moisture content determination along production line of ibuprofen soft gelatin capsule manufacturing by near infrared spectroscopy and ensemble deep neural networks","authors":"Alejandro Romero, Joe Villa-Medina, Jorge Ropero, Néstor Cubillán","doi":"10.1002/cjce.25496","DOIUrl":"https://doi.org/10.1002/cjce.25496","url":null,"abstract":"<p>In the manufacturing process of ibuprofen soft gelatin capsules, controlling moisture content at each production line stage, including in their components—gelatin, fill content, and shell—is vital to ensure quality and stability. This study developed and assessed an analytical method for rapid and non-destructive moisture determination using near-infrared spectroscopy (NIRS) coupled with deep neural networks (DNN) on all stages of the ibuprofen production line. The NIRS-DNN classifier models were able to distinguish between the three components, achieving accuracy scores of up to 99%. The DNN models for moisture quantification also demonstrated high accuracy, with <i>R</i><sup>2</sup> values exceeding 0.997 across all production stages and prediction errors to those of previously reported models. A significant advantage of the NIRS-DNN approach was its ability to maintain accuracy over a wide moisture concentration range, from 7% to 48%. The ensemble model, NIRS-EDNN, seamlessly integrated classification and quantification, revealing its potential for real-time process control in soft gel manufacturing. The comprehensive sampling approach ensured a diverse representation of moisture content, thereby enhancing the understanding of its impact on the final product stability, demonstrating that this methodology is potentially applicable to any soft gelatin capsule tracking worldwide.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2251-2262"},"PeriodicalIF":1.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigation on the influence of particle size and porosity on solid phase fluidization and heat transfer in carbon fibre porous media","authors":"Licheng Wang, Wenwen Zhang, Zhouzhe Yang","doi":"10.1002/cjce.25511","DOIUrl":"https://doi.org/10.1002/cjce.25511","url":null,"abstract":"<p>In this paper, the 3D pore structure was reconstructed and solid phase fluidization in porous media was investigated. Based on the two fluid model, a computational fluid dynamics (CFD) model of gas–solid fluidization was established and the influence of particle size and porosity were investigated. When porosity was constant, during the fluidization process, the particle velocity and solid concentration standard deviation gradually decreased, and the bed height increased. At the same time, the smaller the particle size was, the smaller the solid concentration standard deviation was, the faster the bed height increased, and the more the particle temperature decreased. Based on the fixed value of particle size, when studying the effect of porosity on fluidization, it was found that with the enhancement of solid-phase fluidization, particle velocity, solid concentration standard deviation, and particle temperature decreased, and bed height increased. Moreover, when porosity was large, particle velocity decreased rapidly, and solid concentration standard deviation reached a smaller minimum value, which took a longer time. Within the same time, the particle temperature also decreased less.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2412-2425"},"PeriodicalIF":1.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengfei Zhou, Ruizhen Wang, Rong Cheng, Qin Sun, Qiqing Yu, Luyue Xia, Xiaofang Sun
{"title":"A physics-constrained hybrid residual neural network for the prediction of moisture content in a closed-cycle drying system","authors":"Mengfei Zhou, Ruizhen Wang, Rong Cheng, Qin Sun, Qiqing Yu, Luyue Xia, Xiaofang Sun","doi":"10.1002/cjce.25516","DOIUrl":"https://doi.org/10.1002/cjce.25516","url":null,"abstract":"<p>Closed-cycle drying technology has the advantages of safety, energy saving, and environmental protection, and has a wide application prospect. Due to the multi-physics and multi-scale nature of heat/mass transfer in the closed-cycle drying process, as well as the characteristics of drying medium circulation and energy integration, it is difficult to obtain the product moisture content prediction model in closed-cycle process based on rigorous closed-cycle drying process mechanism model. However, accurate monitoring of product moisture content in the closed-cycle drying process is the key to improving drying quality and process optimization. Aiming at the challenges in predicting moisture content, this paper proposes a physics-constrained hybrid residual neural network (PC-HRNN) for soft sensor modelling within a designed closed-cycle drying system. The characteristic of this proposed method lies in its effective fusion of physics, knowledge, and data. First, a hybrid residual neural network (HRNN) is constructed based on the integration of a physics model and a data-driven model. The HRNN takes the knowledge from the physics model as its auxiliary features and learns the prediction residuals of the physics model through a neural network model. Then, a new loss function that takes into account physical laws is introduced into HPNN to standardize model training and improve the generalization performance of the model. The experimental results show that the PC-HRNN model improves prediction accuracy and model robustness, reduces the demand for data, and demonstrates stronger extrapolation capabilities under limited data.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2204-2217"},"PeriodicalIF":1.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicky Rahmana Putra, Muhammad Abbas Ahmad Zaini, Ahmad Syahmi Zaini, Bramantyo Airlangga, Dwila Nur Rizkiyah, Heri Septya Kusuma, Sri Agustini, Syahrial Abdullah, Yustisia Yustisia, Izhar Khairullah, I. Gusti Komang Dana Arsana
{"title":"Evaluating the efficacy of palm waste in adsorption processes for wastewater treatment: A review","authors":"Nicky Rahmana Putra, Muhammad Abbas Ahmad Zaini, Ahmad Syahmi Zaini, Bramantyo Airlangga, Dwila Nur Rizkiyah, Heri Septya Kusuma, Sri Agustini, Syahrial Abdullah, Yustisia Yustisia, Izhar Khairullah, I. Gusti Komang Dana Arsana","doi":"10.1002/cjce.25515","DOIUrl":"https://doi.org/10.1002/cjce.25515","url":null,"abstract":"<p>The growing environmental concerns related to industrial effluents and waste underscore the urgent need for sustainable and cost-effective wastewater treatment solutions. This review investigates the efficacy of palm waste-derived adsorbents for removing heavy metals and organic pollutants from wastewater. It explores various modifications—including physical, chemical, and nanomaterial enhancements—applied to palm waste materials such as palm kernel shells, empty fruit bunches, and palm oil fuel ash, aimed at improving their adsorption capacities. The review reveals that these modified palm waste adsorbents demonstrate high removal efficiencies for contaminants like Cu(II), Pb(II), and organic dyes, often surpassing conventional adsorbents. Nonetheless, challenges remain, such as optimizing adsorbent preparation, understanding adsorption mechanisms in multi-component systems, and enhancing adsorbent reusability. This review highlights the need for continued research to address these issues and advance the application of palm waste-based materials in sustainable wastewater treatment.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2088-2106"},"PeriodicalIF":1.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of sparse nonlinear controlled variables for near-optimal operation of chemical processes","authors":"Xie Ma, Hongwei Guan, Lingjian Ye","doi":"10.1002/cjce.25514","DOIUrl":"https://doi.org/10.1002/cjce.25514","url":null,"abstract":"<p>For optimal operation of chemical processes, the selection of controlled variables plays an important role. A previous proposal is to approximate the necessary conditions of optimality (NCO) as the controlled variables, such that process optimality is automatically maintained by tracking constant zero setpoints. In this paper, we extend the NCO approximation method by identifying sparse nonlinear controlled variables, motivated by the fact that simplicity is always favoured for practical implementations. To this end, the <span></span><math>\u0000 <msub>\u0000 <mi>l</mi>\u0000 <mn>1</mn>\u0000 </msub></math>-regularization is employed to approximate the NCO, such that the controlled variables are maintained simple, even they are specified as nonlinear functions. The sparse controlled variables are solved using the proximal gradient method, implemented within a tailored Adam algorithm. Two case studies are provided to illustrate the proposed approach.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2281-2296"},"PeriodicalIF":1.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling and parameter identification of penicillin fermentation using physics-informed neural networks","authors":"Siqi Zhao, Zhonggai Zhao, Fei Liu","doi":"10.1002/cjce.25510","DOIUrl":"https://doi.org/10.1002/cjce.25510","url":null,"abstract":"<p>With the rapid development of machine learning technology and computer science, artificial neural networks have become an effective and popular method in the existing modelling research of penicillin fermentation process. Although these networks can capture the complexity of the fermentation process, they may lead to overfitting and require large amounts of data. In addition, the inference of the model on the data may not satisfy the physical laws. In this paper, a penicillin fermentation modelling method based on physics-informed neural networks is proposed. The fermentation mechanism equations are combined with the neural networks to develop the model as constraints. First, a general penicillin fermentation mechanism model is built according to known prior knowledge, and then its unknown nonlinear dynamic parameters are identified by physics-informed neural networks. Finally, the successfully trained model exhibits a high prediction accuracy, which not only satisfies the physical laws in the loss function, but also verifies the effectiveness of the proposed mechanism model.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"1965-1977"},"PeriodicalIF":1.6,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143836413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wan Nur Aisyah Wan Osman, Jonathan Khoo Lee Min, Shafirah Samsuri
{"title":"Analysis of chemical properties for biodiesel derived from crude palm oil","authors":"Wan Nur Aisyah Wan Osman, Jonathan Khoo Lee Min, Shafirah Samsuri","doi":"10.1002/cjce.25501","DOIUrl":"https://doi.org/10.1002/cjce.25501","url":null,"abstract":"<p>High biodiesel purity (98.86% to 99.54%) has been achieved using cooking oil, which undergoes various purification stages before being sold. This inherent purity contributes to the high biodiesel purity produced during solvent-aided crystallization (SAC). This study aims to investigate the performance of SAC using unpurified oil as the feedstock for crude biodiesel preparation. Crude palm oil (CPO) was used as the feedstock, and the effects of crystallization temperature (6, 8, 10, 12, and 14°C), crystallization time (20, 25, 30, 35, and 40 min), and shaking speed (32, 43, 61, 71, and 84 rpm) were measured. The highest biodiesel purity achieved was 99.05% at 6°C crystallization temperature, 30 min crystallization time, and medium shaking speed. Additionally, all samples met international standards EN 14214 and ASTM D6751 for chemical properties, including iodine and acid value analysis. These results suggest that SAC is an effective method for producing high-quality biodiesel from less refined feedstock, potentially lowering production costs and expanding the range of viable raw materials for biodiesel production.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2053-2065"},"PeriodicalIF":1.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143836377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carine Menezes Rebello, Erbet Almeida Costa, Antonio Santos Sánchez, Fredy Vides, Idelfonso B. R. Nogueira
{"title":"Assuring optimality in surrogate-based optimization: A novel theorem and its practical implementation in pressure swing adsorption optimization","authors":"Carine Menezes Rebello, Erbet Almeida Costa, Antonio Santos Sánchez, Fredy Vides, Idelfonso B. R. Nogueira","doi":"10.1002/cjce.25512","DOIUrl":"https://doi.org/10.1002/cjce.25512","url":null,"abstract":"<p>Surrogate-based optimization has gained significant traction in several engineering fields, given its ability to handle complex systems without significant computational burdens. However, surrogate models are approximations and may have limitations, including the possibility of artificial minima. The main contribution of this work is the derivation of a robustness test that guarantees the optimality of surrogate-based optimization. The derivation of this metric is based on the universal approximation theorem. The full framework proposed in this work is also composed by a sampling sizing methodology to randomly select samples within a feasible operating region (FOR) resulting from the optimization population, reducing the computational cost of the analysis and avoiding biases in the robustness calculation. The applicability and importance of this methodology are demonstrated through a case study of a complex chemical process—a pressure swing adsorption (PSA) unit—which presents a high computational cost to solve optimization problems. The results highlight the need and importance of evaluating the optimality of surrogate-based optimization schemes.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 3","pages":"1036-1059"},"PeriodicalIF":1.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjce.25512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Facile synthesis of zeolitic-imidazole framework-67 (ZIF-67) for the adsorption of indigo carmine dye","authors":"Duygu Yanardag Kola, Serpil Edebali","doi":"10.1002/cjce.25503","DOIUrl":"https://doi.org/10.1002/cjce.25503","url":null,"abstract":"<p>This study aims to synthesize ZIF-67 for the adsorption of indigo carmine (I.C.) dye. ZIF-67 materials were synthesized under different conditions and the synthesis condition of ZIF-67 giving the best adsorption efficiency was obtained. In batch adsorption studies, pH, adsorbent amount, contact time, initial dye concentration, and temperature effects were investigated. Adsorption data were applied to Langmuir, Freundlich, and Temkin isotherm models. The best correlation value was obtained in Langmuir isotherm (<i>R</i><sup>2</sup> = 0.999). The adsorption of I.C. dye with ZIF-67 occurred in a monolayer with a homogeneous surface according to Langmuir isotherm. The highest adsorption capacity value of ZIF-67 metal–organic framework for I.C. dye was found as 370 mg/g. Kinetic model studies were also performed and pseudo first-order, pseudo second-order, and intraparticle diffusion models were used. Pseudo second-order was the best fitting kinetic model to the data (<i>R</i><sup>2</sup> = 0.997). Adsorption mechanisms of ZIF-67 for I.C. dye include electrostatic interaction, π–π interaction, and hydrogen bonding. Thermodynamic studies showed that I.C. removal by ZIF-67 is an exothermic and spontaneous process. ZIF-67 was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscope (FE-SEM), and N<sub>2</sub> adsorption–desorption. The surface area of synthesized ZIF-67 was found 1493 m<sup>2</sup> g<sup>−1</sup>. The salt concentration effect on I.C. adsorption by ZIF-67 was also investigated, showing an increase in adsorption capacities with increasing salt concentration. The regeneration study was carried out and after 5 cycles, the reduction in efficiency was 21%.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 5","pages":"2373-2385"},"PeriodicalIF":1.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143836378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying design criteria for implementing inherent safety in chemical process industries part 2: Design mechanism","authors":"Zafirah Zakaria, Kamarizan Kidam, Mimi H. Hassim","doi":"10.1002/cjce.25497","DOIUrl":"https://doi.org/10.1002/cjce.25497","url":null,"abstract":"<p>Inherent safety concepts are common knowledge today, but accidents with similar characteristics do recur. Research on accident causes found that design errors, especially equipment failure, contribute the highest percentage of accidents. The development of inherent safety tools has been increasing at a positive pace, but only a small number of these tools are applicable to equipment design. Ample amounts of inherent safety tools are only suitable to be used at the early design stage. This amplifies the fact that inherent safety tools are still conceptual (e.g., change process routes, change safer materials). This is in contrast to the circumstances, where tools are expected to reinforce the inherent safety of equipment. The objective of this research is to identify design mechanism that can help trigger design thinking for implementation of inherent safety in the chemical process industry. To identify such a design mechanism, 526 cases were collected, and knowledge of the mechanism was extracted from design changes and presented in this research paper. The mechanisms were classified according to equipment and inherent safety keywords. The significant design mechanisms from the overall summation were listed (turbulence, change heat transfer fluid, continuous removal, large surface area, corrosion resistance, seamless joint, thin film, dividing wall, on demand, and double wall).</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 1","pages":"63-81"},"PeriodicalIF":1.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}