This study investigates the feasibility of directly applying the CO2 self-circulation calcination process in existing furnaces. A CFD model based on the Euler-Lagrange framework was employed to analyze the effects of CO2 gas temperature, gas flow rate, feeding rate, and magnesite preheating temperature on decomposition extent and energy consumption. By combining the response surface methodology (RSM) and the NSGA-II algorithm, multi-objective parameter optimization was conducted to maximize production capacity and minimize energy consumption. Results indicate that applying the new process necessitates a reduction in production capacity. A strategy combining high CO2 and magnesite temperatures with low gas flow rates is recommended. The optimized production capacity ranges from 0.85 kg/s to 1.02 kg/s, with energy consumption between 1.81 × 106 and 2.36 × 106 kcal/t. The gas-solid mass ratio and gas-solid water equivalent ratio should be maintained above 2.5 and 3.0, respectively. Furthermore, compared to conventional processes, directly applying the CO2 self-circulation process reduces production capacity by at least 26.6 % and increases energy consumption by at least 40.6 %. This study highlights the costs and limitations of directly adapting existing equipment to the new process, providing theoretical and data support for subsequent process optimization and equipment design.
{"title":"Optimization of operating parameters in a CO₂ self-circulation magnesite flash calciner based on CFD and NSGA-II","authors":"Daokuan Cheng , Hanlu Xu , Xichen Han , Liang Zhao , Hui Dong , Zhijun Zhang , Mingming Li , Jinhui Zhang","doi":"10.1016/j.cherd.2026.02.018","DOIUrl":"10.1016/j.cherd.2026.02.018","url":null,"abstract":"<div><div>This study investigates the feasibility of directly applying the CO<sub>2</sub> self-circulation calcination process in existing furnaces. A CFD model based on the Euler-Lagrange framework was employed to analyze the effects of CO<sub>2</sub> gas temperature, gas flow rate, feeding rate, and magnesite preheating temperature on decomposition extent and energy consumption. By combining the response surface methodology (RSM) and the NSGA-II algorithm, multi-objective parameter optimization was conducted to maximize production capacity and minimize energy consumption. Results indicate that applying the new process necessitates a reduction in production capacity. A strategy combining high CO<sub>2</sub> and magnesite temperatures with low gas flow rates is recommended. The optimized production capacity ranges from 0.85 kg/s to 1.02 kg/s, with energy consumption between 1.81 × 10<sup>6</sup> and 2.36 × 10<sup>6</sup> kcal/t. The gas-solid mass ratio and gas-solid water equivalent ratio should be maintained above 2.5 and 3.0, respectively. Furthermore, compared to conventional processes, directly applying the CO<sub>2</sub> self-circulation process reduces production capacity by at least 26.6 % and increases energy consumption by at least 40.6 %. This study highlights the costs and limitations of directly adapting existing equipment to the new process, providing theoretical and data support for subsequent process optimization and equipment design.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 718-728"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384989","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: 2026-01-29DOI: 10.1016/j.cherd.2026.01.046
Lijuan Shi , Tian Wang , Alexander Shapiro
Salt precipitation during CO2 injection into saline reservoirs poses a major challenge to maintaining injectivity and long-term storage security. Yet its pore-scale dynamics remains poorly understood. We combine a high-resolution microscope imaging system (MIS) and a full-field imaging system (FFIS) to investigate how multiphase flow conditions govern salt formation in a microfluidic glass model. MIS reveals two distinct morphologies: compact, transparent crystals that develop in brine-rich regions near brine-CO₂ interfaces, and dark, porous aggregates that dominate gas-rich regions. Graphical analysis shows that porous aggregates grow roughly six times faster than compact crystals. FFIS captures the evolution of residual-brine fields during CO₂ invasion and links salt accumulation with the spatial distribution of trapped brine. At low injection rate, CO2 first advanced with a relatively smooth front followed by instability and localized brine trapping near the outlet. At higher rates, the displacement became unstable and finger-like, causing earlier breakthrough and more dispersed brine retention. Replicated experiments confirmed the stochastic nature of the displacement process. The combined MIS–FFIS approach uniquely enables both (i) pore-scale tracking of salt-growth dynamics within individual regions and (ii) chip-scale monitoring of the evolving brine field during CO₂ invasion. This dual-scale capability allows simultaneous visualization of salt-growth kinetics and residual-brine evolution, important for understanding and planning CO2 storage.
含盐油藏注二氧化碳过程中的盐沉淀对维持注入能力和长期储存安全性构成了重大挑战。然而，人们对其孔隙尺度动力学仍然知之甚少。我们结合高分辨率显微镜成像系统（MIS）和全场成像系统（FFIS）来研究多相流条件如何影响微流控玻璃模型中盐的形成。MIS揭示了两种不同的形态：致密、透明的晶体，在靠近盐水- co 2界面的富盐水区域发育；深色、多孔的聚集体，在富气区占主导地位。图形分析表明，多孔聚集体的生长速度大约是致密晶体的6倍。FFIS捕捉了CO 2入侵过程中剩余盐水场的演化，并将盐的富集与捕获盐水的空间分布联系起来。在低注入速率下，CO2首先以相对平滑的锋面推进，随后是不稳定的，并在出口附近局部捕获盐水。在较高的速率下，驱替变得不稳定，呈手指状，导致更早的突破和更分散的盐水潴留。重复实验证实了位移过程的随机性。miss - ffis联合方法能够在孔隙尺度上跟踪单个区域内的盐生长动态，以及在CO₂侵入过程中对盐水场的演变进行芯片尺度的监测。这种双尺度能力允许同时可视化盐生长动力学和残余盐水演化，这对于理解和规划二氧化碳储存非常重要。
{"title":"Investigation of salt precipitation under CO2-brine displacement in micromodels","authors":"Lijuan Shi , Tian Wang , Alexander Shapiro","doi":"10.1016/j.cherd.2026.01.046","DOIUrl":"10.1016/j.cherd.2026.01.046","url":null,"abstract":"<div><div>Salt precipitation during CO<sub>2</sub> injection into saline reservoirs poses a major challenge to maintaining injectivity and long-term storage security. Yet its pore-scale dynamics remains poorly understood. We combine a high-resolution microscope imaging system (MIS) and a full-field imaging system (FFIS) to investigate how multiphase flow conditions govern salt formation in a microfluidic glass model. MIS reveals two distinct morphologies: compact, transparent crystals that develop in brine-rich regions near brine-CO₂ interfaces, and dark, porous aggregates that dominate gas-rich regions. Graphical analysis shows that porous aggregates grow roughly six times faster than compact crystals. FFIS captures the evolution of residual-brine fields during CO₂ invasion and links salt accumulation with the spatial distribution of trapped brine. At low injection rate, CO<sub>2</sub> first advanced with a relatively smooth front followed by instability and localized brine trapping near the outlet. At higher rates, the displacement became unstable and finger-like, causing earlier breakthrough and more dispersed brine retention. Replicated experiments confirmed the stochastic nature of the displacement process. The combined MIS–FFIS approach uniquely enables both (i) pore-scale tracking of salt-growth dynamics within individual regions and (ii) chip-scale monitoring of the evolving brine field during CO₂ invasion. This dual-scale capability allows simultaneous visualization of salt-growth kinetics and residual-brine evolution, important for understanding and planning CO<sub>2</sub> storage.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 279-296"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171270","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: 2026-02-02DOI: 10.1016/j.cherd.2026.02.003
Xuefang Gao , Dewu Wang , Yan Liu , Ruojin Wang , Baisong Hu , Lei Wang , Hongrui Wei , Shaofeng Zhang , Meng Tang
Fluid mixing plays a significant role in the mass transfer process. Static mixers are core insert elements in the mixing industry. The relationship between the vortex evolution induced by the perforated structures and the resultant chaotic mixing performance in a rotational–perforated static mixer (RPSM) remains to be quantitatively elucidated. To elucidate the impact of perforated structures on chaotic mixing, we employed Planar Laser Induced Fluorescence (PLIF) to visualize the vortex evolution in RPSMs under different installations. The transient and spatial development of vortices was traced using optical flow and edge detection algorithms, while the mixing performance was assessed by the coefficient of variation (CoV) and the largest Lyapunov exponent (LLE). It was found that the perforated structures promoted rotational strengthening in the central area and periodic near-wall vortex changes; however, a larger aperture ratio adversely affected mixing. The outer ring area exhibited superior mixing performance to the center. The backward installation conferred a significant advantage, reducing the CoV by 11–56 % compared to the forward installation. Subsequent factors analysis enabled the calculation of CoV, and the close agreement (relative error < 15 %) between calculated and experimental values validated the findings.
{"title":"Experimental study of vortex evolution process and chaotic mixing analysis of rotational–perforated static mixers with different perforated structures","authors":"Xuefang Gao , Dewu Wang , Yan Liu , Ruojin Wang , Baisong Hu , Lei Wang , Hongrui Wei , Shaofeng Zhang , Meng Tang","doi":"10.1016/j.cherd.2026.02.003","DOIUrl":"10.1016/j.cherd.2026.02.003","url":null,"abstract":"<div><div>Fluid mixing plays a significant role in the mass transfer process. Static mixers are core insert elements in the mixing industry. The relationship between the vortex evolution induced by the perforated structures and the resultant chaotic mixing performance in a rotational–perforated static mixer (RPSM) remains to be quantitatively elucidated. To elucidate the impact of perforated structures on chaotic mixing, we employed Planar Laser Induced Fluorescence (PLIF) to visualize the vortex evolution in RPSMs under different installations. The transient and spatial development of vortices was traced using optical flow and edge detection algorithms, while the mixing performance was assessed by the coefficient of variation (<em>CoV</em>) and the largest Lyapunov exponent (<em>LLE</em>). It was found that the perforated structures promoted rotational strengthening in the central area and periodic near-wall vortex changes; however, a larger aperture ratio adversely affected mixing. The outer ring area exhibited superior mixing performance to the center. The backward installation conferred a significant advantage, reducing the <em>CoV</em> by 11–56 % compared to the forward installation. Subsequent factors analysis enabled the calculation of <em>CoV</em>, and the close agreement (relative error < 15 %) between calculated and experimental values validated the findings.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 416-434"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171271","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: 2026-02-05DOI: 10.1016/j.cherd.2026.01.066
Achu Govind K.R.
Precise thermal regulation of rotary kilns is essential for maintaining product quality and energy efficiency in ZnO production. However, the strong nonlinear dynamics, distributed thermal behavior, and persistent disturbances in kiln operation pose significant challenges to conventional control strategies. These difficulties are compounded by model uncertainty, actuator limitations, and long-term drift in process characteristics. To address these issues, this work proposes a hybrid Active Disturbance Rejection Control (ADRC) with Long Short-Term Memory (LSTM) control framework. This integrates the robustness of ADRC with a data-driven residual correction learned by an LSTM network. The extended state observer (ESO) provides real-time disturbance estimation, while the LSTM compensates for unmodeled dynamics and estimator bias. The controller is designed to remain computationally lightweight and compatible with industrial implementation. A comprehensive evaluation is conducted, including an ablation study, parameter-uncertainty tests, gain-sensitivity analysis, actuator-fault simulations, Monte Carlo robustness assessment, and Lyapunov-based stability verification. The results show that the proposed ADRC-LSTM controller significantly improves transient and steady-state performance compared with nominal ADRC and a nonlinear MPC baseline. The hybrid controller achieves faster disturbance recovery, reduced undershoot, and smoother actuator usage. Robustness is maintained under -20% parameter variations and gain perturbations, and the system exhibits stable behavior under noise, actuator degradation, and fault conditions. Monte Carlo analysis confirms consistent closed-loop performance, while Lyapunov analysis verifies satisfaction of stability conditions. Overall, the proposed architecture provides a reliable, efficient, and fault-tolerant solution for advanced rotary-kiln temperature control.
{"title":"Learning-assisted active disturbance rejection control for robust temperature regulation of industrial rotary kilns","authors":"Achu Govind K.R.","doi":"10.1016/j.cherd.2026.01.066","DOIUrl":"10.1016/j.cherd.2026.01.066","url":null,"abstract":"<div><div>Precise thermal regulation of rotary kilns is essential for maintaining product quality and energy efficiency in ZnO production. However, the strong nonlinear dynamics, distributed thermal behavior, and persistent disturbances in kiln operation pose significant challenges to conventional control strategies. These difficulties are compounded by model uncertainty, actuator limitations, and long-term drift in process characteristics. To address these issues, this work proposes a hybrid Active Disturbance Rejection Control (ADRC) with Long Short-Term Memory (LSTM) control framework. This integrates the robustness of ADRC with a data-driven residual correction learned by an LSTM network. The extended state observer (ESO) provides real-time disturbance estimation, while the LSTM compensates for unmodeled dynamics and estimator bias. The controller is designed to remain computationally lightweight and compatible with industrial implementation. A comprehensive evaluation is conducted, including an ablation study, parameter-uncertainty tests, gain-sensitivity analysis, actuator-fault simulations, Monte Carlo robustness assessment, and Lyapunov-based stability verification. The results show that the proposed ADRC-LSTM controller significantly improves transient and steady-state performance compared with nominal ADRC and a nonlinear MPC baseline. The hybrid controller achieves faster disturbance recovery, reduced undershoot, and smoother actuator usage. Robustness is maintained under <span><math><mrow><mo>±</mo><mn>10</mn></mrow></math></span>-20% parameter variations and <span><math><mrow><mo>±</mo><mn>20</mn><mtext>%</mtext></mrow></math></span> gain perturbations, and the system exhibits stable behavior under noise, actuator degradation, and fault conditions. Monte Carlo analysis confirms consistent closed-loop performance, while Lyapunov analysis verifies satisfaction of stability conditions. Overall, the proposed architecture provides a reliable, efficient, and fault-tolerant solution for advanced rotary-kiln temperature control.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 400-415"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171262","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 absence of reliable online sensors for substrate () and ethanol () concentrations remains a critical limitation in industrial ethanol fermentation. An energy-balance-based soft sensor was developed to estimate and using temperature and water flow data in combination with thermodynamic and stoichiometric parameters. The model was calibrated under non-stripping fed-batch conditions at 34 °C, yielding a heat yield coefficient () of 0.0946 g kJ−1 (corresponding to a heat generation per gram of biomass of = 10.57 kJ g−1), an ethanol yield coefficient () of 0.463 ± 0.024 g ethanol (g TRS)−1, and a biomass yield coefficient () of 0.0451 ± 0.0039 g biomass (g TRS)−1. Validation in fermentations under distinct operational conditions, including extractive CO2 stripping and very high gravity (VHG) feeding, confirmed high predictive accuracy. Coefficients of determination (R²) exceeded 0.98 and mean absolute percentage errors (MAPE) remained below 8 %. These results demonstrate that the proposed framework provides a reliable basis for real-time estimation of substrate and ethanol concentrations under anaerobic conditions.
{"title":"Heat balance soft sensor for ethanol and substrate monitoring in very high gravity fed-batch fermentations with CO2 stripping","authors":"V.T. Mazziero , I.I.K. Veloso , B.G. Campos , M.V. Santos , A.J.G. Cruz , A.C. Badino , M.O. Cerri","doi":"10.1016/j.cherd.2026.01.064","DOIUrl":"10.1016/j.cherd.2026.01.064","url":null,"abstract":"<div><div>The absence of reliable online sensors for substrate (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>S</mi></mrow></msub></math></span>) and ethanol (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>E</mi></mrow></msub></math></span>) concentrations remains a critical limitation in industrial ethanol fermentation. An energy-balance-based soft sensor was developed to estimate <span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>S</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>E</mi></mrow></msub></math></span> using temperature and water flow data in combination with thermodynamic and stoichiometric parameters. The model was calibrated under non-stripping fed-batch conditions at 34 °C, yielding a heat yield coefficient (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mi>H</mi></mrow></msub></math></span>) of 0.0946 g kJ<sup>−1</sup> (corresponding to a heat generation per gram of biomass <span><math><msub><mrow><mi>Y</mi></mrow><mrow><mrow><mi>Q</mi></mrow><mo>/</mo><mrow><mi>X</mi></mrow></mrow></msub></math></span> of = 10.57 kJ g<sup>−1</sup>), an ethanol yield coefficient (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mrow><mi>E</mi></mrow><mo>/</mo><mrow><mi>S</mi></mrow></mrow></msub></math></span>) of 0.463 ± 0.024 g ethanol (g TRS)<sup>−1</sup>, and a biomass yield coefficient (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mrow><mi>X</mi></mrow><mo>/</mo><mrow><mi>S</mi></mrow></mrow></msub></math></span>) of 0.0451 ± 0.0039 g biomass (g TRS)<sup>−1</sup>. Validation in fermentations under distinct operational conditions, including extractive CO<sub>2</sub> stripping and very high gravity (VHG) feeding, confirmed high predictive accuracy. Coefficients of determination (R²) exceeded 0.98 and mean absolute percentage errors (MAPE) remained below 8 %. These results demonstrate that the proposed framework provides a reliable basis for real-time estimation of substrate and ethanol concentrations under anaerobic conditions.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 297-308"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171267","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.2026.02.001
Shuangshuang Tian , Yang Li , Dan Luo , Runlong Yang , Benli Liu , Nnditshedzeni Eric Maluta , Chenying Li , Xiaoxing Zhang
Following the phase-out of traditional halon-based agents, there is an increasing demand for efficient and eco-friendly alternatives. Perfluorohexanone (C6F12O), an eco-friendly fire extinguishing agent, has attracted significant attention, but problems such as relatively high fire extinguishing concentration and transient combustion-promoting effect at elevated temperatures persist when used alone. To optimize its performance, the synergistic fire suppression effect between C6F12O and heptafluoropropane (C3HF7) is systematically investigated via a combination of experiments and theoretical analyses. In the theoretical part, combustion models with different mixing ratios are established based on ReaxFF molecular dynamics (ReaxFF-MD), and the decomposition pathways of fluorine-containing compounds, free radical capture processes, and formation mechanisms of stable products are tracked; in the experimental part, multiple mixing ratios are designed, and key indicators of fire extinguishing performance are measured. It is found that CF2, CF3, and other species generated by the decomposition of the agents can effectively capture H, O, and OH radicals in combustion chain reactions and form stable products to interrupt the combustion process. The model with a 60 % C6F12O mixing ratio performs optimally: it not only drives thermodynamics toward fire suppression but also enables the composite system to exhibit the best positive synergistic effect (S=0.83) and fire extinguishing performance. This ratio also effectively inhibits the formation of toxic combustion products, with toxicity levels meeting relevant standards and no potential safety hazards to humans. This study provides important theoretical support for the development of eco-friendly and efficient fire extinguishing technologies and confirms the application potential of the composite system.
{"title":"Study on the synergistic fire suppression effects of C6F12O and C3HF7","authors":"Shuangshuang Tian , Yang Li , Dan Luo , Runlong Yang , Benli Liu , Nnditshedzeni Eric Maluta , Chenying Li , Xiaoxing Zhang","doi":"10.1016/j.cherd.2026.02.001","DOIUrl":"10.1016/j.cherd.2026.02.001","url":null,"abstract":"<div><div>Following the phase-out of traditional halon-based agents, there is an increasing demand for efficient and eco-friendly alternatives. Perfluorohexanone (C<sub>6</sub>F<sub>12</sub>O), an eco-friendly fire extinguishing agent, has attracted significant attention, but problems such as relatively high fire extinguishing concentration and transient combustion-promoting effect at elevated temperatures persist when used alone. To optimize its performance, the synergistic fire suppression effect between C<sub>6</sub>F<sub>12</sub>O and heptafluoropropane (C<sub>3</sub>HF<sub>7</sub>) is systematically investigated via a combination of experiments and theoretical analyses. In the theoretical part, combustion models with different mixing ratios are established based on ReaxFF molecular dynamics (ReaxFF-MD), and the decomposition pathways of fluorine-containing compounds, free radical capture processes, and formation mechanisms of stable products are tracked; in the experimental part, multiple mixing ratios are designed, and key indicators of fire extinguishing performance are measured. It is found that CF<sub>2</sub>, CF<sub>3</sub>, and other species generated by the decomposition of the agents can effectively capture H, O, and OH radicals in combustion chain reactions and form stable products to interrupt the combustion process. The model with a 60 % C<sub>6</sub>F<sub>12</sub>O mixing ratio performs optimally: it not only drives thermodynamics toward fire suppression but also enables the composite system to exhibit the best positive synergistic effect (S=0.83) and fire extinguishing performance. This ratio also effectively inhibits the formation of toxic combustion products, with toxicity levels meeting relevant standards and no potential safety hazards to humans. This study provides important theoretical support for the development of eco-friendly and efficient fire extinguishing technologies and confirms the application potential of the composite system.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 506-514"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171203","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: 2026-02-10DOI: 10.1016/j.cherd.2026.02.020
Cong Liu, Xiaolong Miao, Dihang Zhou, Hongxing Wang
Isosorbide, a bio-based diol derived from sorbitol, is a promising alternative to bisphenol A (BPA) in polymer manufacturing, yet its large-scale production remains limited by diffusion constraints, secondary dehydration, and energy-intensive separation. In this work, we develop a continuous, high-selectivity process for isosorbide synthesis using a heterogeneous azeotropic catalytic distillation strategy. A direct-pump feeding system enables the continuous introduction of high-viscosity sorbitol without dilution, while an ion-exchange resin catalyst provides efficient dehydration under intensified reaction–separation conditions. Nearly complete sorbitol conversion (∼100 %) and 91.2 % isosorbide selectivity were achieved. Temperature-dependent LHHW kinetic modeling reveals that equilibrium shifting through continuous water removal, rather than mass-transfer limitations, governs selectivity enhancement. Process simulation further establishes a scalable three-column azeotropic catalytic distillation design capable of producing 10,000 tons per year, supported by favorable thermal and economic performance. This study demonstrates a practical and energy-efficient route for industrial isosorbide production and provides mechanistic and design guidance for future process scale-up.
{"title":"High selectivity continuous production of isosorbide from sorbitol via reactive distillation","authors":"Cong Liu, Xiaolong Miao, Dihang Zhou, Hongxing Wang","doi":"10.1016/j.cherd.2026.02.020","DOIUrl":"10.1016/j.cherd.2026.02.020","url":null,"abstract":"<div><div>Isosorbide, a bio-based diol derived from sorbitol, is a promising alternative to bisphenol A (BPA) in polymer manufacturing, yet its large-scale production remains limited by diffusion constraints, secondary dehydration, and energy-intensive separation. In this work, we develop a continuous, high-selectivity process for isosorbide synthesis using a heterogeneous azeotropic catalytic distillation strategy. A direct-pump feeding system enables the continuous introduction of high-viscosity sorbitol without dilution, while an ion-exchange resin catalyst provides efficient dehydration under intensified reaction–separation conditions. Nearly complete sorbitol conversion (∼100 %) and 91.2 % isosorbide selectivity were achieved. Temperature-dependent LHHW kinetic modeling reveals that equilibrium shifting through continuous water removal, rather than mass-transfer limitations, governs selectivity enhancement. Process simulation further establishes a scalable three-column azeotropic catalytic distillation design capable of producing 10,000 tons per year, supported by favorable thermal and economic performance. This study demonstrates a practical and energy-efficient route for industrial isosorbide production and provides mechanistic and design guidance for future process scale-up.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 568-582"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171329","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: 2026-02-05DOI: 10.1016/j.cherd.2026.02.008
Zifeng Jin
As the core separation unit in petrochemical processes, the real-time optimization of distillation columns is crucial for energy efficiency and product quality. Traditional mechanistic models are computationally expensive for dynamic conditions, while data-driven approaches often ignore the mass/heat transfer topology between trays, leading to significant errors. Although graph neural networks (GNNs) can model system structure, they face challenges like unstable training, inadequate heterogeneous graph modeling, and high latency. To address these issues, this study proposes a real-time decision-making system using a Dynamic Spatiotemporal Graph Convolutional Network (DST-GCN). It employs heterogeneous node encoding to distinguish tray states and component properties, a dynamic adjacency matrix to capture spatiotemporal evolution of energy transfer, and uses orthogonal convolution with regularization to stabilize training. Integrated with feedforward-feedback control and edge computing, the system achieves millisecond response and lightweight deployment. Industrial tests in ethylene and methanol separation demonstrate improved purity control, reduced steam and power consumption, high fault detection accuracy, strong robustness, and cross-condition generalization. The results confirm the feasibility of GNNs in real-time optimization of complex industrial systems. Future work will focus on transfer learning, equipment degradation integration, and federated learning to advance from single-column to plant-wide intelligence.
{"title":"Optimization model of distillation tower operation based on graph neural network: Real time decision system for multi component separation","authors":"Zifeng Jin","doi":"10.1016/j.cherd.2026.02.008","DOIUrl":"10.1016/j.cherd.2026.02.008","url":null,"abstract":"<div><div>As the core separation unit in petrochemical processes, the real-time optimization of distillation columns is crucial for energy efficiency and product quality. Traditional mechanistic models are computationally expensive for dynamic conditions, while data-driven approaches often ignore the mass/heat transfer topology between trays, leading to significant errors. Although graph neural networks (GNNs) can model system structure, they face challenges like unstable training, inadequate heterogeneous graph modeling, and high latency. To address these issues, this study proposes a real-time decision-making system using a Dynamic Spatiotemporal Graph Convolutional Network (DST-GCN). It employs heterogeneous node encoding to distinguish tray states and component properties, a dynamic adjacency matrix to capture spatiotemporal evolution of energy transfer, and uses orthogonal convolution with regularization to stabilize training. Integrated with feedforward-feedback control and edge computing, the system achieves millisecond response and lightweight deployment. Industrial tests in ethylene and methanol separation demonstrate improved purity control, reduced steam and power consumption, high fault detection accuracy, strong robustness, and cross-condition generalization. The results confirm the feasibility of GNNs in real-time optimization of complex industrial systems. Future work will focus on transfer learning, equipment degradation integration, and federated learning to advance from single-column to plant-wide intelligence.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 465-479"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171330","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: 2026-01-23DOI: 10.1016/j.cherd.2026.01.048
Liang Zhang , Haifeng Lu , Xiaolei Guo , Haifeng Liu
This study addresses the challenges of micro-dosing and mixing in the continuous manufacturing of solid pharmaceutical formulations by developing a novel continuous feeding-mixing system based on external vibration excitation. The innovative design of a hopper structure with adjustable outlet area distribution demonstrated the potential for achieving precise mixing control of an active pharmaceutical ingredient (API) and an excipient across varying ratios. Experiments first validated the promotion of viscous particle flow by vertical vibration, achieving stable feeding within the range of 0.6–15 mg/s. Building on this, precise control of mixing ratios was enabled by designing different outlet area ratios. In mixing performance evaluation, online X-ray fluorescence spectroscopy confirmed the system achieves high-uniformity mixing with a coefficient of variation below 10 %. The study further revealed that optimal mixing stability occurs when Γ < 5, whereas excessive vibration degrades mixing quality.
{"title":"Micro-feeding and mixing of pharmaceutical solid dosage forms under external vibration","authors":"Liang Zhang , Haifeng Lu , Xiaolei Guo , Haifeng Liu","doi":"10.1016/j.cherd.2026.01.048","DOIUrl":"10.1016/j.cherd.2026.01.048","url":null,"abstract":"<div><div>This study addresses the challenges of micro-dosing and mixing in the continuous manufacturing of solid pharmaceutical formulations by developing a novel continuous feeding-mixing system based on external vibration excitation. The innovative design of a hopper structure with adjustable outlet area distribution demonstrated the potential for achieving precise mixing control of an active pharmaceutical ingredient (API) and an excipient across varying ratios. Experiments first validated the promotion of viscous particle flow by vertical vibration, achieving stable feeding within the range of 0.6–15 mg/s. Building on this, precise control of mixing ratios was enabled by designing different outlet area ratios. In mixing performance evaluation, online X-ray fluorescence spectroscopy confirmed the system achieves high-uniformity mixing with a coefficient of variation below 10 %. The study further revealed that optimal mixing stability occurs when Γ < 5, whereas excessive vibration degrades mixing quality.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 97-105"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076148","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.2026.02.016
Vytenis Šumskas , Feliksas Ivanauskas , Aivaras Kareiva , Andrius Pakalniškis , Rokas Astrauskas
In this paper, a mathematical model of yttrium aluminum garnet (YAG) synthesis is presented. It is described by a nonlinear system of reaction-diffusion equations and solved in a three-dimensional domain using numerical methods. Various simulations of the mathematical model are analyzed to obtain theoretical data on the dependence between chemical reaction yield and some factors of the model. The analyzed factors include temperature, particle size, reaction rate constant, diffusion coefficient and intermediate mixing of the materials. Idealized and more realistic randomized mixing models are proposed, and the optimal moments of mixing for various cases are calculated. The analysis of product aggregation is supplemented with visualizations of the model at the microscale level. Based upon numerical experiments, the recommendations for optimization of reaction yield with respect to time are summarized. In particular, mathematical simulations revealed that for the reaction taking place at 1000 °C, the optimal time for an intermediate mixing was found to be approximately 2.1 h after the start of reaction. The mixing resulted in the reduction of the synthesis time by approximately 0.9 h.
{"title":"Yttrium aluminum garnet synthesis: Analysis of yield factors using modeling","authors":"Vytenis Šumskas , Feliksas Ivanauskas , Aivaras Kareiva , Andrius Pakalniškis , Rokas Astrauskas","doi":"10.1016/j.cherd.2026.02.016","DOIUrl":"10.1016/j.cherd.2026.02.016","url":null,"abstract":"<div><div>In this paper, a mathematical model of yttrium aluminum garnet (YAG) synthesis is presented. It is described by a nonlinear system of reaction-diffusion equations and solved in a three-dimensional domain using numerical methods. Various simulations of the mathematical model are analyzed to obtain theoretical data on the dependence between chemical reaction yield and some factors of the model. The analyzed factors include temperature, particle size, reaction rate constant, diffusion coefficient and intermediate mixing of the materials. Idealized and more realistic randomized mixing models are proposed, and the optimal moments of mixing for various cases are calculated. The analysis of product aggregation is supplemented with visualizations of the model at the microscale level. Based upon numerical experiments, the recommendations for optimization of reaction yield with respect to time are summarized. In particular, mathematical simulations revealed that for the reaction taking place at 1000 °C, the optimal time for an intermediate mixing was found to be approximately 2.1 h after the start of reaction. The mixing resulted in the reduction of the synthesis time by approximately 0.9 h.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 657-664"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384901","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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