Pub Date : 2026-01-30DOI: 10.1016/j.cherd.2026.01.063
Gianluca Lombardini , Sara Badr , Tim Dreckmann , Hirokazu Sugiyama
Pharmaceutical manufacturing increasingly embraces digitalization to enhance reliability, ensure compliance and reduce downtime. This study introduces an integrated modeling framework designed to systematically determine robust operational regions (ROR) in water-for-injection (WFI) distribution loops, which are critical infrastructures subject to variable consumer demand and stringent regulatory constraints. Employing a structured workflow that combines first principles modeling, sensitivity-based parameter identifiability, and Monte Carlo simulations, the framework reliably captures the hydraulic behavior across operational conditions to guide process experts in establishing robust system operation. The approach addresses challenges arising from sparse data and limited sensor coverage, prevalent in current pharmaceutical operations. The application of the framework using industrial data demonstrated identification of conditions likely to trigger system alarms. Consequently, actionable setpoint recommendations were generated to ensure stable and alarm-free operation, offering a transferable blueprint for other fluid distribution networks. The results underscore the broader applicability of rigorous identifiability diagnostics as foundational tools to accelerate Pharma 4.0 adoption, sensor placement optimization, and proactive operational decision-making.
{"title":"An integrated modeling framework to determine robust operational regions in pharmaceutical water-for-injection distribution loops","authors":"Gianluca Lombardini , Sara Badr , Tim Dreckmann , Hirokazu Sugiyama","doi":"10.1016/j.cherd.2026.01.063","DOIUrl":"10.1016/j.cherd.2026.01.063","url":null,"abstract":"<div><div>Pharmaceutical manufacturing increasingly embraces digitalization to enhance reliability, ensure compliance and reduce downtime. This study introduces an integrated modeling framework designed to systematically determine robust operational regions (ROR) in water-for-injection (WFI) distribution loops, which are critical infrastructures subject to variable consumer demand and stringent regulatory constraints. Employing a structured workflow that combines first principles modeling, sensitivity-based parameter identifiability, and Monte Carlo simulations, the framework reliably captures the hydraulic behavior across operational conditions to guide process experts in establishing robust system operation. The approach addresses challenges arising from sparse data and limited sensor coverage, prevalent in current pharmaceutical operations. The application of the framework using industrial data demonstrated identification of conditions likely to trigger system alarms. Consequently, actionable setpoint recommendations were generated to ensure stable and alarm-free operation, offering a transferable blueprint for other fluid distribution networks. The results underscore the broader applicability of rigorous identifiability diagnostics as foundational tools to accelerate Pharma 4.0 adoption, sensor placement optimization, and proactive operational decision-making.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 388-399"},"PeriodicalIF":3.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171256","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 : 2026-01-29DOI: 10.1016/j.cherd.2026.01.061
Mohamed K. Hadj-Kali, Irfan Wazeer, Lahssen El blidi, Attiyah A. Al-Zahrani
The selective extraction of aromatic hydrocarbons, such as tetralin, from aliphatic compounds, such as decane, is of paramount importance in the petrochemical industry. The aim of this study is to investigate the application of deep eutectic solvents (DESs) as an environmentally friendly substitute for conventional solvents. A comprehensive screening of 79 DESs was conducted using the COSMO-RS model to identify the DESs that show the most promising extraction capabilities. Based on the screening results, four DESs were selected for experimental validation. The experimental investigation involved the determination of liquid-liquid equilibria for each DES-tetralin-decane system. Indeed, tetrabutyl ammonium bromide with triethylene glycol showed the highest selectivity of 9.40 at 20 % tetralin in the feed, while tetrabutyl ammonium bromide and levulinic acid showed a significant selectivity of 6.57 at an increased tetralin concentration of 60 %. The data were then successfully correlated using the Non-Random Two-Liquid model, with root mean square deviation values between experimental and calculated data less than 1.2 % for all ternary systems. Finally, insights into the interaction mechanisms between DESs and the aromatic compound were explored by interpreting the COSMO-RS sigma profile and sigma potential plots. The regeneration capability and cyclic reuse of TBAB:2-TEG DES were further evaluated, revealing a minimal performance loss of only 4.80 % after solvent recovery, while consistently maintaining extraction performance above 76 % over four extraction cycles.
{"title":"Selective extraction of tetralin from decane using tailored deep eutectic solvents: A COSMO-RS-guided approach","authors":"Mohamed K. Hadj-Kali, Irfan Wazeer, Lahssen El blidi, Attiyah A. Al-Zahrani","doi":"10.1016/j.cherd.2026.01.061","DOIUrl":"10.1016/j.cherd.2026.01.061","url":null,"abstract":"<div><div>The selective extraction of aromatic hydrocarbons, such as tetralin, from aliphatic compounds, such as decane, is of paramount importance in the petrochemical industry. The aim of this study is to investigate the application of deep eutectic solvents (DESs) as an environmentally friendly substitute for conventional solvents. A comprehensive screening of 79 DESs was conducted using the COSMO-RS model to identify the DESs that show the most promising extraction capabilities. Based on the screening results, four DESs were selected for experimental validation. The experimental investigation involved the determination of liquid-liquid equilibria for each DES-tetralin-decane system. Indeed, tetrabutyl ammonium bromide with triethylene glycol showed the highest selectivity of 9.40 at 20 % tetralin in the feed, while tetrabutyl ammonium bromide and levulinic acid showed a significant selectivity of 6.57 at an increased tetralin concentration of 60 %. The data were then successfully correlated using the Non-Random Two-Liquid model, with root mean square deviation values between experimental and calculated data less than 1.2 % for all ternary systems. Finally, insights into the interaction mechanisms between DESs and the aromatic compound were explored by interpreting the COSMO-RS sigma profile and sigma potential plots. The regeneration capability and cyclic reuse of TBAB:2-TEG DES were further evaluated, revealing a minimal performance loss of only 4.80 % after solvent recovery, while consistently maintaining extraction performance above 76 % over four extraction cycles.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 328-342"},"PeriodicalIF":3.9,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171199","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 : 2026-01-29DOI: 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":"2026-01-29","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 : 2026-01-29DOI: 10.1016/j.cherd.2026.01.060
Abdul Najim
The passive direct-contact evaporative cooling method has a vast potential to preserve fruits and vegetables after harvest. The coolers employing the method are attractive to areas access to water, as no external energy is required for cooling. However, the coolers cool down the space very slowly, particularly over several hours to half a day, to achieve the maximum temperature drop and saturation effectiveness. This article proposes and assesses a passive direct contact evaporative cooler with rapid cooling capability. A new evaporative cooling pad has been designed and used in the cooler with a storage volume of 47.3 L. In the field experiment, the cooler achieved a maximum temperature drop of 8 °C and a maximum saturation effectiveness of 0.65 in 50 min at the ambient temperature of 35.5 °C. The process duration to achieve the maximum temperature drop and saturation effectiveness was reduced by 58.5–79.3 % compared to an existing cooler in the literature, a crate (56 L storage volume) wrapped in a charcoal blanket. Additionally, the relative humidity inside the cooler was increased by 40.4 % at the ambient air relative humidity of 35.1 %.
{"title":"Experimental study of passive direct-contact evaporative cooler with rapid cooling for preserving fresh fruits and vegetables","authors":"Abdul Najim","doi":"10.1016/j.cherd.2026.01.060","DOIUrl":"10.1016/j.cherd.2026.01.060","url":null,"abstract":"<div><div>The passive direct-contact evaporative cooling method has a vast potential to preserve fruits and vegetables after harvest. The coolers employing the method are attractive to areas access to water, as no external energy is required for cooling. However, the coolers cool down the space very slowly, particularly over several hours to half a day, to achieve the maximum temperature drop and saturation effectiveness. This article proposes and assesses a passive direct contact evaporative cooler with rapid cooling capability. A new evaporative cooling pad has been designed and used in the cooler with a storage volume of 47.3 L. In the field experiment, the cooler achieved a maximum temperature drop of 8 °C and a maximum saturation effectiveness of 0.65 in 50 min at the ambient temperature of 35.5 °C. The process duration to achieve the maximum temperature drop and saturation effectiveness was reduced by 58.5–79.3 % compared to an existing cooler in the literature, a crate (56 L storage volume) wrapped in a charcoal blanket. Additionally, the relative humidity inside the cooler was increased by 40.4 % at the ambient air relative humidity of 35.1 %.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 343-353"},"PeriodicalIF":3.9,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171265","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 : 2026-01-28DOI: 10.1016/j.cherd.2026.01.058
Mrudul Nilesh Shroff, Supriyo Kumar Mondal, Sandhya R. Shewale
Sunflower seeds (Helianthus annuus L.) are well-known for their high protein and oil content, which are particularly abundant in monounsaturated and polyunsaturated fatty acids (MUFA and PUFA). Traditionally, oil extraction from these seeds involves pre-pressing and the use of solvents like n-hexane. However, these method has certain disadvantages, including solvent toxicity and prolonged processing times. To mitigate these issues, the three phase partitioning (TPP) technique has been introduced as an alternative, allowing for the efficient extraction of both oil and high-quality protein from sunflower seed residue. The TPP technique was used to extract oil from sunflower seeds, optimizing parameters such as ammonium sulphate concentration (45% w/v), slurry to t-butanol ratio (1:2 v/v), temperature (28 ± 2 °C), and solid to aqueous ratio (1:10 w/v). The study also includes a comparison of two types of ultrasound assisted TPP study. Ultrasound pre-treatment followed by TPP and simultaneous ultrasound-assisted TPP, both yielding 48.3% and 48% oil extraction. Extraction kinetics for conventional method, ultrasound-assisted three phase partitioning (UTPP), and ultrasound pre-treatment-assisted three phase partitioning (UPTPP) conformed to Peleg’s model.
{"title":"A study of three phase partitioning and ultrasound assisted three phase partitioning method to extract sunflower oil","authors":"Mrudul Nilesh Shroff, Supriyo Kumar Mondal, Sandhya R. Shewale","doi":"10.1016/j.cherd.2026.01.058","DOIUrl":"10.1016/j.cherd.2026.01.058","url":null,"abstract":"<div><div>Sunflower seeds (<em>Helianthus annuus L.</em>) are well-known for their high protein and oil content, which are particularly abundant in monounsaturated and polyunsaturated fatty acids (MUFA and PUFA). Traditionally, oil extraction from these seeds involves pre-pressing and the use of solvents like n-hexane. However, these method has certain disadvantages, including solvent toxicity and prolonged processing times. To mitigate these issues, the three phase partitioning (TPP) technique has been introduced as an alternative, allowing for the efficient extraction of both oil and high-quality protein from sunflower seed residue. The TPP technique was used to extract oil from sunflower seeds, optimizing parameters such as ammonium sulphate concentration (45% w/v), slurry to t-butanol ratio (1:2 v/v), temperature (28 ± 2 °C), and solid to aqueous ratio (1:10 w/v). The study also includes a comparison of two types of ultrasound assisted TPP study. Ultrasound pre-treatment followed by TPP and simultaneous ultrasound-assisted TPP, both yielding 48.3% and 48% oil extraction. Extraction kinetics for conventional method, ultrasound-assisted three phase partitioning (UTPP), and ultrasound pre-treatment-assisted three phase partitioning (UPTPP) conformed to Peleg’s model.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 234-242"},"PeriodicalIF":3.9,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-27DOI: 10.1016/j.cherd.2026.01.055
H.M. Radwan , K. Pope , K.A. Hawboldt , G.F. Naterer
This study investigates the hydrolysis process of the thermochemical copper-chlorine (Cu-Cl) cycle of hydrogen production, specifically the influence of CuCl₂ particle morphology and size on conversion and reaction rates. Effects of drying, crushing, and crystallization of particles are considered. CuCl₂ samples with average particle diameters of 95 µm (dried), 27 µm (crushed), and 230 µm (crystallized) were tested in a semi-batch fixed bed reactor at 390°C. Crystallization using HCl as an anti-solvent yielded flaky agglomerated particles and achieved up to 97 % conversion, outperforming dried material and closely matching the crushed sample. Kinetic modelling with a shrinking core model (SCM), for both spherical and cylindrical geometries, identified gas film diffusion as the dominant resistance for the smallest sizes of crushed and crystallized particles. X-ray diffraction indicated the formation of CuCl as a side product. The findings established crystallization as a promising approach to facilitate the hydrolysis process.
{"title":"Particle morphology effects on conversion and reaction rate of copper chloride hydrolysis for thermochemical hydrogen production","authors":"H.M. Radwan , K. Pope , K.A. Hawboldt , G.F. Naterer","doi":"10.1016/j.cherd.2026.01.055","DOIUrl":"10.1016/j.cherd.2026.01.055","url":null,"abstract":"<div><div>This study investigates the hydrolysis process of the thermochemical copper-chlorine (Cu-Cl) cycle of hydrogen production, specifically the influence of CuCl₂ particle morphology and size on conversion and reaction rates. Effects of drying, crushing, and crystallization of particles are considered. CuCl₂ samples with average particle diameters of 95 µm (dried), 27 µm (crushed), and 230 µm (crystallized) were tested in a semi-batch fixed bed reactor at 390°C. Crystallization using HCl as an anti-solvent yielded flaky agglomerated particles and achieved up to 97 % conversion, outperforming dried material and closely matching the crushed sample. Kinetic modelling with a shrinking core model (SCM), for both spherical and cylindrical geometries, identified gas film diffusion as the dominant resistance for the smallest sizes of crushed and crystallized particles. X-ray diffraction indicated the formation of CuCl as a side product. The findings established crystallization as a promising approach to facilitate the hydrolysis process.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 255-267"},"PeriodicalIF":3.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076150","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 : 2026-01-27DOI: 10.1016/j.cherd.2026.01.057
Y.Y. Liang , M. Li
Membrane technologies are increasingly applied for microplastic (MP) removal; however, their effectiveness, fouling characteristics, and subsequent environmental impacts are not sufficiently synthesized. This paper integrates concepts on microplastic fate, membrane aging, fouling mechanisms, and AI-enabled process support. This paper primarily highlights pressure-driven membranes such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) membranes, as well as hybrid technologies such as surface-modified membranes and electrochemical membrane bioreactors (EMBRs). This paper also highlights that Extreme Gradient Boosting (XGB) models and NF-grid partitioning (NF-GP) models were found to provide the best predictions on membrane process performance, whereas models using Support Vector Regression on Fast Forest Actuator (SVR-FFA) were found to provide the best predictions on micropollutant behavior. Finally, an AI-enabled modeling strategy is introduced by combining concepts on Hermia fouling models and physics-informed AI models.
{"title":"Microplastic removal using membrane technologies: Challenges, fouling mitigation, and emerging AI-enabled solutions","authors":"Y.Y. Liang , M. Li","doi":"10.1016/j.cherd.2026.01.057","DOIUrl":"10.1016/j.cherd.2026.01.057","url":null,"abstract":"<div><div>Membrane technologies are increasingly applied for microplastic (MP) removal; however, their effectiveness, fouling characteristics, and subsequent environmental impacts are not sufficiently synthesized. This paper integrates concepts on microplastic fate, membrane aging, fouling mechanisms, and AI-enabled process support. This paper primarily highlights pressure-driven membranes such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) membranes, as well as hybrid technologies such as surface-modified membranes and electrochemical membrane bioreactors (EMBRs). This paper also highlights that Extreme Gradient Boosting (XGB) models and NF-grid partitioning (NF-GP) models were found to provide the best predictions on membrane process performance, whereas models using Support Vector Regression on Fast Forest Actuator (SVR-FFA) were found to provide the best predictions on micropollutant behavior. Finally, an AI-enabled modeling strategy is introduced by combining concepts on Hermia fouling models and physics-informed AI models.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 268-278"},"PeriodicalIF":3.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171272","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}
In this work, hydroxyapatite (HAp) synthesized from natural Moroccan phosphate and its polyaniline-modified composites (HAp–5PANI and HAp–10PANI) were developed as efficient adsorbents for the removal of methyl orange (MO) from aqueous solutions. Structural and spectroscopic characterizations using XRD, FTIR, and SEM–EDX confirmed the successful formation of crystalline hydroxyapatite and its effective functionalization with polyaniline, resulting in hybrid materials with modified surface chemistry and enhanced heterogeneity. Batch adsorption experiments demonstrated that polyaniline incorporation markedly improved adsorption performance. The theoretical adsorption capacity derived from the Dubinin–Radushkevich model increased from 39.3 mg·g⁻¹ for pristine HAp to 94.2 mg·g⁻¹ for HAp–10PANI, reflecting a strong synergistic effect between the inorganic matrix and the polymeric phase. Kinetic studies showed that MO adsorption followed a pseudo-second-order model with high correlation coefficients (R² > 0.97), indicating rapid uptake and efficient utilization of adsorption sites. Isotherm analysis revealed that the Freundlich model provided the most appropriate description of the adsorption process (R² up to 0.981), consistent with heterogeneous multilayer adsorption dominated by physical interactions, as confirmed by low mean adsorption energy values (E < 0.5 kJ·mol⁻¹). Regeneration experiments demonstrated good reusability of the PANI-modified composites, with HAp–10PANI retaining approximately 89 % of its initial removal efficiency after five adsorption–desorption cycles using alkaline regeneration, compared to about 70 % for pristine HAp. Overall, the results highlight the potential of polyaniline-functionalized hydroxyapatite derived from natural phosphate as a sustainable, efficient, and cost-effective adsorbent for dye-contaminated wastewater treatment.
{"title":"Enhanced adsorption of methyl orange using polyaniline-modified hydroxyapatite derived from natural Moroccan phosphate","authors":"Yousra Benchhiba, Souhayla Latifi, Douae Touareb, Larbi El Hammari, Sanaâ Saoiabi","doi":"10.1016/j.cherd.2026.01.051","DOIUrl":"10.1016/j.cherd.2026.01.051","url":null,"abstract":"<div><div>In this work, hydroxyapatite (HAp) synthesized from natural Moroccan phosphate and its polyaniline-modified composites (HAp–5PANI and HAp–10PANI) were developed as efficient adsorbents for the removal of methyl orange (MO) from aqueous solutions. Structural and spectroscopic characterizations using XRD, FTIR, and SEM–EDX confirmed the successful formation of crystalline hydroxyapatite and its effective functionalization with polyaniline, resulting in hybrid materials with modified surface chemistry and enhanced heterogeneity. Batch adsorption experiments demonstrated that polyaniline incorporation markedly improved adsorption performance. The theoretical adsorption capacity derived from the Dubinin–Radushkevich model increased from 39.3 mg·g⁻¹ for pristine HAp to 94.2 mg·g⁻¹ for HAp–10PANI, reflecting a strong synergistic effect between the inorganic matrix and the polymeric phase. Kinetic studies showed that MO adsorption followed a pseudo-second-order model with high correlation coefficients (R² > 0.97), indicating rapid uptake and efficient utilization of adsorption sites. Isotherm analysis revealed that the Freundlich model provided the most appropriate description of the adsorption process (R² up to 0.981), consistent with heterogeneous multilayer adsorption dominated by physical interactions, as confirmed by low mean adsorption energy values (E < 0.5 kJ·mol⁻¹). Regeneration experiments demonstrated good reusability of the PANI-modified composites, with HAp–10PANI retaining approximately 89 % of its initial removal efficiency after five adsorption–desorption cycles using alkaline regeneration, compared to about 70 % for pristine HAp. Overall, the results highlight the potential of polyaniline-functionalized hydroxyapatite derived from natural phosphate as a sustainable, efficient, and cost-effective adsorbent for dye-contaminated wastewater treatment.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 165-186"},"PeriodicalIF":3.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076069","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 : 2026-01-27DOI: 10.1016/j.cherd.2026.01.031
Yao Shi, Ming Xiao, Zhe Wu
Traditional Lyapunov-based model predictive control (LMPC) using machine learning models typically involves three sequential steps: developing a machine learning (ML) model, designing a Lyapunov function for stability guarantees, and constructing the model predictive controller (MPC). However, these steps are inherently interdependent, and improper design in one component, such as the ML model or the Lyapunov function, can adversely affect controller design and closed-loop performance. To overcome these challenges, we propose an end-to-end machine learning-based Lyapunov-stable MPC (E2E-MLMPC) framework that simultaneously learns the Lyapunov function and MPC policy for nonlinear systems directly from data. Given a pre-trained ML model, a stabilizing control policy is learned within a unified computational graph that integrates the ML-based dynamics, system constraints, and Lyapunov stability conditions. The neural policy parameters are optimized via automatic differentiation, enabling end-to-end training with explicit stability certification. A rigorous theoretical analysis is provided to establish the closed-loop stability of the resulting controller. Furthermore, since the learned controller is implemented as a neural network, it substantially reduces online computation time compared with traditional ML-based MPC schemes. Simulation studies demonstrate that the proposed E2E-MLMPC framework achieves stable and efficient control performance in a chemical reactor example.
{"title":"End-to-end machine learning of Lyapunov-stable MPC for nonlinear systems with unknown dynamics","authors":"Yao Shi, Ming Xiao, Zhe Wu","doi":"10.1016/j.cherd.2026.01.031","DOIUrl":"10.1016/j.cherd.2026.01.031","url":null,"abstract":"<div><div>Traditional Lyapunov-based model predictive control (LMPC) using machine learning models typically involves three sequential steps: developing a machine learning (ML) model, designing a Lyapunov function for stability guarantees, and constructing the model predictive controller (MPC). However, these steps are inherently interdependent, and improper design in one component, such as the ML model or the Lyapunov function, can adversely affect controller design and closed-loop performance. To overcome these challenges, we propose an end-to-end machine learning-based Lyapunov-stable MPC (E2E-MLMPC) framework that simultaneously learns the Lyapunov function and MPC policy for nonlinear systems directly from data. Given a pre-trained ML model, a stabilizing control policy is learned within a unified computational graph that integrates the ML-based dynamics, system constraints, and Lyapunov stability conditions. The neural policy parameters are optimized via automatic differentiation, enabling end-to-end training with explicit stability certification. A rigorous theoretical analysis is provided to establish the closed-loop stability of the resulting controller. Furthermore, since the learned controller is implemented as a neural network, it substantially reduces online computation time compared with traditional ML-based MPC schemes. Simulation studies demonstrate that the proposed E2E-MLMPC framework achieves stable and efficient control performance in a chemical reactor example.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 130-141"},"PeriodicalIF":3.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-27DOI: 10.1016/j.cherd.2026.01.053
Ayse Elif Ates , Sinan Ates , Serdar Aydın , Gamze Varank
The treatment of real pharmaceutical wastewater remains a major challenge due to its highly complex composition, strong matrix effects, and associated toxicity. In this study, a real industrial pharmaceutical wastewater was treated using electrocatalytic oxidation (ECO) and photo electrocatalytic oxidation (PECO) processes employing Zn/TiO2-coated stainless-steel electrodes. The performance of the two processes was systematically evaluated and compared under identical operating conditions. Response Surface Methodology (RSM) was applied to optimize key operational parameters, including initial pH, applied current density, reaction time, and temperature. The developed models successfully predicted COD and UV254 removal efficiencies with high accuracy (R2>0.98), revealing strong interaction effects among operational variables. Principal Component Analysis (PCA) was further employed to elucidate multivariate relationships, identifying COD, UV254, and current density as the dominant contributors to process variability. Among the tested configurations, the PECO system using a Zn/TiO2-TiO2 electrode pair exhibited superior performance, achieving maximum removal efficiencies of 78.78 % COD and 71.75 % UV254. Acute toxicity assessment using Daphnia magna demonstrated a substantial improvement in effluent quality, with immobilization decreasing from 97 % to 28 % after PECO treatment. A strong correlation between UV₂₅₄ reduction and toxicity abatement was observed, indicating that UV254 may serve as a useful indicative parameter for tracking ecotoxicity changes within this specific system. This study presents a comparative and integrated evaluation of ECO and PECO processes for real pharmaceutical wastewater, combining advanced electrode design, statistical optimization, multivariate analysis, and ecotoxicological assessment. The results highlight the critical role of photo-assisted electrocatalysis and process optimization in achieving effective pollutant removal and toxicity reduction under realistic industrial conditions.
{"title":"Performance comparison of electrocatalytic and photoelectrocatalytic oxidation processes for the treatment of real pharmaceutical wastewater: Mechanistic insights and acute toxicity assessment","authors":"Ayse Elif Ates , Sinan Ates , Serdar Aydın , Gamze Varank","doi":"10.1016/j.cherd.2026.01.053","DOIUrl":"10.1016/j.cherd.2026.01.053","url":null,"abstract":"<div><div>The treatment of real pharmaceutical wastewater remains a major challenge due to its highly complex composition, strong matrix effects, and associated toxicity. In this study, a real industrial pharmaceutical wastewater was treated using electrocatalytic oxidation (ECO) and photo electrocatalytic oxidation (PECO) processes employing Zn/TiO<sub>2</sub>-coated stainless-steel electrodes. The performance of the two processes was systematically evaluated and compared under identical operating conditions. Response Surface Methodology (RSM) was applied to optimize key operational parameters, including initial pH, applied current density, reaction time, and temperature. The developed models successfully predicted COD and UV<sub>254</sub> removal efficiencies with high accuracy (R<sup>2</sup>>0.98), revealing strong interaction effects among operational variables. Principal Component Analysis (PCA) was further employed to elucidate multivariate relationships, identifying COD, UV<sub>254</sub>, and current density as the dominant contributors to process variability. Among the tested configurations, the PECO system using a Zn/TiO<sub>2</sub>-TiO<sub>2</sub> electrode pair exhibited superior performance, achieving maximum removal efficiencies of 78.78 % COD and 71.75 % UV<sub>254</sub>. Acute toxicity assessment using <em>Daphnia magna</em> demonstrated a substantial improvement in effluent quality, with immobilization decreasing from 97 % to 28 % after PECO treatment. A strong correlation between UV₂₅₄ reduction and toxicity abatement was observed, indicating that UV<sub>254</sub> may serve as a useful indicative parameter for tracking ecotoxicity changes within this specific system. This study presents a comparative and integrated evaluation of ECO and PECO processes for real pharmaceutical wastewater, combining advanced electrode design, statistical optimization, multivariate analysis, and ecotoxicological assessment. The results highlight the critical role of photo-assisted electrocatalysis and process optimization in achieving effective pollutant removal and toxicity reduction under realistic industrial conditions.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 204-222"},"PeriodicalIF":3.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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