Pub Date : 2026-03-01Epub Date: 2026-02-07DOI: 10.1016/j.cherd.2026.02.004
Wei-Xuan Xu , Vincentius Surya Kurnia Adi , Chuei-Tin Chang
Modern process design must ensure robust operability under uncertainties, not just minimize the cost. The dynamic flexibility index () quantifies whether a system governed by ordinary or partial differential equations ((ODEs or PDEs) can satisfy given constraints under time-varying disturbances. Computing is, however, computationally challenging: extending the traditional steady-state vertex method to its dynamic counterpart requires time (and, for PDEs, space) discretization, which renders exponential growth of the computation time for vertex enumeration with the numbers of uncertain parameters and discretization intervals. This combinatorial explosion problem makes routine flexibility analysis impractical in real-world studies where timely, decisions are absolutely necessary. A parallel genetic algorithm (PGA) is developed in this work to accelerate vertex search by distributing fitness evaluations across multi-core processors while still preserving the original optimization structure. The proposed framework utilizes piecewise-constant parameterization of control inputs and couples outer GA with inner deterministic solver. In all case studies, this approach attains the same values as those calculated with the serial GA while substantially reducing computation time. It has also been shown that increasing control granularity can elevate achievable flexibility effectively. The above-mentioned PGA provides a scalable, accurate, and practical route to dynamic flexibility assessment for high-dimensional chemical systems.
{"title":"Toward practical flexibility assessment of complex dynamic systems via parallel vertex search","authors":"Wei-Xuan Xu , Vincentius Surya Kurnia Adi , Chuei-Tin Chang","doi":"10.1016/j.cherd.2026.02.004","DOIUrl":"10.1016/j.cherd.2026.02.004","url":null,"abstract":"<div><div>Modern process design must ensure robust operability under uncertainties, not just minimize the cost. The dynamic flexibility index (<span><math><msub><mrow><mi>FI</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span>) quantifies whether a system governed by ordinary or partial differential equations ((ODEs or PDEs) can satisfy given constraints under time-varying disturbances. Computing <span><math><msub><mrow><mi>FI</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> is, however, computationally challenging: extending the traditional steady-state vertex method to its dynamic counterpart requires time (and, for PDEs, space) discretization, which renders exponential growth of the computation time for vertex enumeration with the numbers of uncertain parameters and discretization intervals. This combinatorial explosion problem makes routine flexibility analysis impractical in real-world studies where timely, decisions are absolutely necessary. A parallel genetic algorithm (PGA) is developed in this work to accelerate vertex search by distributing fitness evaluations across multi-core processors while still preserving the original optimization structure. The proposed framework utilizes piecewise-constant parameterization of control inputs and couples outer GA with inner deterministic solver. In all case studies, this approach attains the same <span><math><msub><mrow><mi>FI</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> values as those calculated with the serial GA while substantially reducing computation time. It has also been shown that increasing control granularity can elevate achievable flexibility effectively. The above-mentioned PGA provides a scalable, accurate, and practical route to dynamic flexibility assessment for high-dimensional chemical systems.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 729-745"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384906","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: 2026-02-15DOI: 10.1016/j.cherd.2026.02.026
Iftiab Ahammed Sarker , Mohd Salman , Rizwan Ullah , Shah Mohammad Mominul Islam , Mohammed Zeehan Saleheen , Mohd Shahbudin Masdar , Edy Herianto Majlan , Nurul Akidah Baharuddin , Zulfadly Anuar Taip , Rasyikah Md Khalid
The growing demand for electricity and peak load pressures in institutional facilities require cost-effective, low-carbon energy solutions. This study evaluates the techno-economic and environmental performance of grid-connected photovoltaic (PV) systems, both with and without energy storage, for institutional consumers. A Malaysian university serves as a representative case for this analysis. The system configurations were optimized using HOMER Grid and validated through design modeling in PVsyst. The results demonstrate that grid-connected PV systems provide significant economic and environmental benefits, primarily by mitigating demand charges during daytime operation. While integrating battery Energy storage system (BESS) enhances operational flexibility and resilience, it also results in higher lifecycle costs given the current tariff and storage price conditions. Both configurations offer significant environmental benefits, reducing CO2 emissions compared to the conventional grid. PVsyst simulations validated the system design, predicting average specific yields exceeding 4.18 kWh/kWp/day and performance ratios of 86 % and 85.3 % respectively. The findings highlight that optimal PV system sizing and tariff-aware operation are more critical for achieving cost-effective decarbonization in grid-connected institutions than the integration of storage solutions. This study offers valuable insights applicable to commercial and institutional facilities with similar load characteristics.
{"title":"Techno-economic feasibility and optimal design of grid-connected PV system with energy storage: A case study for Malaysia’s institutional","authors":"Iftiab Ahammed Sarker , Mohd Salman , Rizwan Ullah , Shah Mohammad Mominul Islam , Mohammed Zeehan Saleheen , Mohd Shahbudin Masdar , Edy Herianto Majlan , Nurul Akidah Baharuddin , Zulfadly Anuar Taip , Rasyikah Md Khalid","doi":"10.1016/j.cherd.2026.02.026","DOIUrl":"10.1016/j.cherd.2026.02.026","url":null,"abstract":"<div><div>The growing demand for electricity and peak load pressures in institutional facilities require cost-effective, low-carbon energy solutions. This study evaluates the techno-economic and environmental performance of grid-connected photovoltaic (PV) systems, both with and without energy storage, for institutional consumers. A Malaysian university serves as a representative case for this analysis. The system configurations were optimized using HOMER Grid and validated through design modeling in PVsyst. The results demonstrate that grid-connected PV systems provide significant economic and environmental benefits, primarily by mitigating demand charges during daytime operation. While integrating battery Energy storage system (BESS) enhances operational flexibility and resilience, it also results in higher lifecycle costs given the current tariff and storage price conditions. Both configurations offer significant environmental benefits, reducing CO<sub>2</sub> emissions compared to the conventional grid. PVsyst simulations validated the system design, predicting average specific yields exceeding 4.18 kWh/kWp/day and performance ratios of 86 % and 85.3 % respectively. The findings highlight that optimal PV system sizing and tariff-aware operation are more critical for achieving cost-effective decarbonization in grid-connected institutions than the integration of storage solutions. This study offers valuable insights applicable to commercial and institutional facilities with similar load characteristics.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 925-944"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384910","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: 2026-02-18DOI: 10.1016/j.cherd.2026.02.050
Rizki Febrian , Hanny Meirinawati , Ni Luh Wulan Septiani , Diana Rahayuning Wulan , Raden Tina Rosmalina , Willy Cahya Nugraha , Nurfina Yudasari , Brian Yuliarto , Muammar Qadafi
This study reports the synthesis of ZnO/C and ZnO/TiO₂/C photocatalysts derived from polyvinylpyrrolidone (PVP)-assisted metal–organic frameworks (PVP/ZIF-8 and PVP/ZIF-8/Ti) for the removal of Bisphenol-A (BPA) from water under ambient and UVC light. The materials were characterized by XRD, SEM–EDX, BET, and UV–Vis DRS. ZnO/TiO2/C exhibited a specific surface area of 1036 m²/g and a bandgap of 2.85 eV, while ZnO/C showed 1056 m²/g and 2.92 eV. Adsorption experiments revealed that PVP/ZIF-8/Ti achieved the highest removal efficiency of 67 %, followed by ZnO/TiO2/C (59 %), PVP/ZIF-8 (58 %), and ZnO/C (55 %). Photocatalytic degradation under UVC light showed superior results, with ZnO/TiO2/C achieving complete BPA removal (100 %) within 60 min, outperforming ZnO/C (85–90 %). Under ambient light, ZnO/TiO2/C and ZnO/C achieved ∼70–75 % and ∼55–60 % degradation, respectively. Scavenger tests indicated that O₂•⁻ radicals played the dominant role in ZnO/C, while ZnO/TiO2/C exhibited multi-radical participation with higher resistance to recombination. Reusability tests confirmed stability over three cycles, maintaining > 94 % activity. Compared with reported catalysts, the PVP/ZIF-8/Ti-derived ZnO/TiO2/C system demonstrated high efficiency at a moderate catalyst-to-BPA ratio (1:50), offering a cost-effective route for BPA degradation.
{"title":"Degradation of bisphenol A in water by ambient/UVC light-assisted ZnO/C and ZnO/TiO2/C photocatalysts derived from PVP/ZIF-8 and PVP/ZIF-8/Ti MOFs","authors":"Rizki Febrian , Hanny Meirinawati , Ni Luh Wulan Septiani , Diana Rahayuning Wulan , Raden Tina Rosmalina , Willy Cahya Nugraha , Nurfina Yudasari , Brian Yuliarto , Muammar Qadafi","doi":"10.1016/j.cherd.2026.02.050","DOIUrl":"10.1016/j.cherd.2026.02.050","url":null,"abstract":"<div><div>This study reports the synthesis of ZnO/C and ZnO/TiO₂/C photocatalysts derived from polyvinylpyrrolidone (PVP)-assisted metal–organic frameworks (PVP/ZIF-8 and PVP/ZIF-8/Ti) for the removal of Bisphenol-A (BPA) from water under ambient and UVC light. The materials were characterized by XRD, SEM–EDX, BET, and UV–Vis DRS. ZnO/TiO<sub>2</sub>/C exhibited a specific surface area of 1036 m²/g and a bandgap of 2.85 eV, while ZnO/C showed 1056 m²/g and 2.92 eV. Adsorption experiments revealed that PVP/ZIF-8/Ti achieved the highest removal efficiency of 67 %, followed by ZnO/TiO<sub>2</sub>/C (59 %), PVP/ZIF-8 (58 %), and ZnO/C (55 %). Photocatalytic degradation under UVC light showed superior results, with ZnO/TiO<sub>2</sub>/C achieving complete BPA removal (100 %) within 60 min, outperforming ZnO/C (85–90 %). Under ambient light, ZnO/TiO<sub>2</sub>/C and ZnO/C achieved ∼70–75 % and ∼55–60 % degradation, respectively. Scavenger tests indicated that O₂•⁻ radicals played the dominant role in ZnO/C, while ZnO/TiO<sub>2</sub>/C exhibited multi-radical participation with higher resistance to recombination. Reusability tests confirmed stability over three cycles, maintaining > 94 % activity. Compared with reported catalysts, the PVP/ZIF-8/Ti-derived ZnO/TiO<sub>2</sub>/C system demonstrated high efficiency at a moderate catalyst-to-BPA ratio (1:50), offering a cost-effective route for BPA degradation.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 894-907"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-27DOI: 10.1016/j.cherd.2026.01.057
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":"2026-03-01","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}
Accurately forecasting the fast transients that govern catalytic reactors remains difficult because first-principles ordinary differential equation (ODE) models neglect unmodelled heat and mass-transfer effects and therefore perform poorly (baseline CO-oxidation rate = –0.231). For the above reason, this study presents a systematic hybrid mechanistic machine-learning (ML) framework that couples a physically rigorous CSTR model with data-driven residual learning to close these physics gaps. A six-factor design of experiments generated 500 operating scenarios, and after simulation, quality screening, derivative estimation, and residual/outlier filtering, the residual-learning dataset comprised approximately 33,096 usable samples. Five regressors (XGBoost, LightGBM, SVR, MLP and sparse Gaussian-process regression) were hyperparameter-tuned with Optuna and blended through weight optimisation. Uncertainty was propagated with GP posterior bands and inter-model disagreement. The optimised ensemble lifted test-set accuracy to = 0.755, RMSE = 0.006 and MdAPE = 93 % a dramatic recovery over the mechanistic baseline. ±2σ GP bands captured 94 % of unseen points, providing actionable epistemic bounds. Performance deteriorated by only ∼21 % when 5 % Gaussian sensor noise was injected, confirming robustness for on-line use. By modularising experiment design, physics-guided feature engineering, automated model selection, and calibrated uncertainty quantification, this workflow delivers interpretable, real-time-capable surrogate models within the modelled operating envelope, outperforming pure ODE and single-model ML baselines. The protocol is transferable to other catalytic systems and establishes a reproducible path toward uncertainty-aware reactor optimisation and control.
{"title":"A systematic hybrid mechanistic–machine learning framework for catalytic reactor modelling and computational validation using CO oxidation","authors":"Ebenezer Aquisman Asare , Dickson Abdul-Wahab , Elsie Effah Kaufmann , Rafeah Wahi , Zainab Ngaini , Abigail Ampadu","doi":"10.1016/j.cherd.2026.01.039","DOIUrl":"10.1016/j.cherd.2026.01.039","url":null,"abstract":"<div><div>Accurately forecasting the fast transients that govern catalytic reactors remains difficult because first-principles ordinary differential equation (ODE) models neglect unmodelled heat and mass-transfer effects and therefore perform poorly (baseline CO-oxidation rate <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> = –0.231). For the above reason, this study presents a systematic hybrid mechanistic machine-learning (ML) framework that couples a physically rigorous CSTR model with data-driven residual learning to close these physics gaps. A six-factor design of experiments generated 500 operating scenarios, and after simulation, quality screening, derivative estimation, and residual/outlier filtering, the residual-learning dataset comprised approximately 33,096 usable samples. Five regressors (XGBoost, LightGBM, SVR, MLP and sparse Gaussian-process regression) were hyperparameter-tuned with Optuna and blended through weight optimisation. Uncertainty was propagated with GP posterior bands and inter-model disagreement. The optimised ensemble lifted test-set accuracy to <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.755, RMSE = 0.006 <span><math><mrow><mi>mol·</mi><msup><mrow><mi>m</mi></mrow><mrow><mo>−</mo><mn>3</mn></mrow></msup><mi>·</mi><msup><mrow><mi>s</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> and MdAPE = 93 % a dramatic recovery over the mechanistic baseline. ±2σ GP bands captured 94 % of unseen points, providing actionable epistemic bounds. Performance deteriorated by only ∼21 % when 5 % Gaussian sensor noise was injected, confirming robustness for on-line use. By modularising experiment design, physics-guided feature engineering, automated model selection, and calibrated uncertainty quantification, this workflow delivers interpretable, real-time-capable surrogate models within the modelled operating envelope, outperforming pure ODE and single-model ML baselines. The protocol is transferable to other catalytic systems and establishes a reproducible path toward uncertainty-aware reactor optimisation and control.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 1-22"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015801","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.2026.02.022
Vladimir P. Zhdanov
Due to its high practical importance and relatively simple mechanism, synthesis of ammonia on Fe-based catalysts is paradigmatic in applied heterogeneous catalysis as well as in related academic studies. Under steady-state conditions, this process is widely considered to occur under appreciable coverage of the surface by N adatoms and to be limited by dissociative N adsorption. It has been described by the kinetic models of the Temkin-Pyzhev type implying appreciable lateral N-N interactions and/or surface heterogeneity and by the Langmuirian models completely neglecting the nonideality of an adsorbed overlayer. Despite the difference of the available approaches, the fits of experiments are typically claimed to be good. Herein, this apparently surprising aspect of the kinetics is clarified by illustrating and comparing systematically the likely role of four different factors in the synthesis kinetics in the framework of a single model taking the lateral N-N interaction into account and allowing one to scrutinize the transition from the ideal to non-ideal case at low, intermediate, and high N coverages and to identify the corresponding similarities and differences. The scale of the lateral interaction has been estimated by using the available experimentally measured and ab initio calculated heat of N adsorption on Fe.
{"title":"Ammonia synthesis: From Langmuirian to non-Langmuirian kinetics at low, intermediate, and high coverages","authors":"Vladimir P. Zhdanov","doi":"10.1016/j.cherd.2026.02.022","DOIUrl":"10.1016/j.cherd.2026.02.022","url":null,"abstract":"<div><div>Due to its high practical importance and relatively simple mechanism, synthesis of ammonia on Fe-based catalysts is paradigmatic in applied heterogeneous catalysis as well as in related academic studies. Under steady-state conditions, this process is widely considered to occur under appreciable coverage of the surface by N adatoms and to be limited by dissociative N<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> adsorption. It has been described by the kinetic models of the Temkin-Pyzhev type implying appreciable lateral N-N interactions and/or surface heterogeneity and by the Langmuirian models completely neglecting the nonideality of an adsorbed overlayer. Despite the difference of the available approaches, the fits of experiments are typically claimed to be good. Herein, this apparently surprising aspect of the kinetics is clarified by illustrating and comparing systematically the likely role of four different factors in the synthesis kinetics in the framework of a single model taking the lateral N-N interaction into account and allowing one to scrutinize the transition from the ideal to non-ideal case at low, intermediate, and high N coverages and to identify the corresponding similarities and differences. The scale of the lateral interaction has been estimated by using the available experimentally measured and <em>ab initio</em> calculated heat of N<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> adsorption on Fe.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 532-539"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171204","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: 2026-01-22DOI: 10.1016/j.cherd.2026.01.045
Damla Yalcin, Hasan Sildir
The sulphur content in crude oil has a significant impact on refinery operations, influencing the feasibility of crude blending, the distribution of product yields, and overall economic performance. Variations in sulphur content introduce uncertainty in the short-term scheduling of crude oil loading, blending, and distillation processes. This study introduces a scenario-based stochastic optimization framework in which sulphur uncertainty is treated as a central modeling element, represented through a regression-based relationship with specific gravity (SG). The approach systematically propagates uncertainty through blending decisions, crude distillation unit (CDU) feed composition, and product yields. The problem is modeled as a mixed-integer quadratically constrained programming (MIQCP) formulation within a continuous-time scheduling framework, enabling the simultaneous optimization of timing, blending, and processing strategies. The results indicate that increased sulphur uncertainty adversely affects the distribution of yields for nine end-products, resulting in profit losses. These findings underscore the importance of explicitly managing compositional uncertainty and provide insights into cost-performance trade-offs in refinery scheduling.
{"title":"Robust scheduling of crude oil farming and processing under uncertainty","authors":"Damla Yalcin, Hasan Sildir","doi":"10.1016/j.cherd.2026.01.045","DOIUrl":"10.1016/j.cherd.2026.01.045","url":null,"abstract":"<div><div>The sulphur content in crude oil has a significant impact on refinery operations, influencing the feasibility of crude blending, the distribution of product yields, and overall economic performance. Variations in sulphur content introduce uncertainty in the short-term scheduling of crude oil loading, blending, and distillation processes. This study introduces a scenario-based stochastic optimization framework in which sulphur uncertainty is treated as a central modeling element, represented through a regression-based relationship with specific gravity (SG). The approach systematically propagates uncertainty through blending decisions, crude distillation unit (CDU) feed composition, and product yields. The problem is modeled as a mixed-integer quadratically constrained programming (MIQCP) formulation within a continuous-time scheduling framework, enabling the simultaneous optimization of timing, blending, and processing strategies. The results indicate that increased sulphur uncertainty adversely affects the distribution of yields for nine end-products, resulting in profit losses. These findings underscore the importance of explicitly managing compositional uncertainty and provide insights into cost-performance trade-offs in refinery scheduling.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 354-373"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-17DOI: 10.1016/j.cherd.2026.02.040
S. Emad Renfroe , Blair K. Brettmann , Jeremy B. Lechman , Joseph M. Monti
Resonant acoustic mixers use low-frequency vertical vibration to deliver well-mixed, fine-featured granular materials without relying on mechanical agitators. We perform discrete element method simulations of dry granular materials and complementary experiments to assess the impact of vibration intensity on the formation of particle size gradients in a resonant acoustic mixer. The simulations primarily consider a broad, continuous particle size distribution that is realistic for as-procured fine-grained materials, while the experiments and supplementary simulations focus on a bimodal, 90%–10% by weight coarse-to-fine size distribution that mimics the simulated continuous size distribution material. Both methodologies indicate the emergence of radial particle size segregation (RPSS) over a range of low-intensity vibration conditions, whereas high-intensity vibration produces well-mixed states. Observed RPSS manifests as an accumulation of coarse particles near the vessel wall, with fine particles concentrating near the vessel center. Through detailed analysis of the simulation trajectories, RPSS is found to coincide with convective rolls comprised mainly of coarse particles, which preferentially expel fine particles. The simulations also show that modest axial size heterogeneity emerges during convection. Our results provide crucial insights into the mixing and demixing tendencies of fine-grained materials, where precise size control is challenging to achieve.
{"title":"Emergence of radial particle size segregation in vibrated size-disperse granular materials","authors":"S. Emad Renfroe , Blair K. Brettmann , Jeremy B. Lechman , Joseph M. Monti","doi":"10.1016/j.cherd.2026.02.040","DOIUrl":"10.1016/j.cherd.2026.02.040","url":null,"abstract":"<div><div>Resonant acoustic mixers use low-frequency vertical vibration to deliver well-mixed, fine-featured granular materials without relying on mechanical agitators. We perform discrete element method simulations of dry granular materials and complementary experiments to assess the impact of vibration intensity on the formation of particle size gradients in a resonant acoustic mixer. The simulations primarily consider a broad, continuous particle size distribution that is realistic for as-procured fine-grained materials, while the experiments and supplementary simulations focus on a bimodal, 90%–10% by weight coarse-to-fine size distribution that mimics the simulated continuous size distribution material. Both methodologies indicate the emergence of radial particle size segregation (RPSS) over a range of low-intensity vibration conditions, whereas high-intensity vibration produces well-mixed states. Observed RPSS manifests as an accumulation of coarse particles near the vessel wall, with fine particles concentrating near the vessel center. Through detailed analysis of the simulation trajectories, RPSS is found to coincide with convective rolls comprised mainly of coarse particles, which preferentially expel fine particles. The simulations also show that modest axial size heterogeneity emerges during convection. Our results provide crucial insights into the mixing and demixing tendencies of fine-grained materials, where precise size control is challenging to achieve.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 965-976"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384982","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: 2026-02-08DOI: 10.1016/j.cherd.2026.02.013
Bin Yuan , Lin Shen , Pei-Qing Yuan , Hao Ling , Xue-Dong Zhu , Rui-Jiang Li
High-purity 2-chloro-1,3-butadiene (2CP) is critical for the polymerization performance and process stability of chloroprene rubber. To enhance 2CP selectivity, we investigated the dehydrochlorination of 3,4-dichlorobut-1-ene (34DCB) by density functional theory and experiment. The E2 elimination affords three products, 2CP, (E)-1-chloro-1,3-butadiene ((E)-1CP) and (Z)-1-chloro-1,3-butadiene ((Z)-1CP). Thermodynamic analysis shows that their stabilities are very similar, indicating a limited thermodynamic contribution to selectivity. In contrast, transition-state and kinetic analyses reveal a much lower activation energy for the 2CP pathway (13.06 kJ/mol) than for the 1CP pathways (about 42 kJ/mol), so 2CP forms much faster than 1CP. Experiments under process-relevant conditions confirm that at temperatures below 313.15 K the 2CP selectivity remains above 98.5 %, with 1CP below 1.5 wt%, and is insensitive to reaction time and conversion; low-temperature conversion can be increased by extending residence time. These results establish kinetic control of 34DCB dehydrochlorination and guide highly selective 2CP production.
{"title":"Reaction-kinetics-driven process optimization for production of high-purity 2-chloro-1,3-butadiene via dehydrochlorination of 3,4-dichlorobut-1-ene","authors":"Bin Yuan , Lin Shen , Pei-Qing Yuan , Hao Ling , Xue-Dong Zhu , Rui-Jiang Li","doi":"10.1016/j.cherd.2026.02.013","DOIUrl":"10.1016/j.cherd.2026.02.013","url":null,"abstract":"<div><div>High-purity 2-chloro-1,3-butadiene (2CP) is critical for the polymerization performance and process stability of chloroprene rubber. To enhance 2CP selectivity, we investigated the dehydrochlorination of 3,4-dichlorobut-1-ene (34DCB) by density functional theory and experiment. The E2 elimination affords three products, 2CP, (<em>E</em>)-1-chloro-1,3-butadiene ((<em>E</em>)-1CP) and (<em>Z</em>)-1-chloro-1,3-butadiene ((<em>Z</em>)-1CP). Thermodynamic analysis shows that their stabilities are very similar, indicating a limited thermodynamic contribution to selectivity. In contrast, transition-state and kinetic analyses reveal a much lower activation energy for the 2CP pathway (13.06 kJ/mol) than for the 1CP pathways (about 42 kJ/mol), so 2CP forms much faster than 1CP. Experiments under process-relevant conditions confirm that at temperatures below 313.15 K the 2CP selectivity remains above 98.5 %, with 1CP below 1.5 wt%, and is insensitive to reaction time and conversion; low-temperature conversion can be increased by extending residence time. These results establish kinetic control of 34DCB dehydrochlorination and guide highly selective 2CP production.</div></div>","PeriodicalId":10019,"journal":{"name":"Chemical Engineering Research & Design","volume":"227 ","pages":"Pages 446-453"},"PeriodicalIF":3.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171200","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":"2026-03-01","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号