A novel multistimuli-responsive fluorescence sensor for Hg2+, P(NIPAM-co-ATU), is synthesized through copolymerization of thermoresponsive N-isopropylacrylamide (NIPAM) as the actuator unit and aggregation-induced emission (AIE)-active tetraphenylethene-5-methyluridine (ATU) as the Hg2+ recognition sensor. Owing to the formation of ATU-Hg2+-ATU metallo-base pairs, the copolymer exhibits high selectivity and affinity toward Hg2+. Through the synergistic effect of ATU-Hg2+-ATU complexation and the phase transition of PNIPAM chains, P(NIPAM-co-ATU) switches from a weak fluorescence state to a significantly enhanced fluorescence emission upon binding of Hg2+ in the environment, thus enabling specific recognition and detection. The chemical structure and stimuli-responsive properties of P(NIPAM-co-ATU) are thoroughly investigated. The copolymer containing 2.2 mol % ATU (PNA-2) exhibits good solubility in both organic solvents and aqueous solutions. As a fluorescence-enhanced probe, PNA-2 exhibits high selectivity and sensitivity toward Hg2+ over other metal ions, even when the other ions are present at 5-fold higher concentrations. It also achieves a low detection limit for trace Hg2+ (LOD = 0.87 nM). The fluorescence enhancement mechanism, attributed to the formation of ATU-Hg2+-ATU metallo-base pairs, is further investigated by using dynamic light scattering (DLS) and theoretical calculations. Moreover, due to its good biocompatibility and low cytotoxicity, PNA-2 demonstrates the ability for detecting Hg2+ in real water samples and tracking Hg2+ in living cells by bioimaging.
{"title":"Fluorescent Probe Based on Multiresponsive Amphiphilic Copolymers for Mercury Ion Detection in Real Water Samples and Bioimaging in Living Cells","authors":"Xing-Long Zhou,Pan Ou,Lin-Bing Zou,Chang-Hai Zhou,Shuang Wang,Da-Wei Pan,Zhuang Liu,Xiao-Jie Ju,Liang-Yin Chu","doi":"10.1021/acs.iecr.5c05191","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c05191","url":null,"abstract":"A novel multistimuli-responsive fluorescence sensor for Hg2+, P(NIPAM-co-ATU), is synthesized through copolymerization of thermoresponsive N-isopropylacrylamide (NIPAM) as the actuator unit and aggregation-induced emission (AIE)-active tetraphenylethene-5-methyluridine (ATU) as the Hg2+ recognition sensor. Owing to the formation of ATU-Hg2+-ATU metallo-base pairs, the copolymer exhibits high selectivity and affinity toward Hg2+. Through the synergistic effect of ATU-Hg2+-ATU complexation and the phase transition of PNIPAM chains, P(NIPAM-co-ATU) switches from a weak fluorescence state to a significantly enhanced fluorescence emission upon binding of Hg2+ in the environment, thus enabling specific recognition and detection. The chemical structure and stimuli-responsive properties of P(NIPAM-co-ATU) are thoroughly investigated. The copolymer containing 2.2 mol % ATU (PNA-2) exhibits good solubility in both organic solvents and aqueous solutions. As a fluorescence-enhanced probe, PNA-2 exhibits high selectivity and sensitivity toward Hg2+ over other metal ions, even when the other ions are present at 5-fold higher concentrations. It also achieves a low detection limit for trace Hg2+ (LOD = 0.87 nM). The fluorescence enhancement mechanism, attributed to the formation of ATU-Hg2+-ATU metallo-base pairs, is further investigated by using dynamic light scattering (DLS) and theoretical calculations. Moreover, due to its good biocompatibility and low cytotoxicity, PNA-2 demonstrates the ability for detecting Hg2+ in real water samples and tracking Hg2+ in living cells by bioimaging.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"1 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111110","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c03997
Nirmal Mallick, Venkata Sudheendra Buddhiraju, Venkataramana Runkana, Anurag S. Rathore
Accurate estimation of the overall mass transfer coefficient (kLa) in aerated stirred tank reactors remains of interest. Conventional models, especially those utilizing population balance models, frequently have sluggish convergence and high processing expenses. This study introduces an innovative computational fluid dynamics methodology that integrates an iterative transport equation for the discrete phase with models for interfacial area concentration, bubble breakup, and coalescence. We facilitate expedited kLa estimation, resulting in a 30–50% decrease in computing time. Furthermore, a temperature-dependent user-defined function (UDF) has been integrated to estimate Henry’s coefficient into the species mass transfer model to enhance the precision of dissolved gas concentration forecasts. The model predictions demonstrate significant concordance with experimental data, with an absolute error of under 8% for kLa and under 1% for oxygen saturation values. Thus, the proposed approach offers a more computationally efficient and experimentally tested approach, rendering it suitable for industrial-scale bioreactor simulations.
{"title":"A Computationally Efficient CFD Framework for Oxygen Mass Transfer Prediction in Aerated Stirred-Tank Reactors Using the Interfacial Area Concentration Model","authors":"Nirmal Mallick, Venkata Sudheendra Buddhiraju, Venkataramana Runkana, Anurag S. Rathore","doi":"10.1021/acs.iecr.5c03997","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c03997","url":null,"abstract":"Accurate estimation of the overall mass transfer coefficient (<i>k</i><sub>L</sub>a) in aerated stirred tank reactors remains of interest. Conventional models, especially those utilizing population balance models, frequently have sluggish convergence and high processing expenses. This study introduces an innovative computational fluid dynamics methodology that integrates an iterative transport equation for the discrete phase with models for interfacial area concentration, bubble breakup, and coalescence. We facilitate expedited <i>k</i><sub>L</sub>a estimation, resulting in a 30–50% decrease in computing time. Furthermore, a temperature-dependent user-defined function (UDF) has been integrated to estimate Henry’s coefficient into the species mass transfer model to enhance the precision of dissolved gas concentration forecasts. The model predictions demonstrate significant concordance with experimental data, with an absolute error of under 8% for <i>k</i><sub>L</sub>a and under 1% for oxygen saturation values. Thus, the proposed approach offers a more computationally efficient and experimentally tested approach, rendering it suitable for industrial-scale bioreactor simulations.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"41 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146116003","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c01136
Leonidas Spyrogiannopoulos,Lawien F. Zubeir,George E. Romanos,Jannis Samios
The behavior of CO2 in [Hmim+][TCM–] was studied by using Gravimetric Absorption and Molecular Dynamics, with properties recorded up to 2 MPa. Among others, we focused on the previously unexplored structure and dynamics of the system. Results are discussed regarding the characteristics of the solution’s components, their mutual interactions, and the structure around CO2. Analysis revealed complex network-like microstructures formed by ions with cages hosting CO2, whose formation depends on intermediate and greater pressure. CO2 preferentially resides near the C01 site of the imidazolium cation ring, while locations at the COT cation tail end or outer TCM– sites are less favored. We found experimentally and through simulations that the diffusivity of CO2 increases with pressure, primarily due to local structural changes around the CO2. Also, these effects are evident in the behavior of the predicted relevant translational, reorientational, and van Hove self-part correlation functions.
{"title":"Structural and Dynamic Properties of CO2 in the Room-Temperature Ionic Liquid Hmim+TCΜ– as a Function of Pressure and Concentration: A Combined Experimental and Molecular Dynamics Simulation Study","authors":"Leonidas Spyrogiannopoulos,Lawien F. Zubeir,George E. Romanos,Jannis Samios","doi":"10.1021/acs.iecr.5c01136","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c01136","url":null,"abstract":"The behavior of CO2 in [Hmim+][TCM–] was studied by using Gravimetric Absorption and Molecular Dynamics, with properties recorded up to 2 MPa. Among others, we focused on the previously unexplored structure and dynamics of the system. Results are discussed regarding the characteristics of the solution’s components, their mutual interactions, and the structure around CO2. Analysis revealed complex network-like microstructures formed by ions with cages hosting CO2, whose formation depends on intermediate and greater pressure. CO2 preferentially resides near the C01 site of the imidazolium cation ring, while locations at the COT cation tail end or outer TCM– sites are less favored. We found experimentally and through simulations that the diffusivity of CO2 increases with pressure, primarily due to local structural changes around the CO2. Also, these effects are evident in the behavior of the predicted relevant translational, reorientational, and van Hove self-part correlation functions.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"91 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111106","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c03143
Zheng Zhang,Dan Sui,Ting Xue,Man Xu,Lingling Yang,Kangjun Wang
Lanthanide (Ln)-doped upconversion nanoparticles (UCNPs) exhibit exceptional properties, are usually used to combine multiple components to achieve double fluorescent imaging and photothermal therapy, and have intrigued researchers for several years. Here, Au nanocrystals are successfully combined with UCNPs using a one-pot strategy to form a multifunctional prism-like nanoparticle (UCNP/Au NPs) with adjustable length. Despite Au being only 4% (w/w), a wide near-infrared (NIR) absorption range covers the full NIR-I and NIR-II regions and achieves a photothermal conversion efficiency (η) of up to 35.65%. Significantly, UCNP/Au NPs with varying Au contents exhibited different capabilities in NIR-triggered photothermal conversion and photoluminescence. With the increase of Au contents, the emission wavelengths of green fluorescence have remained almost untouched. Besides, UCNP/Au NPs exhibit satisfactory drug loading efficiency and cumulative release. The study proposes a concise strategy for solutions to many key issues in medical sciences.
{"title":"A Concise Design Strategy for Upconversion Nanoprisms with Tunable Photothermal Conversion and Photoluminescence","authors":"Zheng Zhang,Dan Sui,Ting Xue,Man Xu,Lingling Yang,Kangjun Wang","doi":"10.1021/acs.iecr.5c03143","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c03143","url":null,"abstract":"Lanthanide (Ln)-doped upconversion nanoparticles (UCNPs) exhibit exceptional properties, are usually used to combine multiple components to achieve double fluorescent imaging and photothermal therapy, and have intrigued researchers for several years. Here, Au nanocrystals are successfully combined with UCNPs using a one-pot strategy to form a multifunctional prism-like nanoparticle (UCNP/Au NPs) with adjustable length. Despite Au being only 4% (w/w), a wide near-infrared (NIR) absorption range covers the full NIR-I and NIR-II regions and achieves a photothermal conversion efficiency (η) of up to 35.65%. Significantly, UCNP/Au NPs with varying Au contents exhibited different capabilities in NIR-triggered photothermal conversion and photoluminescence. With the increase of Au contents, the emission wavelengths of green fluorescence have remained almost untouched. Besides, UCNP/Au NPs exhibit satisfactory drug loading efficiency and cumulative release. The study proposes a concise strategy for solutions to many key issues in medical sciences.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"327 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111107","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c04106
Sreekumar Maroor,Stepan Spatenka,Udit Gupta
Digitalization has become a growing necessity within the process industry when challenged with increasing energy prices, demand and supply market volatility, and decarbonization goals. With increasing computational power and access to process data, companies are striving to push their assets to their limits while advancing sustainability and circularity initiatives. This study presents a methodology to accelerate catalytic reactor design by developing and deploying a surrogate model within an advanced process modeling framework. A case study for the CO2 methanation reaction system has been used to demonstrate the predictive accuracy and computational efficiency of this approach. The surrogate model-based approach provides 6 times speed up, 1/5th of memory usage, and improved robustness compared to the reactor model with the discretized catalyst pellet. This work demonstrates the potential of surrogate modeling to support scalable innovation in the context of sustainable chemical process development.
{"title":"Application of Surrogate Modeling To Accelerate Design Space Exploration for Catalytic Reactor Systems","authors":"Sreekumar Maroor,Stepan Spatenka,Udit Gupta","doi":"10.1021/acs.iecr.5c04106","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c04106","url":null,"abstract":"Digitalization has become a growing necessity within the process industry when challenged with increasing energy prices, demand and supply market volatility, and decarbonization goals. With increasing computational power and access to process data, companies are striving to push their assets to their limits while advancing sustainability and circularity initiatives. This study presents a methodology to accelerate catalytic reactor design by developing and deploying a surrogate model within an advanced process modeling framework. A case study for the CO2 methanation reaction system has been used to demonstrate the predictive accuracy and computational efficiency of this approach. The surrogate model-based approach provides 6 times speed up, 1/5th of memory usage, and improved robustness compared to the reactor model with the discretized catalyst pellet. This work demonstrates the potential of surrogate modeling to support scalable innovation in the context of sustainable chemical process development.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"20 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111108","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c05007
Yichen Gu, Ge Feng, Zaixiang Xu, Mingzhe Xue, Xiaoge Peng, Wei Guo, Yanan Deng, Yang Ding, Yunyi Cao, Haoqiang Cao, Xing Zhong, Jianguo Wang
Effective chlorine and reactive oxygen species (ROS) are vital for oxidative wastewater remediation, yet conventional electrocatalysts often face activity and selectivity trade-offs. Here, a grain boundary (GB) engineering strategy is used to construct RuIrSnCoNbOx multicomponent oxides, achieving 97.0% Faradaic efficiency (FE) and over 1400 h of stability for chlorine evolution under acidic conditions. The electrocatalyst also enables simultaneous generation of effective chlorine and ROS in simulated tap water, sustaining 87.7% FE with stability approaching 160 h. Density functional theory (DFT) reveals that the RuIrSnCoNbOx GB structure facilitates dual pathways, with chlorine produced via OCl* (ηTD = 0.96 V) and ROS via the adsorbate evolution mechanism (ηTD = 1.08 V), consistent with in situ *OOH detection. Integrated into a continuous flow electrolyzer, the system ensures efficient mass transport and active zone utilization, achieving around 99% pollutant removal. This work highlights a GB engineering route to efficient and durable electrocatalysts for water treatment.
{"title":"Grain Boundary Engineering in Multicomponent Metal Oxides for the Simultaneous Generation of Effective Chlorine and Reactive Oxygen Species","authors":"Yichen Gu, Ge Feng, Zaixiang Xu, Mingzhe Xue, Xiaoge Peng, Wei Guo, Yanan Deng, Yang Ding, Yunyi Cao, Haoqiang Cao, Xing Zhong, Jianguo Wang","doi":"10.1021/acs.iecr.5c05007","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c05007","url":null,"abstract":"Effective chlorine and reactive oxygen species (ROS) are vital for oxidative wastewater remediation, yet conventional electrocatalysts often face activity and selectivity trade-offs. Here, a grain boundary (GB) engineering strategy is used to construct RuIrSnCoNbO<sub><i>x</i></sub> multicomponent oxides, achieving 97.0% Faradaic efficiency (FE) and over 1400 h of stability for chlorine evolution under acidic conditions. The electrocatalyst also enables simultaneous generation of effective chlorine and ROS in simulated tap water, sustaining 87.7% FE with stability approaching 160 h. Density functional theory (DFT) reveals that the RuIrSnCoNbO<sub><i>x</i></sub> GB structure facilitates dual pathways, with chlorine produced via OCl* (η<sub>TD</sub> = 0.96 V) and ROS via the adsorbate evolution mechanism (η<sub>TD</sub> = 1.08 V), consistent with in situ *OOH detection. Integrated into a continuous flow electrolyzer, the system ensures efficient mass transport and active zone utilization, achieving around 99% pollutant removal. This work highlights a GB engineering route to efficient and durable electrocatalysts for water treatment.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"63 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146116002","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 : 2026-02-04DOI: 10.1021/acs.iecr.6c00336
Adam McNeeley, Y. A. Liu
In Figure 16, in the top two rows of chemical reactions under Straight Chain, the reaction type for the top row should be esterification, not transesterication; and the reaction type for the second row should be transesterication, not esterification. The corrected figure appears below: Figure 16. Summary of the four primary reactions relevant in PLA and lactic acid systems. This article has not yet been cited by other publications.
{"title":"Correction to “Assessment of PLA Depolymerization for Circular Economy: Production Pathways, Physical Properties, Thermodynamics, and Kinetic Modeling”","authors":"Adam McNeeley, Y. A. Liu","doi":"10.1021/acs.iecr.6c00336","DOIUrl":"https://doi.org/10.1021/acs.iecr.6c00336","url":null,"abstract":"In Figure 16, in the top two rows of chemical reactions under Straight Chain, the reaction type for the top row should be esterification, not transesterication; and the reaction type for the second row should be transesterication, not esterification. The corrected figure appears below: Figure 16. Summary of the four primary reactions relevant in PLA and lactic acid systems. This article has not yet been cited by other publications.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"39 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115992","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c04772
Reza Salehiyan,Hyeong Yong Song,Sanaz Soleymani Eil Bakhtiari,Kyu Hyun,Mohammadreza Nofar,Islam Shyha,Dongyang Sun
Poly(lactic acid)/poly(butylene adipate-co-terephthalate) (PLA/PBAT) blends require compatibilization to reconcile stiffness with ductility, particularly after thermal histories typical of recycling. Epoxy-functional chain extenders (Joncryl ADR) are widely used, yet the interplay between blend sequence and deformation amplitude remains underexplored. We compare four routes, neat, simultaneous dosing (PLA/PBAT/ADR), and two prereaction sequences (PLA + ADR)/PBAT and (PBAT + ADR)/PLA, for PLA-rich (70/30) and balanced (50/50) compositions using small-amplitude oscillatory shear (SAOS) tests, large-amplitude oscillatory shear (LAOS) tests with Fourier-transform (FT) analysis and Chebyshev decomposition, and isothermal time-sweep tests. SAOS results show a composition-dependent optimal route; (PBAT + ADR)/PLA maximizes the linear elasticity in (70/30), whereas PLA/PBAT/ADR is superior in (50/50). Chebyshev e3 (elastic third-order coefficient) tracks intracycle strain-stiffening driven by long-chain branching and interfacial bridging, while zero-strain nonlinear parameter Q0 quantifies the overall degree of waveform distortion without distinguishing its elastic or viscous origin; consequently, Q0 and e3 can rank materials differently. Time-sweeps results indicate continued reaction for PLA/PBAT/ADR at (50/50) and thermal stability for (PBAT + ADR)/PLA at (70/30). We map these signatures to processing and recycling; the optimal sequences deliver high low-shear melt strength with bounded high-shear dissipation, provided residence time and temperature are controlled to avoid over-reaction.
{"title":"Sequence-Dependent Compatibilization in PLA/PBAT Blends with Joncryl ADR Chain Extender: Insights from Linear and Nonlinear Rheology for Recycling Efficiency and Melt Stability","authors":"Reza Salehiyan,Hyeong Yong Song,Sanaz Soleymani Eil Bakhtiari,Kyu Hyun,Mohammadreza Nofar,Islam Shyha,Dongyang Sun","doi":"10.1021/acs.iecr.5c04772","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c04772","url":null,"abstract":"Poly(lactic acid)/poly(butylene adipate-co-terephthalate) (PLA/PBAT) blends require compatibilization to reconcile stiffness with ductility, particularly after thermal histories typical of recycling. Epoxy-functional chain extenders (Joncryl ADR) are widely used, yet the interplay between blend sequence and deformation amplitude remains underexplored. We compare four routes, neat, simultaneous dosing (PLA/PBAT/ADR), and two prereaction sequences (PLA + ADR)/PBAT and (PBAT + ADR)/PLA, for PLA-rich (70/30) and balanced (50/50) compositions using small-amplitude oscillatory shear (SAOS) tests, large-amplitude oscillatory shear (LAOS) tests with Fourier-transform (FT) analysis and Chebyshev decomposition, and isothermal time-sweep tests. SAOS results show a composition-dependent optimal route; (PBAT + ADR)/PLA maximizes the linear elasticity in (70/30), whereas PLA/PBAT/ADR is superior in (50/50). Chebyshev e3 (elastic third-order coefficient) tracks intracycle strain-stiffening driven by long-chain branching and interfacial bridging, while zero-strain nonlinear parameter Q0 quantifies the overall degree of waveform distortion without distinguishing its elastic or viscous origin; consequently, Q0 and e3 can rank materials differently. Time-sweeps results indicate continued reaction for PLA/PBAT/ADR at (50/50) and thermal stability for (PBAT + ADR)/PLA at (70/30). We map these signatures to processing and recycling; the optimal sequences deliver high low-shear melt strength with bounded high-shear dissipation, provided residence time and temperature are controlled to avoid over-reaction.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"8 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111109","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}
Linear α-olefins are important feedstocks in industry, and the critical challenge of their production lies in the separation of multicomponent α-olefins/paraffins. Currently, most research focused on binary α-olefin/paraffin systems, and the lack of understanding about the multicomponent α-olefins/paraffins hinders the development of adsorption technologies. Here, we investigated the competitive adsorption behavior of C6–C8 α-olefins/paraffins based on 13X zeolites, and it exhibited preferential adsorption toward 1-hexene, 1-heptene, and 1-octene than corresponding paraffins, as evidenced by the batch adsorption experiments and pulse experiments. To balance the competitive adsorption behavior among α-olefins, the mixed desorbent of 1-decene/n-decane was designed to realize the separation with optimized separation resolutions of α-olefins/paraffins and olefins. A 16-column simulated moving bed process was established guided by the pulse experiments on a scale-up column, and 99% purity C6–C8 α-olefins with 99% yield were obtained. This work reveals an energy-efficient adsorption process for C6–C8 α-olefins and paraffins with potential industrial use.
{"title":"Efficient Separation of Multicomponent C6–C8 α-Olefins and Paraffins on 13X Zeolite by Tuning Competitive Adsorption","authors":"Yifan Jin,Senming Lin,Xili Cui,Xian Suo,Xiaofei Lu,Anyun Zhang,Lifeng Yang,Huabin Xing","doi":"10.1021/acs.iecr.5c04660","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c04660","url":null,"abstract":"Linear α-olefins are important feedstocks in industry, and the critical challenge of their production lies in the separation of multicomponent α-olefins/paraffins. Currently, most research focused on binary α-olefin/paraffin systems, and the lack of understanding about the multicomponent α-olefins/paraffins hinders the development of adsorption technologies. Here, we investigated the competitive adsorption behavior of C6–C8 α-olefins/paraffins based on 13X zeolites, and it exhibited preferential adsorption toward 1-hexene, 1-heptene, and 1-octene than corresponding paraffins, as evidenced by the batch adsorption experiments and pulse experiments. To balance the competitive adsorption behavior among α-olefins, the mixed desorbent of 1-decene/n-decane was designed to realize the separation with optimized separation resolutions of α-olefins/paraffins and olefins. A 16-column simulated moving bed process was established guided by the pulse experiments on a scale-up column, and 99% purity C6–C8 α-olefins with 99% yield were obtained. This work reveals an energy-efficient adsorption process for C6–C8 α-olefins and paraffins with potential industrial use.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"41 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111111","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 : 2026-02-04DOI: 10.1021/acs.iecr.5c04493
Yi Dai,Andrew Allman
Distributed modular process systems are gaining prominence across various industries due to their flexibility, scalability, and potential for localized deployment. These architectures are particularly relevant in contexts such as biomass processing, where decentralized, small-scale units are better suited to handle heterogeneous and spatially distributed feedstocks. However, such systems present complex control challenges, particularly in managing real-time configuration decisions. To address this, we propose a machine learning-enhanced model predictive control (MPC) framework tailored for modular reactor systems. Classical classifiers, including k-nearest neighbors, decision trees, and support vector machines, are employed to predict optimal system configurations at each control step. To improve robustness, we incorporate a modified AdaBoost algorithm guided by a performance metric, which favors configuration decisions that minimize performance degradation even under misclassification. The framework is validated on a benchmark nonisothermal CSTR system with multiple feasible configurations. Results show that k-nearest neighbors offers the best overall prediction accuracy, while support vector machines demonstrate superior robustness in worst-case scenarios, revealing a trade-off between accuracy and resilience. The AdaBoost-enhanced MPC further improves tracking performance and reduces the degradation of misclassifications. While applicable to a broad range of modular process systems, this approach is particularly promising for biomass processing applications, where heterogeneity and decentralized operations make robust, flexible control essential.
{"title":"Learning Dynamic Reconfiguration for Distributed Modular Process Systems","authors":"Yi Dai,Andrew Allman","doi":"10.1021/acs.iecr.5c04493","DOIUrl":"https://doi.org/10.1021/acs.iecr.5c04493","url":null,"abstract":"Distributed modular process systems are gaining prominence across various industries due to their flexibility, scalability, and potential for localized deployment. These architectures are particularly relevant in contexts such as biomass processing, where decentralized, small-scale units are better suited to handle heterogeneous and spatially distributed feedstocks. However, such systems present complex control challenges, particularly in managing real-time configuration decisions. To address this, we propose a machine learning-enhanced model predictive control (MPC) framework tailored for modular reactor systems. Classical classifiers, including k-nearest neighbors, decision trees, and support vector machines, are employed to predict optimal system configurations at each control step. To improve robustness, we incorporate a modified AdaBoost algorithm guided by a performance metric, which favors configuration decisions that minimize performance degradation even under misclassification. The framework is validated on a benchmark nonisothermal CSTR system with multiple feasible configurations. Results show that k-nearest neighbors offers the best overall prediction accuracy, while support vector machines demonstrate superior robustness in worst-case scenarios, revealing a trade-off between accuracy and resilience. The AdaBoost-enhanced MPC further improves tracking performance and reduces the degradation of misclassifications. While applicable to a broad range of modular process systems, this approach is particularly promising for biomass processing applications, where heterogeneity and decentralized operations make robust, flexible control essential.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"20 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111115","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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