Xuexue Dong, Benhuan Xu, Jian Tian, Bo Jiang, Yu Deng, Bin Chen, Yixin Li, Gen Li, Guowu Zhan
Selective deoxygenation of fatty acids to diesel-range alkanes without carbon-chain shortening is essential for sustainable biomass upgrading, but high selectivity remains challenging by competing decarbonylation/decarboxylation pathways. Here, a Re/In2O3 featuring Re single atoms and ReO3 clusters was synthesized for the hydrodeoxygenation of stearic acid. In contrast to In2O3, which primarily yields 1-octadecanol (93.1% selectivity) with minimal n-octadecane (1.2% selectivity), the optimized Re/In2O3 catalyst achieves 100% selectivity diesel-range alkanes (>85% n-octadecane). Isotopic labeling, in situ spectroscopy, and kinetic analyses reveal Re-induced synergy: ReO3 enhance H2 dissociation, while Re single atoms promote bidentate adsorption of fatty acids, and oxygen vacancies in In2O3 facilitate selective C–O bond cleavage. This multifunctional synergy suppresses C–C bond scission and significantly lowers the apparent activation energy for hydrodeoxygenation by 36.5 kJ·mol−1. The catalyst exhibits broad applicability across diverse carboxylic acids, including unsaturated and aromatic substrates, underscoring its potential for efficient biomass utilization.
{"title":"Dual-site Re/In2O3 enables selective hydrodeoxygenation of fatty acids via suppressed decarbonylation","authors":"Xuexue Dong, Benhuan Xu, Jian Tian, Bo Jiang, Yu Deng, Bin Chen, Yixin Li, Gen Li, Guowu Zhan","doi":"10.1002/aic.70304","DOIUrl":"https://doi.org/10.1002/aic.70304","url":null,"abstract":"Selective deoxygenation of fatty acids to diesel-range alkanes without carbon-chain shortening is essential for sustainable biomass upgrading, but high selectivity remains challenging by competing decarbonylation/decarboxylation pathways. Here, a Re/In<sub>2</sub>O<sub>3</sub> featuring Re single atoms and ReO<sub>3</sub> clusters was synthesized for the hydrodeoxygenation of stearic acid. In contrast to In<sub>2</sub>O<sub>3</sub>, which primarily yields 1-octadecanol (93.1% selectivity) with minimal n-octadecane (1.2% selectivity), the optimized Re/In<sub>2</sub>O<sub>3</sub> catalyst achieves 100% selectivity diesel-range alkanes (>85% n-octadecane). Isotopic labeling, in situ spectroscopy, and kinetic analyses reveal Re-induced synergy: ReO<sub>3</sub> enhance H<sub>2</sub> dissociation, while Re single atoms promote bidentate adsorption of fatty acids, and oxygen vacancies in In<sub>2</sub>O<sub>3</sub> facilitate selective C–O bond cleavage. This multifunctional synergy suppresses C–C bond scission and significantly lowers the apparent activation energy for hydrodeoxygenation by 36.5 kJ·mol<sup>−1</sup>. The catalyst exhibits broad applicability across diverse carboxylic acids, including unsaturated and aromatic substrates, underscoring its potential for efficient biomass utilization.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"81 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147371378","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}
Bingyan Wang, Menglong Zhao, Yuhan Guo, Hong Zhang, Jiahao Cao, Jie Han, Kai Cui, Wenfang Cai, Kun Guo
Coupling water electrolysis with hydrogen-oxidizing bacteria (HOB) fermentation represents a promising strategy for sustainable polyhydroxybutyrate (PHB) production and CO2 mitigation. In this study, a novel PHB-producing HOB consortium dominated by Acinetobacter was selectively enriched in a custom-designed gas-lift bioreactor supplied with electrolytic H2 and O2. The effects of nitrogen limitation, oxygen limitation, and combined nitrogen–oxygen dual limitation on PHB accumulation were systematically investigated. Results demonstrated that oxygen limitation more effectively promoted PHB accumulation compared to nitrogen limitation, while dual limitation yielded the highest PHB content (55.65% of CDW), comparable to pure cultures. Structural and compositional analyses verified successful PHB biosynthesis. Compared with reported pure and engineered strains, the enriched PHB-HOB community exhibited enhanced adaptability, lower cultivation costs, and promising scalability. These findings highlight the potential of mixed HOB consortia as an efficient and sustainable platform for PHB production from CO2, offering valuable insights into electricity-driven carbon capture and biopolymer synthesis.
{"title":"Electricity-driven CO2-to-PHB conversion via enriched hydrogen-oxidizing bacterial consortia in a gas-lift bioreactor","authors":"Bingyan Wang, Menglong Zhao, Yuhan Guo, Hong Zhang, Jiahao Cao, Jie Han, Kai Cui, Wenfang Cai, Kun Guo","doi":"10.1002/aic.70300","DOIUrl":"https://doi.org/10.1002/aic.70300","url":null,"abstract":"Coupling water electrolysis with hydrogen-oxidizing bacteria (HOB) fermentation represents a promising strategy for sustainable polyhydroxybutyrate (PHB) production and CO<sub>2</sub> mitigation. In this study, a novel PHB-producing HOB consortium dominated by <i>Acinetobacter</i> was selectively enriched in a custom-designed gas-lift bioreactor supplied with electrolytic H<sub>2</sub> and O<sub>2</sub>. The effects of nitrogen limitation, oxygen limitation, and combined nitrogen–oxygen dual limitation on PHB accumulation were systematically investigated. Results demonstrated that oxygen limitation more effectively promoted PHB accumulation compared to nitrogen limitation, while dual limitation yielded the highest PHB content (55.65% of CDW), comparable to pure cultures. Structural and compositional analyses verified successful PHB biosynthesis. Compared with reported pure and engineered strains, the enriched PHB-HOB community exhibited enhanced adaptability, lower cultivation costs, and promising scalability. These findings highlight the potential of mixed HOB consortia as an efficient and sustainable platform for PHB production from CO<sub>2</sub>, offering valuable insights into electricity-driven carbon capture and biopolymer synthesis.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"29 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147368518","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}
Understanding how viscosity modulates chaotic dynamics in microfluidic systems has remained elusive, despite its importance for high-viscosity mixing. This study investigates viscosity-dependent chaos and mixing in an oscillating feedback micromixer (OFM) through experiments and simulations. Systematic Reynolds-number correlations reveal that feedback intensity, vorticity, deformation, vortex distortion, and helicity all follow unified inertia-dominated scaling laws, indicating a common chaotic evolution mechanism linked with viscosity. Attractor reconstruction and Lyapunov analysis demonstrate the viscosity tolerance of the chaotic state, showing only a moderate attenuation of chaotic intensity once chaos is established. Within the chaotic regime, multiscale mixing metrics (mixing efficiency and norm, micromixing time) show consistent Reynolds-number-dependent scaling-law behavior, with mixing efficiency and micromixing time sharing an exponent of about 0.25. These results establish a unified viscosity-mediated Reynolds linkage among secondary flows, chaotic advection, and multiscale mixing, clarifying that viscosity primarily shifts the transition threshold while inertially intensified chaos governs mixing performance.
{"title":"Deciphering viscosity-driven mechanisms governing chaotic flow dynamics and mixing efficiency in micromixers","authors":"Shi-Xiao Wei, Ting-Liang Xie, Shuang-Feng Yin","doi":"10.1002/aic.70344","DOIUrl":"https://doi.org/10.1002/aic.70344","url":null,"abstract":"Understanding how viscosity modulates chaotic dynamics in microfluidic systems has remained elusive, despite its importance for high-viscosity mixing. This study investigates viscosity-dependent chaos and mixing in an oscillating feedback micromixer (OFM) through experiments and simulations. Systematic Reynolds-number correlations reveal that feedback intensity, vorticity, deformation, vortex distortion, and helicity all follow unified inertia-dominated scaling laws, indicating a common chaotic evolution mechanism linked with viscosity. Attractor reconstruction and Lyapunov analysis demonstrate the viscosity tolerance of the chaotic state, showing only a moderate attenuation of chaotic intensity once chaos is established. Within the chaotic regime, multiscale mixing metrics (mixing efficiency and norm, micromixing time) show consistent Reynolds-number-dependent scaling-law behavior, with mixing efficiency and micromixing time sharing an exponent of about 0.25. These results establish a unified viscosity-mediated Reynolds linkage among secondary flows, chaotic advection, and multiscale mixing, clarifying that viscosity primarily shifts the transition threshold while inertially intensified chaos governs mixing performance.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"81 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147371532","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}
Jie Yu, Haolin Cheng, Yan Fu, Jinli Zhang, Jiangjiexing Wu
Stabilizing oxygen evolution catalysts under high-current-density operation remains a key challenge for alkaline water electrolysis, where reaction kinetics, mass transport, and structural degradation are strongly coupled. Herein, we report a SiO2-modified NiFeOOH electrocatalyst that enables sustained oxygen evolution via the oxide path mechanism (OPM) by concurrent regulation of surface structure and electronic states. Silicon incorporation reconstructs surface topography and stabilizes high-valence Ni/Fe active sites, while mitigating gas-bubble accumulation and metal dissolution under demanding conditions. Operando spectroscopic combined with density functional theory calculations reveal that Si modulation lowers the energetic barrier for direct OO coupling along the OPM pathway and suppresses degradation pathways. The catalyst delivers an overpotential of 300 mV at 500 mA·cm−2 with stable operation for over 120 h, achieving overall water splitting at 1.74 and 1.87 V in a membrane flow cell. This works provides engineering insights into stabilizing oxide-pathway electrocatalysis under high-rate electrolysis.
{"title":"Silicon-modulated NiFeOOH enables stable oxide-pathway oxygen evolution under high-current-density operation","authors":"Jie Yu, Haolin Cheng, Yan Fu, Jinli Zhang, Jiangjiexing Wu","doi":"10.1002/aic.70333","DOIUrl":"https://doi.org/10.1002/aic.70333","url":null,"abstract":"Stabilizing oxygen evolution catalysts under high-current-density operation remains a key challenge for alkaline water electrolysis, where reaction kinetics, mass transport, and structural degradation are strongly coupled. Herein, we report a SiO<sub>2</sub>-modified NiFeOOH electrocatalyst that enables sustained oxygen evolution via the oxide path mechanism (OPM) by concurrent regulation of surface structure and electronic states. Silicon incorporation reconstructs surface topography and stabilizes high-valence Ni/Fe active sites, while mitigating gas-bubble accumulation and metal dissolution under demanding conditions. Operando spectroscopic combined with density functional theory calculations reveal that Si modulation lowers the energetic barrier for direct O<span></span>O coupling along the OPM pathway and suppresses degradation pathways. The catalyst delivers an overpotential of 300 mV at 500 mA·cm<sup>−2</sup> with stable operation for over 120 h, achieving overall water splitting at 1.74 and 1.87 V in a membrane flow cell. This works provides engineering insights into stabilizing oxide-pathway electrocatalysis under high-rate electrolysis.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"45 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147368517","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}
Yaxiong Yu, Feng Lu, Lin Chai, Jun Xue, Fei Wei, Chenxi Zhang
A continuum particle–wall heat transfer model is essential for continuum simulations of gas–solid fluidized beds, yet models applicable to polydisperse systems remain lacking. In this study, a modified version of the Rong and Horio discrete element method (DEM) particle–fluid–particle/wall heat transfer model was proposed by incorporating particle thermal conductivity. The modified DEM model accurately predicts the effective thermal conductivity in an experimental packed bed. Based on computational fluid dynamics–discrete element method data, a continuum particle–wall heat transfer model was developed for monodisperse systems and successfully extended to polydisperse systems by introducing a volume-averaged particle size. Additionally, a theoretical expression was established to predict the contribution of each particle component to the overall heat transfer coefficient in polydisperse beds. The model predictions agree well with simulation results, especially at relatively low fines contents (<15%). This work provides a reliable particle–wall heat transfer model for continuum simulations of polydisperse fluidized beds.
连续介质颗粒壁传热模型是气固流化床连续介质模拟的必要条件，但目前还缺乏适用于多分散系统的模型。本研究提出了一种改进的Rong and Horio离散元法（DEM）颗粒-流体-颗粒/壁面传热模型，加入了颗粒导热系数。改进的DEM模型能准确地预测实验充填床的有效导热系数。基于计算流体力学-离散元法数据，建立了单分散系统的连续颗粒-壁面传热模型，并通过引入体积平均粒径成功推广到多分散系统。此外，建立了一个理论表达式来预测各颗粒组分对多分散床层总传热系数的贡献。模型预测结果与模拟结果吻合较好，特别是在相对较低的细粒含量（<15%）下。为多分散流化床的连续模拟提供了可靠的颗粒壁传热模型。
{"title":"A continuum particle–wall heat transfer model for polydisperse fluidized beds","authors":"Yaxiong Yu, Feng Lu, Lin Chai, Jun Xue, Fei Wei, Chenxi Zhang","doi":"10.1002/aic.70338","DOIUrl":"https://doi.org/10.1002/aic.70338","url":null,"abstract":"A continuum particle–wall heat transfer model is essential for continuum simulations of gas–solid fluidized beds, yet models applicable to polydisperse systems remain lacking. In this study, a modified version of the Rong and Horio discrete element method (DEM) particle–fluid–particle/wall heat transfer model was proposed by incorporating particle thermal conductivity. The modified DEM model accurately predicts the effective thermal conductivity in an experimental packed bed. Based on computational fluid dynamics–discrete element method data, a continuum particle–wall heat transfer model was developed for monodisperse systems and successfully extended to polydisperse systems by introducing a volume-averaged particle size. Additionally, a theoretical expression was established to predict the contribution of each particle component to the overall heat transfer coefficient in polydisperse beds. The model predictions agree well with simulation results, especially at relatively low fines contents (<15%). This work provides a reliable particle–wall heat transfer model for continuum simulations of polydisperse fluidized beds.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"14 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147368520","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}
Designing organic dyes with precise spectral properties remains challenging despite their importance in downstream industries. This work introduces a machine learning framework (MMoE-CV, with MAEs <8 nm for absorption and <13 nm for emission) integrated with statistical analysis to uncover interpre- structure–property relationships. Experimental validation with newly synthesized thiadiazole derivatives confirms the model's high accuracy even for de novo compounds. Analysis of a library of 729 dye derivatives demonstrates that substituent effects are strongly modulated by both the parent chromophore scaffold and substitution position. This nuance is often overlooked in traditional design approaches. Statistical analysis reveals quantitative insights into these complex interactions, providing a novel rule framework for dye optimization. This approach bridges predictive power with chemical understanding, accelerating the discovery of functional organic dyes for applications in various areas and offering a new perspective on the integration of artificial intelligence in materials design and industrial implementation.
{"title":"Unlocking structure–property relationships in organic dyes with machine learning and statistics","authors":"Hao Wu, Zhiwei Yang, Haoyu Jiang, Qirui Yuan, Liangyin Zhao, Ran Tan, Lichun Dong, Chenyang Lu, Luxi Tan, Guanxin Zhang, Shayu Li","doi":"10.1002/aic.70318","DOIUrl":"https://doi.org/10.1002/aic.70318","url":null,"abstract":"Designing organic dyes with precise spectral properties remains challenging despite their importance in downstream industries. This work introduces a machine learning framework (MMoE-CV, with MAEs <8 nm for absorption and <13 nm for emission) integrated with statistical analysis to uncover interpre- structure–property relationships. Experimental validation with newly synthesized thiadiazole derivatives confirms the model's high accuracy even for de novo compounds. Analysis of a library of 729 dye derivatives demonstrates that substituent effects are strongly modulated by both the parent chromophore scaffold and substitution position. This nuance is often overlooked in traditional design approaches. Statistical analysis reveals quantitative insights into these complex interactions, providing a novel rule framework for dye optimization. This approach bridges predictive power with chemical understanding, accelerating the discovery of functional organic dyes for applications in various areas and offering a new perspective on the integration of artificial intelligence in materials design and industrial implementation.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360052","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}
Ahmad Mohamadiyeh, Jeffrey Peakall, Michael Fairweather, Martyn Barnes, Timothy N. Hunter
This study investigates the erosion behavior and modeling of glass particle beds under impinging jet conditions, with a focus on particle size effects and the onset of cohesion. Ultrasonic profiling is implemented to scan and measure static crater profiles. Results indicate that particle size significantly affects crater dimensions, ring peak formation, and overall crater shape. The smallest glass particles (d50 = 35 μm) studied deviate from the trends in crater size, yield stress, and analytical modeling established using larger particles, indicating the onset of cohesion effects at this small particle size. The standard erosion parameter worked well for modeling cohesionless particles down to a certain size limit, beyond which cohesive forces become significant. A new parameter, Eτ based on particle critical shear stress, is introduced for erosion modeling in this study. The transition to cohesive behavior observed in the smallest glass particles is successfully accounted for using Eτ.
{"title":"Erosion of granular sediments by submerged impinging jets: Particle size effects and cohesion onset","authors":"Ahmad Mohamadiyeh, Jeffrey Peakall, Michael Fairweather, Martyn Barnes, Timothy N. Hunter","doi":"10.1002/aic.70336","DOIUrl":"https://doi.org/10.1002/aic.70336","url":null,"abstract":"This study investigates the erosion behavior and modeling of glass particle beds under impinging jet conditions, with a focus on particle size effects and the onset of cohesion. Ultrasonic profiling is implemented to scan and measure static crater profiles. Results indicate that particle size significantly affects crater dimensions, ring peak formation, and overall crater shape. The smallest glass particles (<i>d</i><sub>50</sub> = 35 μm) studied deviate from the trends in crater size, yield stress, and analytical modeling established using larger particles, indicating the onset of cohesion effects at this small particle size. The standard erosion parameter worked well for modeling cohesionless particles down to a certain size limit, beyond which cohesive forces become significant. A new parameter, <i>E</i><sub><i>τ</i></sub> based on particle critical shear stress, is introduced for erosion modeling in this study. The transition to cohesive behavior observed in the smallest glass particles is successfully accounted for using <i>E</i><sub><i>τ</i></sub>.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"10 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360055","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}
Inyoung Hur, Daniel Casas-Orozco, Gintaras Reklaitis, Zoltan K. Nagy
This article demonstrates the integration of in-line mass spectrometry as a process analytical technology (PAT) tool with model-based soft sensors in a continuous filtration-drying carousel system for solid–liquid separation (SLS) of crystal slurries. A hybrid monitoring framework, combining real-time PAT data and model-based soft sensors via moving horizon estimation, is used to optimize process parameters and mitigate disturbances. Two disturbance scenarios—variations in critical material attributes and control variable changes—are investigated. The framework successfully monitors process disturbances and adjusts control variables to achieve desired moisture content. Additionally, it provides insights into mass and heat transfer kinetics and, when coupled with a proportional-integral controller, enables online feedback control for improved process performance. This study highlights the potential of the hybrid framework for enhancing control and optimization in continuous SLS processes.
{"title":"Monitoring and control of a continuous, integrated filtration-drying system with in-line mass spectrometry via PharmaPy","authors":"Inyoung Hur, Daniel Casas-Orozco, Gintaras Reklaitis, Zoltan K. Nagy","doi":"10.1002/aic.70291","DOIUrl":"https://doi.org/10.1002/aic.70291","url":null,"abstract":"This article demonstrates the integration of in-line mass spectrometry as a process analytical technology (PAT) tool with model-based soft sensors in a continuous filtration-drying carousel system for solid–liquid separation (SLS) of crystal slurries. A hybrid monitoring framework, combining real-time PAT data and model-based soft sensors via moving horizon estimation, is used to optimize process parameters and mitigate disturbances. Two disturbance scenarios—variations in critical material attributes and control variable changes—are investigated. The framework successfully monitors process disturbances and adjusts control variables to achieve desired moisture content. Additionally, it provides insights into mass and heat transfer kinetics and, when coupled with a proportional-integral controller, enables online feedback control for improved process performance. This study highlights the potential of the hybrid framework for enhancing control and optimization in continuous SLS processes.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360053","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}
Haolin Wu, Hongbin Liu, Bin Wang, Fan Wang, Amr F. M. Ibrahim, Miao Yu, Shenglai Zhong, Weihong Xing, Rongfei Zhou
The industrial application of microporous crystalline membranes for gas separation has been persistently hindered by the inefficiency of conventional batch synthesis. To address this limitation, we reported a continuous and ultrafast synthesis (CUS) strategy that enables the efficient production of ultrathin b-oriented MFI and SSZ-13 zeolite membranes in just 10–15 min. The resulting MFI and SSZ-13 membranes exhibited superior separation performance in n-butane/i-butane and CO2/N2 mixtures, respectively, far exceeding those of previously reported membranes. Remarkably, the CUS process achieved a two-order-of-magnitude reduction in synthesis time, a 95% decrease in energy consumption and a 98% reduction in gel consumption compared to the batch process. Process simulation using Aspen Plus confirmed that energy consumption was reduced by over 87.6% with membrane separation compared to conventional distillation for butane isomer separation. This work establishes an efficient, scalable, and economically viable pathway for industrial-scale fabrication of zeolite membranes for gas separation.
{"title":"Continuous and rapid manufacturing of ultrathin zeolite membranes with exceptional gas separation performance","authors":"Haolin Wu, Hongbin Liu, Bin Wang, Fan Wang, Amr F. M. Ibrahim, Miao Yu, Shenglai Zhong, Weihong Xing, Rongfei Zhou","doi":"10.1002/aic.70321","DOIUrl":"https://doi.org/10.1002/aic.70321","url":null,"abstract":"The industrial application of microporous crystalline membranes for gas separation has been persistently hindered by the inefficiency of conventional batch synthesis. To address this limitation, we reported a continuous and ultrafast synthesis (CUS) strategy that enables the efficient production of ultrathin <i>b</i>-oriented MFI and SSZ-13 zeolite membranes in just 10–15 min. The resulting MFI and SSZ-13 membranes exhibited superior separation performance in <i>n</i>-butane/<i>i</i>-butane and CO<sub>2</sub>/N<sub>2</sub> mixtures, respectively, far exceeding those of previously reported membranes. Remarkably, the CUS process achieved a two-order-of-magnitude reduction in synthesis time, a 95% decrease in energy consumption and a 98% reduction in gel consumption compared to the batch process. Process simulation using Aspen Plus confirmed that energy consumption was reduced by over 87.6% with membrane separation compared to conventional distillation for butane isomer separation. This work establishes an efficient, scalable, and economically viable pathway for industrial-scale fabrication of zeolite membranes for gas separation.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"26 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The amination of lignin is crucial for its high-value utilization, but conventional chemical methods suffer from low selectivity and environmental drawbacks. Here, the amination of industrial alkali lignin was achieved for the first time via a biocatalytic pathway. A cascade catalytic system was constructed based on the mechanistic analysis of lignin model compounds. Aryl alcohol oxidase (AAO) selectively oxidizes hydroxyl groups, while ω-transaminase (ω-TA) mediates the transamination of aldehyde groups. The –NH2 group ratio in nitrogen reached 93.63% in bio-aminated lignin (EAL1), reflecting a ~9% increase over chemically aminated lignin (AAL1). The enzymatic pathway enabled efficient and selective amination, avoiding byproducts and structural damage from traditional Mannich reactions. Notably, EAL1 exhibited 100% removal efficiency under the experimental conditions for low-concentration Cu(II) solution via amino-coordination chemisorption, as verified by density functional theory (DFT) calculations. This study presents a novel approach for green functionalization of lignin, demonstrating potential applications in wastewater treatment.
{"title":"Green synthesis of aminated lignin via biocatalytic pathway for removal of Cu(II) from wastewater","authors":"Zhiyi Huang, Pingxian Feng, Xiao Wu, Yaru Luo, Hui Luo, Wei Liu, Wei Wang, Huan Wang","doi":"10.1002/aic.70320","DOIUrl":"https://doi.org/10.1002/aic.70320","url":null,"abstract":"The amination of lignin is crucial for its high-value utilization, but conventional chemical methods suffer from low selectivity and environmental drawbacks. Here, the amination of industrial alkali lignin was achieved for the first time via a biocatalytic pathway. A cascade catalytic system was constructed based on the mechanistic analysis of lignin model compounds. Aryl alcohol oxidase (AAO) selectively oxidizes hydroxyl groups, while ω-transaminase (ω-TA) mediates the transamination of aldehyde groups. The –NH<sub>2</sub> group ratio in nitrogen reached 93.63% in bio-aminated lignin (EAL1), reflecting a ~9% increase over chemically aminated lignin (AAL1). The enzymatic pathway enabled efficient and selective amination, avoiding byproducts and structural damage from traditional Mannich reactions. Notably, EAL1 exhibited 100% removal efficiency under the experimental conditions for low-concentration Cu(II) solution via amino-coordination chemisorption, as verified by density functional theory (DFT) calculations. This study presents a novel approach for green functionalization of lignin, demonstrating potential applications in wastewater treatment.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"6 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360056","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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