AIChE JournalPub Date : 2026-10-01DOI: 10.1002/aic.70672
Luyang Liu, Ritu Ranjan, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan
{"title":"Development and experimental validation of a predictive resilient framework for cyber‐physical systems","authors":"Luyang Liu, Ritu Ranjan, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan","doi":"10.1002/aic.70672","DOIUrl":"https://doi.org/10.1002/aic.70672","url":null,"abstract":"Cyber‐physical process systems integrate process dynamics, control, sensing, actuation, and communication, making them vulnerable to attacks that falsify data, alter control actions, or disrupt networks and drive operations toward unsafe states. This work presents a safety‐focused resilience framework that adds an independent protection layer to existing control systems. Using trusted state and controller‐output measurements, a controller digital twin (DT) checks whether control actions are consistent, while a process DT predicts future behavior after detecting a compromise. These predictions are assessed using the minimum safety margin and the time to minimum safety margin, which indicate risk severity and urgency and classify conditions as Safe, Possible Critical, or Safety Critical. Mitigation actions are chosen when they can restore an acceptable safety margin; otherwise, the system proceeds to safe shutdown. Simulated continuous stirred‐tank reactor and experimental continuous stirred‐tank heater studies show the layer detects attacks, supports recovery, and triggers automatic shutdown when needed.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"80 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149085992","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}
AIChE JournalPub Date : 2026-10-01DOI: 10.1002/aic.70678
Jie Wang, Chenglu Shan, Yu Ren, Yao Yang, Xiaoqiang Fan, Binbo Jiang, Zhengliang Huang, Jingdai Wang, Yongrong Yang
{"title":"A novel acceleration approach for free radical polymerization simulation: Coupled pre‐sequencing Monte Carlo model","authors":"Jie Wang, Chenglu Shan, Yu Ren, Yao Yang, Xiaoqiang Fan, Binbo Jiang, Zhengliang Huang, Jingdai Wang, Yongrong Yang","doi":"10.1002/aic.70678","DOIUrl":"https://doi.org/10.1002/aic.70678","url":null,"abstract":"Monte Carlo (MC) simulation is one of the most powerful methods for predicting the detailed molecular architecture of free radical polymerization products, but its efficiency is severely limited by stepwise random selection of massive elementary reactions. To address this challenge, we propose an accelerated approach termed the coupled pre‐sequencing MC model. Unlike previous hybrid models, the proposed approach first completes the deterministic calculation of reaction rates throughout the entire reaction process and converts the elementary reaction rates into reaction counts within each coarse‐grained unit. The detailed chain structure information lost in the deterministic model is then recovered through MC simulation. To further enhance the efficiency of this process, a unique pre‐sequencing strategy is designed, which includes executing initiator decomposition in advance, treating propagation reactions as a queue, and inserting low‐frequency reactions. Simulation results for LDPE and EVA production demonstrate high accuracy and substantially reduced computational cost.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"225 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086262","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}
{"title":"Physics‐constrained artificial intelligence for accelerating experimental discovery of MOFs in gas separation","authors":"Dongming Huan, Chenkai Gu, Yawei Gu, Bingbo Shen, Rujing Hou, Jing Zhong, Yichang Pan, Weihong Xing","doi":"10.1002/aic.70680","DOIUrl":"https://doi.org/10.1002/aic.70680","url":null,"abstract":"Metal–organic frameworks (MOFs) hold great potential for low‐energy gas separation, but the enormous chemical space of MOFs poses a major screening challenge. Existing artificial intelligence (AI) methods suffer from high data demand and poor extrapolation capability. To address this, we develop a physics‐constrained neural network (PCNN) for propylene/propane separation that integrates physical knowledge into the model, balancing prediction accuracy and physical rationality. The PCNN achieves comparable accuracy with <10% training data of conventional models and exhibits excellent extrapolation performance. Guided by PCNN prediction, we experimentally synthesized a MOF with an ultrahigh C <jats:sub>3</jats:sub> H <jats:sub>6</jats:sub> /C <jats:sub>3</jats:sub> H <jats:sub>8</jats:sub> IAST selectivity of 3.5 × 10 <jats:sup>5</jats:sup> , demonstrating the effectiveness of this method for data‐efficient MOF screening.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"6 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086264","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}
AIChE JournalPub Date : 2026-09-30DOI: 10.1002/aic.70673
Yan Sun, Shangwei Ma, Yiou Wang, Bruno Chaudret, Tejraj Aminabhavi, Helei Liu
{"title":"Direct conversion of captured CO 2 into syngas via interface‐coupled carbonate activation in dual‐functional materials","authors":"Yan Sun, Shangwei Ma, Yiou Wang, Bruno Chaudret, Tejraj Aminabhavi, Helei Liu","doi":"10.1002/aic.70673","DOIUrl":"https://doi.org/10.1002/aic.70673","url":null,"abstract":"Integrated carbon capture and utilization can reduce the energy penalty of CO <jats:sub>2</jats:sub> valorization, but is often limited by slow transport between capture and catalytic sites. Here, we report a proximity‐engineered dual‐functional material for direct conversion of captured CO <jats:sub>2</jats:sub> into syngas via isothermal calcium‐looping dry reforming of methane at 650°C. Embedding trace Ni into a CaO framework and introducing CeO <jats:sub>2</jats:sub> creates abundant Ni–Ce–Ca interfacial sites with shortened carbonate diffusion pathways, enhanced oxygen mobility, and improved resistance to sintering and coking. The optimized material achieves a CO <jats:sub>2</jats:sub> capture capacity of 12.6 mmol g <jats:sup>−1</jats:sup> and a syngas yield of 58 mmol g <jats:sup>−1</jats:sup> , representing up to a 2.9‐fold improvement over conventional materials. Operando spectroscopy and density functional theory reveal that captured carbonates are directly converted through a lower‐energy COOH‐mediated interfacial pathway, demonstrating an effective strategy to overcome transport limitations in integrated CO <jats:sub>2</jats:sub> capture and conversion.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149085993","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}
AIChE JournalPub Date : 2026-09-29DOI: 10.1002/aic.70663
Zhicong Fang, Xiaopo Cheng, Hui Geng, Jiaze Ma
{"title":"Process‐informed co‐optimization of liquid air energy storage and data centers under off‐design thermodynamic operation","authors":"Zhicong Fang, Xiaopo Cheng, Hui Geng, Jiaze Ma","doi":"10.1002/aic.70663","DOIUrl":"https://doi.org/10.1002/aic.70663","url":null,"abstract":"The rapid growth of AI data centers (AIDCs) is intensifying stress on power systems and exposing operators to volatile electricity markets. This work develops a process‐informed co‐optimization framework that integrates liquid air energy storage (LAES) with AIDC operation. Unlike black‐box storage models, the proposed formulation captures LAES thermodynamics through charging start‐up dynamics and off‐design discharge behavior, linking process efficiency with dispatch decisions. The model is formulated as a mixed‐integer program with a robust extension for joint participation in energy and reserve markets. Results across CAISO, PJM, and ERCOT show that LAES–AIDC integration reduces operating costs by 9%–50.9% in energy markets and up to 66.1% when reserve services are included. The analysis reveals that optimal operation is governed not only by price signals but also by maintaining LAES near efficient thermodynamic regimes, with AIDC workload flexibility shaping demand to support process performance.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"11 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086153","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}
AIChE JournalPub Date : 2026-09-29DOI: 10.1002/aic.70665
Shuang Li, Yujing You, Wenlong Yang, Zhecheng Fang, Yujie Song, Jie Fu
{"title":"Functional compartmentalization in asymmetric Co–Ni microenvironment for selective CO 2 ‐to‐ C 2 H 4 photoreduction","authors":"Shuang Li, Yujing You, Wenlong Yang, Zhecheng Fang, Yujie Song, Jie Fu","doi":"10.1002/aic.70665","DOIUrl":"https://doi.org/10.1002/aic.70665","url":null,"abstract":"Photocatalytic CO <jats:sub>2</jats:sub> ‐to‐C <jats:sub>2</jats:sub> H <jats:sub>4</jats:sub> conversion faces a kinetic paradox in which enriching C <jats:sub>1</jats:sub> intermediates for C–C coupling inherently compromises their hydrogenation and product release due to strong surface binding. Here, we resolve this paradox through sulfur‐vacancy (Vs) engineering in CoNi <jats:sub>2</jats:sub> S <jats:sub>4</jats:sub> nanosheets, which creates a functionally compartmentalized Co–Ni microenvironment. Vs induces directional charge transfer from Ni to Co, generating adjacent electron‐deficient Ni(δ+) and electron‐rich Co(δ‐) sites. Ni(δ+) selectively stabilizes *CO while Co(δ‐) drives its hydrogenation to *CHO, enabling a spatially confined *CO–*CHO coupling pathway with a markedly lower thermodynamic barrier than direct *CO dimerization. Meanwhile, this microenvironment weakens C <jats:sub>2</jats:sub> H <jats:sub>4</jats:sub> adsorption relative to the pristine surface, alleviating product inhibition and promoting active‐site regeneration. The catalyst achieves a C <jats:sub>2</jats:sub> H <jats:sub>4</jats:sub> evolution rate of 57.24 μmol·g <jats:sup>−1</jats:sup> ·h <jats:sup>−1</jats:sup> with 75.81% selectivity, a 28‐fold enhancement over pristine CoNi <jats:sub>2</jats:sub> S <jats:sub>4</jats:sub> . This work establishes defect‐engineered geometric and electronic complementarity as a design paradigm for selective multicarbon photosynthesis.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"465 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086154","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}
AIChE JournalPub Date : 2026-09-29DOI: 10.1002/aic.70643
Zheqing Huang, Yuxuan Zhao, Jinxin Ma, Qiang Zhou
{"title":"Filtered reaction rate model incorporating intraparticle diffusion for reactive gas–solid flows","authors":"Zheqing Huang, Yuxuan Zhao, Jinxin Ma, Qiang Zhou","doi":"10.1002/aic.70643","DOIUrl":"https://doi.org/10.1002/aic.70643","url":null,"abstract":"This work pursues an integrated filtered reaction rate (FRR) model that incorporates intraparticle diffusion effectiveness factor ( <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> ) into a framework combining reaction kinetics regime (KR) and external mass transfer regime (EMTR) via fine‐grid two‐fluid model (TFM) simulations. Simulation results indicate that the modified Damköhler number remains a reliable criterion for distinguishing between KR and EMTR. Within the KR, the FRR model that neglects <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> overestimates the mesoscale effectiveness factor ( <jats:italic>η</jats:italic> <jats:sub>Δ</jats:sub> ) when <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> < 0.5, though these effects become negligible at <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> >0.5. This overestimation is attributed to the increase in the Damköhler number with decreasing <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> , which subsequently results in a lower <jats:italic>η</jats:italic> <jats:sub>Δ</jats:sub> . Accordingly, an integrated FRR model incorporating <jats:italic>η</jats:italic> <jats:sub> <jats:italic>I</jats:italic> </jats:sub> is proposed. Coarse‐grid TFM simulations demonstrate that the FRR model without intraparticle diffusion yields only modest improvements, whereas the version integrated with intraparticle diffusion achieves substantially better agreement with the filtered fine‐grid TFM results.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"79 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086194","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}
AIChE JournalPub Date : 2026-09-25DOI: 10.1002/aic.70636
Zhenyi Zhao, Tianyi Zhao, Sai Chen, Xianhui Wang, Zelin Wu, Mengyuan Wang, Kaige Tian, Pengyu Xiang, Chunlei Pei, Jinlong Gong
{"title":"Kinetic analysis of chemical looping oxidative propane dehydrogenation at relatively low temperature","authors":"Zhenyi Zhao, Tianyi Zhao, Sai Chen, Xianhui Wang, Zelin Wu, Mengyuan Wang, Kaige Tian, Pengyu Xiang, Chunlei Pei, Jinlong Gong","doi":"10.1002/aic.70636","DOIUrl":"https://doi.org/10.1002/aic.70636","url":null,"abstract":"Chemical looping oxidative propane dehydrogenation (CL‐ODH) as a potentially efficient strategy for propylene production is determined by the gas–solid reaction kinetics. This article describes a macroscopic kinetic model for CL‐ODH over the VCeAl oxygen carrier. Specifically, a comprehensive kinetic model is established to quantify the concurrent pathways of lattice oxygen‐mediated ODH and the catalytic propane dehydrogenation (PDH) over reduced sites as a function of solid conversion. At relatively low temperatures (470–515°C), CL‐ODH gradually evolves from ODH to stable PDH, while ODH has a relatively low activation energy than PDH. It is found that a lower temperature can result in a higher ratio of ODH in comparison with PDH, while higher propane pressure accelerates lattice oxygen depletion and shifts the reaction toward the PDH regime. The macro‐kinetic model could facilitate the industrial scale‐up of CL‐ODH processes.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"3 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048879","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}
{"title":"Unraveling the role of Zn species in catalyst deactivation and coke formation over Zn/ HZSM ‐5 during LDPE pyrolysis","authors":"Hao Liu, Xuanshen Shen, Yixian Zhao, Yu Wang, Ruibin Yuan, Ning Deng, Jian Wang, Liangyuan Jia","doi":"10.1002/aic.70667","DOIUrl":"https://doi.org/10.1002/aic.70667","url":null,"abstract":"Zn/HZSM‐5 enables selective LDPE pyrolysis to monocyclic aromatics with minimal light olefins, yet suffers from rapid coke‐induced deactivation. This study clarifies the dynamic evolution of Zn species governing this process. Isolated Zn sites drive deep dehydrogenation, generating acetylene and diene intermediates that accelerate polycyclic aromatic hydrocarbons (PAHs, coke precursors) formation. Crucially, oxygenated additives in LDPE degrade over acid sites to form intermediates that lower the energy barrier for PAH condensation, further exacerbating coking. Coke distribution is spatially heterogeneous: external surfaces accumulate long‐chain alkenes and oxygenates, while micropores foster condensed aromatics via sequential HACA and MAC mechanisms. Progressive coking encapsulates and sinters active [ZnOH] <jats:sup>+</jats:sup> into inert ZnO, triggering a switch from Zn‐driven aromatization to Brønsted acid‐dominated cracking. These findings reveal an intrinsic trade‐off where sites enabling high selectivity simultaneously dictate rapid deactivation, guiding the design of robust catalysts for plastic upcycling.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"19 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048880","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}
{"title":"Machine learning‐assisted design of low‐energy, high‐efficiency nonaqueous amine solutions","authors":"Xinping Yang, Juntao Wang, Yiming Zhao, Yongchun Zhang, Anmin Liu, Qilei Liu, Chong Peng","doi":"10.1002/aic.70668","DOIUrl":"https://doi.org/10.1002/aic.70668","url":null,"abstract":"Conventional aqueous alkanolamines suffer from high regeneration energy, corrosion, and solvent degradation, limiting large‐scale CO <jats:sub>2</jats:sub> capture. Here, a machine‐learning‐assisted strategy was developed to screen nonaqueous absorbents from a limited experimental dataset by correlating molecular structure with CO <jats:sub>2</jats:sub> desorption performance. The identified 2‐(butylamino)ethanol (BEA)‐tetramethylethylenediamine (TMEDA) system achieved a desorption capacity of 0.668 mol CO <jats:sub>2</jats:sub> ·mol <jats:sup>−1</jats:sup> amine and a maximum desorption rate of 0.0513 mol CO <jats:sub>2</jats:sub> ·mol <jats:sup>−1</jats:sup> amine·min <jats:sup>−1</jats:sup> , while exhibiting good cyclic stability, low‐temperature performance, and low corrosivity. Its regeneration energy requirement was only 1.38 GJ·t <jats:sup>−1</jats:sup> CO <jats:sub>2</jats:sub> , 62.3% lower than that of aqueous monoethanolamine. Quantitative <jats:sup>13</jats:sup> C NMR spectroscopy and density functional theory calculations revealed that BEA governs CO <jats:sub>2</jats:sub> fixation, whereas TMEDA acts as a proton acceptor, facilitates proton transfer, destabilizes the intermediate products, and lowers the heat of reaction. This work establishes a data‐driven and mechanistically informed framework for the rational development of energy‐efficient nonaqueous absorbents for CO <jats:sub>2</jats:sub> capture.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"52 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048847","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}