Andrew J Medford , Todd N Whittaker , Bjarne Kreitz , David W Flaherty , John R Kitchin
{"title":"Prospects for using artificial intelligence to understand intrinsic kinetics of heterogeneous catalytic reactions","authors":"Andrew J Medford , Todd N Whittaker , Bjarne Kreitz , David W Flaherty , John R Kitchin","doi":"10.1016/j.coche.2026.101232","DOIUrl":"10.1016/j.coche.2026.101232","url":null,"abstract":"<div><div>Heterogeneous catalysis research struggles to connect intrinsic kinetics with experimentally observed behavior due to complex multiscale models, limited observability, and a many-to-one mapping between mechanisms and data. Advances in <em>operando</em> experiments, atomic-scale models, microkinetic models, and reactor simulations provide rich information, but dramatically expand model complexity and uncertainty. Artificial intelligence can reduce the human time needed for modeling by enabling ‘self-driving’ multiscale models that automate model construction, refinement, and validation across scales. Increased throughput will result in large ensembles of multiscale models that better explore parameter space, yield insight into sensitivity and uncertainty, and improve quantitative agreement between theory and experiment.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101232"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial intelligence in thermodynamics: hybrid modeling of thermophysical properties of fluids","authors":"Hans Hasse, Sebastian Schmitt, Fabian Jirasek","doi":"10.1016/j.coche.2026.101236","DOIUrl":"10.1016/j.coche.2026.101236","url":null,"abstract":"<div><div>Artificial intelligence is currently transforming thermodynamics. Hybrid models that combine machine learning (ML) with physical modeling enable predictions of thermophysical properties with unprecedented scope and accuracy. Focusing on the thermophysical properties of fluids, recent advances in this field are highlighted, covering two hybridization techniques: (i) embedding ML into physical models and (ii) incorporating physical knowledge into ML models. The discussion covers different types of thermodynamic models: (i) excess Gibbs energy models, (ii) equations of state, and (iii) force field models. The new hybrid models combine the soundness of physical models with the flexibility of ML models and give the best results when trained on large data sets, which are, however, not always available. The new hybrid models often significantly outperform widely used classical physical thermodynamic benchmark models. We have only begun to explore the new routes opened up by hybrid thermodynamic modeling; this review provides a starting point for future work in this field.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101236"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rafael Granados-Fernández , Miguel A. Rodriguez-Cano , Cristina Sáez, Justo Lobato, Manuel A. Rodrigo
{"title":"Recent progress in scaling up promising electrochemical technologies","authors":"Rafael Granados-Fernández , Miguel A. Rodriguez-Cano , Cristina Sáez, Justo Lobato, Manuel A. Rodrigo","doi":"10.1016/j.coche.2025.101206","DOIUrl":"10.1016/j.coche.2025.101206","url":null,"abstract":"<div><div>Scaling up electrochemical technologies is key to industrial adoption. Mature processes like chlor-alkali and alumina electrolysis continue evolving to address environmental concerns. Recent commercial advances include water electrolysis and hydrogen fuel cells, though efficiency improvements are needed for profitability. Most emerging technologies face challenges in stability, reproducibility, and operability under real-world conditions. Environmental treatments remain limited to demonstration scale, while CO₂ electroreduction and organic electrosynthesis are still in early development. However, growing pressure to reduce emissions and replace fossil fuels is accelerating interest in e-fuels and electro-organic production. This review highlights recent progress and key barriers in scaling electrochemical technologies toward full-scale industrial implementation.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101206"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sven M Papidocha , Andreas Burger , Varinia Bernales , Alán Aspuru-Guzik
{"title":"The elephant in the lab: synthesizability in generative small-molecule design","authors":"Sven M Papidocha , Andreas Burger , Varinia Bernales , Alán Aspuru-Guzik","doi":"10.1016/j.coche.2025.101217","DOIUrl":"10.1016/j.coche.2025.101217","url":null,"abstract":"<div><div>The design of small molecules with tailored properties is a central goal in chemistry and materials science. Recent advances in machine learning provide powerful tools to accelerate the pace of discovery. One promising avenue for acceleration involves the use of generative models that propose novel candidates for diverse optimization tasks. Despite their promise, these methods are often evaluated solely using computational benchmarks, and many studies fail to advance proposed candidates to experimental validation in the wet lab. A key reason for this gap, the elephant in the room, is the limited <em>synthesizability</em> of the generated molecules. In response, the community has recently developed various strategies to address this challenge and incorporate synthesizability into generative design workflows. In this opinion, we provide a comprehensive overview of recent contributions that explicitly tackle molecular synthesizability, highlighting notable advances. We also discuss key limitations of current approaches and outline promising directions for future research.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101217"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Amine solutions for CO2-capture: how to get from PCC to DAC?","authors":"Paul Feron , Ali Kiani","doi":"10.1016/j.coche.2026.101227","DOIUrl":"10.1016/j.coche.2026.101227","url":null,"abstract":"<div><div>The use of amine solutions for direct air capture (DAC) can draw on the extensive experience from post-combustion CO<sub>2</sub>-capture (PCC) applications. The low CO<sub>2</sub> concentration in air, however, results in the need for significantly altered process designs, different equipment and new liquid absorbents, while retaining the overall process essentials of the thermal swing-driven CO<sub>2</sub>-capture process. Here, we explore several DAC process design considerations and formulate key DAC process attributes, using publicly available results from DAC process modelling.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101227"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent developments in the application of particle-resolved CFD to fixed-bed reactors","authors":"Anthony G Dixon","doi":"10.1016/j.coche.2025.101225","DOIUrl":"10.1016/j.coche.2025.101225","url":null,"abstract":"<div><div>Particle-resolved computational fluid dynamics (PRCFD) has recently been widely adopted by multiple research groups for the mathematical modeling of fixed-bed chemical reactors. At present, simulations are limited to handling a few hundred to a thousand particles, but real fixed-bed reactors can consist of tens to hundreds of thousands of particles. The question is how to anchor PRCFD models to real-world fixed-bed reactors. This review focuses on approaches to that question, including developing the ability to obtain more useful PRCFD models by increasing the number of particles or including more realistic reaction kinetics, improving PRCFD methodology, applying PRCFD to new reactor configurations and non-spherical particle shapes, and using PRCFD to provide a fundamental understanding that can be transferred into effective continuum models at the full reactor scale. Future directions are discussed, including the use of tools such as machine learning to extend the capabilities of PRCFD modeling.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"51 ","pages":"Article 101225"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Afroditi Kourou, Siyuan Chen, Thiranya Tillekeratne, Geraldine J Heynderickx, Yi Ouyang, Kevin M Van Geem
{"title":"Direct air capture: novel contactor designs and intensification strategies","authors":"Afroditi Kourou, Siyuan Chen, Thiranya Tillekeratne, Geraldine J Heynderickx, Yi Ouyang, Kevin M Van Geem","doi":"10.1016/j.coche.2025.101199","DOIUrl":"10.1016/j.coche.2025.101199","url":null,"abstract":"<div><div>Direct air capture (DAC) plays a crucial role in mitigating climate change, although it currently faces challenges such as high costs and low efficiency. Emerging novel contactor designs aim to reduce pressure drops and minimize mass and heat transfer resistances. Recent research trends focus on intensification and integration strategies, including high-gravity technology, electrification, innovative heating methods, and combining DAC with conversion techniques. Optimizing geometry and operational conditions is essential to advance these proof-of-concept studies towards industrial application.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"50 ","pages":"Article 101199"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roberto Mennitto , Richard Blom , Maurice Dörr , Marian Rosental , Nils Rettenmaier
{"title":"Solid sorbents for direct air capture: a technological and environmental perspective","authors":"Roberto Mennitto , Richard Blom , Maurice Dörr , Marian Rosental , Nils Rettenmaier","doi":"10.1016/j.coche.2025.101195","DOIUrl":"10.1016/j.coche.2025.101195","url":null,"abstract":"<div><div>Direct air capture (DAC) is a pivotal technology for achieving net-zero emissions, yet its scalability is constrained by energy intensity and material limitations. This work critically examines the current landscape of solid sorbents for DAC, focusing on their performance, durability, and environmental impact. Key sorbent classes — amine-functionalized materials, carbonates, zeolites, and metal-organic frameworks — are evaluated in terms of CO₂ uptake, energy requirements, and life cycle emissions. A novel exergetic efficiency metric is introduced, incorporating sorbent degradation to better reflect real-world performance. Structured supports such as laminates and monoliths are discussed for their role in enhancing mass transfer and reducing pressure drop, though often at increased cost and environmental burden. Life cycle assessment (LCA) results highlight that energy consumption dominates DAC’s carbon footprint, with sorbent-related impacts becoming significant only for short-lived or energy-intensive materials. Emerging materials like hydroxylated activated carbon, along with alternative processes such as moisture swing adsorption and electrochemical DAC, offer promising pathways to reduce energy demand and improve sustainability. The work underscores the need for integrated assessments that link sorbent properties, process design, and environmental metrics from early development stages. Future research should prioritise sorbent longevity, comprehensive kinetic data, and inclusion of support structures in LCA models to enable cost-effective and climate-positive DAC deployment.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"50 ","pages":"Article 101195"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura Clarizia, Tejraj M Aminabhavi, Gunda Mohanakrishna, Nicolas Keller, Cui Y Toe
{"title":"Editorial overview: Solar photocatalytic and photoelectrochemical hydrogen evolution using novel and effective materials","authors":"Laura Clarizia, Tejraj M Aminabhavi, Gunda Mohanakrishna, Nicolas Keller, Cui Y Toe","doi":"10.1016/j.coche.2025.101194","DOIUrl":"10.1016/j.coche.2025.101194","url":null,"abstract":"","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"50 ","pages":"Article 101194"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Direct air capture of CO2: an industrial perspective","authors":"Tim M Nisbet, Alexander W van der Made","doi":"10.1016/j.coche.2025.101190","DOIUrl":"10.1016/j.coche.2025.101190","url":null,"abstract":"<div><div>Direct air capture (DAC) is a crucial carbon dioxide removal (CDR) technology for achieving net-zero emissions by balancing atmospheric CO₂ release with removal. It serves two key roles: (a) when integrated with Carbon Capture and Storage (DAC-CCS), it enables permanent CO₂ removal to offset emissions from hard-to-abate sources like aviation; and (b) when combined with Carbon Capture and Utilization (DAC-CCU), it provides non-fossil CO₂ for producing defossilized fuels and zero-carbon chemicals. To fulfill these roles, DAC systems must be scalable and economically viable. While academic studies often focus on assessing sorbent performance under a limited range of weather conditions and for limited periods, we advocate that industrial scale deployment demands DAC systems with additional key features such as low pressure drop, high reliability for long periods (years) in a wide range of weather conditions (temperature, relative humidity), resistance to fouling from particulates in air, and without loss of performance by reingestion of CO2 depleted air. These key features are more commonly addressed in patent literature by companies nearing commercialization rather than in academic publications. Moreover, DAC technologies must be capital-efficient, and use low-cost, recyclable sorbents.</div></div>","PeriodicalId":292,"journal":{"name":"Current Opinion in Chemical Engineering","volume":"50 ","pages":"Article 101190"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}