用于内热化学过程的电气化催化剂:材料需求、进展与挑战

IF 4.3 Q2 ENGINEERING, CHEMICAL ACS Engineering Au Pub Date : 2023-12-11 DOI:10.1021/acsengineeringau.3c00051
Meghana Idamakanti, Elmer B. Ledesma, Ram R. Ratnakar, Michael P. Harold, Vemuri Balakotaiah and Praveen Bollini*, 
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引用次数: 0

摘要

目前,大规模的内热化学工艺采用的是通过燃烧化石燃料从外部加热的管式反应器,是一种高碳密集型工艺。焦耳加热反应器是利用流经催化剂的电流通过内部加热直接提供热能的反应器,这种反应器正在迅速崛起,成为这些传统外部加热反应器的替代品。焦耳加热反应器有助于显著提高模块化程度,同时减少与这些热焓要求高的工艺相关的资本、能源和碳足迹。然而,开发这些新型反应器的前提是克服通过电流穿过催化剂基质来提供热量时所遇到的催化剂设计难题。我们在此回顾了近期在催化剂设计方面取得的一些重要进展,并强调了对所提出的新型反应器运行模式至关重要的注意事项。我们概述了所提出的各类电加热催化剂、其合成方法以及焦耳加热催化剂在各种应用中的反应器性能。此外,我们还讨论了可能需要解决的关键知识差距,以努力加快这一类新兴反应器的部署,它们可在能源密集型大规模化学过程的脱碳过程中发挥关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Electrified Catalysts for Endothermic Chemical Processes: Materials Needs, Advances, and Challenges

Large-scale endothermic chemical processes, as currently practiced, employ tubular reactors that are heated externally through the combustion of fossil fuels, and are highly carbon-intensive. Joule-heated reactors in which electric currents flowing through the catalyst are used to provide thermal energy directly through internal heating are rapidly emerging as an alternative to these conventional, externally heated reactors. Joule-heated reactors could help significantly improve modularity and also reduce the capital, energy, and carbon footprint associated with these enthalpically demanding processes. Development of these novel types of reactors, however, is predicated on overcoming catalyst design challenges encountered uniquely when supplying heat through the use of electric currents passing through catalyst substrates. We review herein some key advancements in catalyst design that have been achieved in the recent past, and highlight considerations critical to the novel mode of reactor operation proposed. We provide an overview of the various types of electrically heated catalysts proposed, methods used in their synthesis, and reactor performance of Joule-heated catalysts for a variety of applications. Also discussed are key knowledge gaps that will likely need to be addressed in an effort to accelerate deployment of this emerging class of reactors that could play a pivotal role in the decarbonization of energy-intensive large-scale chemical processes.

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ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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