Production of Acetaldehyde via Oxidative Dehydrogenation of Ethanol in a Chemical Looping Setup

IF 4.3 Q2 ENGINEERING, CHEMICAL
Joseph C. Gebers*, Abu Farhan Bin Abu Kasim, George J. Fulham, Kien Yi Kwong and Ewa J. Marek*, 
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引用次数: 1

Abstract

A novel chemical looping (CL) process was demonstrated to produce acetaldehyde (AA) via oxidative dehydrogenation (ODH) of ethanol. Here, the ODH of ethanol takes place in the absence of a gaseous oxygen stream; instead, oxygen is supplied from a metal oxide, an active support for an ODH catalyst. The support material reduces as the reaction takes place and needs to be regenerated in air in a separate step, resulting in a CL process. Here, strontium ferrite perovskite (SrFeO3−δ) was used as the active support, with both silver and copper as the ODH catalysts. The performance of Ag/SrFeO3−δ and Cu/SrFeO3−δ was investigated in a packed bed reactor, operated at temperatures from 200 to 270 °C and a gas hourly space velocity of 9600 h–1. The CL capability to produce AA was then compared to the performance of bare SrFeO3−δ (no catalysts) and materials comprising a catalyst on an inert support, Cu or Ag on Al2O3. The Ag/Al2O3 catalyst was completely inactive in the absence of air, confirming that oxygen supplied from the support is required to oxidize ethanol to AA and water, while Cu/Al2O3 gradually got covered in coke, indicating cracking of ethanol. The bare SrFeO3−δ achieved a similar selectivity to AA as Ag/SrFeO3−δ but at a greatly reduced activity. For the best performing catalyst, Ag/SrFeO3−δ, the obtained selectivity to AA reached 92–98% at yields of up to 70%, comparable to the incumbent Veba-Chemie process for ethanol ODH, but at around 250 °C lower temperature. The CL-ODH setup was operated at high effective production times (i.e., the time spent producing AA to the time spent regenerating SrFeO3−δ). In the investigated configuration with 2 g of the CLC catalyst and 200 mL/min feed flowrate ∼5.8 vol % ethanol, only three reactors would be required for the pseudo-continuous production of AA via CL-ODH.

Abstract Image

在化学环装置中通过乙醇氧化脱氢生产乙醛
采用一种新的化学环(CL)工艺,通过乙醇的氧化脱氢(ODH)生产乙醛(AA)。这里,乙醇的ODH发生在没有气态氧流的情况下;相反,氧气由金属氧化物提供,金属氧化物是ODH催化剂的活性载体。载体材料随着反应的进行而减少,需要在单独的步骤中在空气中再生,从而产生CL过程。本文以锶铁氧体钙钛矿(SrFeO3-δ)为活性载体,银和铜均为ODH催化剂。在填充床反应器中研究了Ag/SrFeO3-δ和Cu/SrFeO3-δ的性能,该反应器在200-270°C的温度和9600 h–1的气体时空速下运行。然后将生产AA的CL能力与裸露的SrFeO3-δ(无催化剂)和包含惰性载体上的催化剂、Al2O3上的Cu或Ag的材料的性能进行比较。Ag/Al2O3催化剂在没有空气的情况下是完全无活性的,这证实了将乙醇氧化为AA和水需要从载体提供的氧气,而Cu/Al2O3逐渐被焦炭覆盖,表明乙醇裂化。裸露的SrFeO3-δ实现了与Ag/SrFeO3-Δ类似的AA选择性,但活性大大降低。对于性能最好的催化剂Ag/SrFeO3-δ,所获得的AA选择性达到92–98%,产率高达70%,与现有的Veba Chemie乙醇ODH工艺相当,但温度较低约250°C。CL-ODH装置在高效生产时间下运行(即,生产AA所花费的时间到再生SrFeO3-δ所花费的时光)。在2 g CLC催化剂和200 mL/min进料流量~5.8 vol%乙醇的研究配置中,通过CL-ODH伪连续生产AA只需要三个反应器。
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来源期刊
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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