Potential of Sorption-Enhanced Ammonia Synthesis−An Equilibrium and Reactor Modeling Study

IF 4.3 Q2 ENGINEERING, CHEMICAL
Theresa Kunz, Thomas Cholewa and Robert Güttel*, 
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Abstract

Ammonia production is one of the most important industrial chemical processes, but the synthesis reaction is strongly limited by chemical equilibrium. This is commonly compensated by applying high pressures, but large recycle ratios and purging losses are still unavoidable. Equilibrium limitations can alternatively be evaded by sorption enhancement, where NH3 is selectively removed from the reaction mixture by a solid sorbent material. One material class commonly applied in this approach are metal halides like MgCl2, as they typically show high NH3 capacity even at elevated temperatures. In this study, a thermodynamic equilibrium model based on Gibbs energy minimization is established that is able to predict the simultaneous NH3 synthesis and sorption equilibrium. After parametrization for metal chloride-based sorbents, the model is used to estimate the potential effect of sorption enhancement on the NH3 synthesis in equilibrium. For kinetic studies under realistic operating conditions, a reactor model was established using kinetics for both iron and ruthenium-based catalysts. Simulations reveal that near-full conversion is possible in sorption-enhanced NH3 synthesis under a wide range of realistic operating conditions. At thermodynamically unfavorable conditions, the process benefits from overstoichiometric amounts of sorbent as this keeps the sorbent saturation low and thus increases the sorption driving force. The integration of a sorbent material into the NH3 synthesis reaction was shown to result in increased conversion, but at the same time also allows for a higher NH3 formation rate. An increase in H2 conversion by up to 550% was found at 350 °C, 100 bar, 15,000 h–1 for twice the stoichiometrically required sorbent. While it has been demonstrated experimentally before, these findings quantify and emphasize the vast potential of sorption-enhanced NH3 synthesis under a wide range of conditions.

吸附增强氨合成的潜力-平衡和反应器建模研究
氨生产是最重要的工业化工工艺之一,但合成反应受到化学平衡的严重限制。这通常可以通过施加高压来弥补,但大的循环比率和净化损失仍然不可避免。平衡限制也可以通过吸附增强来避免,即通过固体吸附材料有选择性地从反应混合物中去除 NH3。常用于这种方法的一类材料是 MgCl2 等金属卤化物,因为即使在高温下,它们通常也具有很高的 NH3 容量。本研究建立了一个基于吉布斯能量最小化的热力学平衡模型,该模型能够同时预测 NH3 合成和吸附平衡。在对基于金属氯化物的吸附剂进行参数化之后,该模型可用于估算吸附增强对平衡状态下 NH3 合成的潜在影响。为了在实际操作条件下进行动力学研究,利用铁基和钌基催化剂的动力学建立了反应器模型。模拟结果表明,在广泛的实际操作条件下,吸附增强型 NH3 合成可实现近乎完全的转化。在热力学条件不利的情况下,吸附剂的超几何量可使工艺受益,因为这可使吸附剂饱和度保持在较低水平,从而增加吸附驱动力。在 NH3 合成反应中加入吸附剂材料不仅能提高转化率,同时还能提高 NH3 的生成率。在 350 °C、100 bar、15,000 h-1 的条件下,只需两倍于化学计量学要求的吸附剂,即可将 H2 转化率提高 550%。虽然之前已有实验证明,但这些发现量化并强调了在各种条件下吸附增强 NH3 合成的巨大潜力。
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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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