Development of an Improved Kinetic Model for CO2 Hydrogenation to Methanol

甲醇 催化作用 动能 热力学 等温过程 化学 动力学 化学计量学 材料科学 物理化学 有机化学 物理 量子力学
作者
Siphesihle Mbatha,Sébastien Thomas,Ksenia Parkhomenko,Anne‐Cécile Roger,Benoît Louis,Xiaoti Cui,Raymond C. Everson,Henrietta W. Langmi,Nicholas M. Musyoka,Jianwei Ren
出处
期刊:Catalysts [Multidisciplinary Digital Publishing Institute]
卷期号:13 (10): 1349-1349 被引量:3
标识
DOI:10.3390/catal13101349
摘要

The kinetics of methanol synthesis remains debatable for various reasons, such as the lack of scientifically conclusive agreement about reaction mechanisms. The focus of this paper is on the evaluation of the intrinsic kinetics of the methanol synthesis reaction based on CO2 hydrogenation and the associated reverse water–gas shift as overall reactions. The industrial methanol synthesis catalyst, Cu/ZnO/Al2O3/MgO, was used for performing the kinetic studies. An optimal kinetic model was assessed for its ability to predict the experimental data from differential to integral conditions, contrary to the typical fitting of only the integral conditions’ data (common practice, as reported in the literature). The catalyst testing and kinetic evaluations were performed at various temperatures (210–260 °C) and pressures (40–77 bar), and for different stoichiometric numbers (0.9–1.9), H2/CO2 ratios (3.0–4.4) and carbon oxide ratios (0.9–1.0), in an isothermal fixed bed reactor, operated in a plug-flow mode. Experiments with CO in the feed were also generated and fitted. Different literature kinetic models with different assumptions on active sites, rate-determining steps, and hence, model formulations were fitted and compared. The original Seidel model appeared to fit the kinetic data very well, but it has twelve parameters. The modified model (MOD) we propose is derived from this Seidel model, but it has fewer (nine) parameters—it excludes CO hydrogenation, but it takes into consideration the morphological changes of active sites and CO adsorption. This MOD model, with three active sites, gave the best fit to all the data sets.
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