Understanding catalytic CO₂ and CO conversion into methanol using computational fluid dynamics

Abstract

The kinetics of methanol synthesis from a mixture of CO2/CO/H2 have been widely studied in the literature. Yet the role of direct CO hydrogenation is still unclear, in terms of...

Development of an Improved Kinetic Model for CO2 Hydrogenation to Methanol

“…Methanol is industrially produced from syngas following the three main equilibrium reactions, as expressed by Equations ( 1)- (3), over an industrial Cu/ZnO/Al 2 O 3 catalyst. However, it has been recently demonstrated that methanol can also be successfully produced from a feed with pure CO 2 /H 2 (via Equation ( 1)), even though the actual reaction mechanism and carbon source for methanol remains an active topic of debate [2,[8][9][10][16][17][18][19][20]. CO…”

“…Kyrimis et al [2] compared the performance of recent models (with and without CO hydrogenation), including the model of Park et al [23] and Nestler et al [10], to establish the role of CO hydrogenation and to better understand which model performs better using a CFD model. The advantage of CFD modeling is that it gives important insights into the species concentrations, temperature profile, and reaction rate magnitude, which are not easy to derive from physical experiments [2].…”

“…Methanol is a versatile chemical for both grid stabilization and valorization of CO 2 [1,2]. It is industrially produced from a syngas mixture (CO/CO 2 /H 2 ) over a Cu/ZnO/Al 2 O 3 catalyst at 50-100 bar and 200-300 • C [1].…”

“…Model complexity is a serious concern when it comes to applying these models in reactor modeling using computational fluid dynamics (CFD) platforms because they can introduce a computationally tedious non-linear coupling [2]. However, with advances in artificial intelligence techniques such as neural networks, there are reasons to believe that the model complexity will be tackled.…”

Quantifying the Impact of Intraparticle Convection within Fixed Beds Formed by Catalytic Particles with Low Macro-Porosities

“…Fixed bed systems involve a broad range of length scales, , spanning the nanometer molecular interactions between reagents and active sites, to the local (cm-scale) and global (up to m-scale) temperature hot spots and pressure drop, all of which need to be understood. In recent years, computational fluid dynamics (CFD) models have been instrumental in the advancement of fixed bed chemical reactors, which are utilized both as investigative and as optimization tools. ,− In particle-resolved CFD (PR-CFD) models, realistic particle arrangements are generated primarily through the discrete element method (DEM), ,, and the individual particles are resolved and meshed. Particle sizes and shapes within the packed bed can either be mono- − or poly-dispersed − in nature, with modern DEM-based beds implementing multiple particle shapes, such as spherical, cylindrical, or Raschig rings. ,,,,− PR-CFD models yield key information regarding the interconnected nature of the physicochemical phenomena during operation of the fixed bed system. ,, Specifically, their ability to consider the impact of the geometrical bed structure to predict the interparticle heat and mass transfer yields highly valuable insights for reactor engineering. − Fixed bed reactors include different levels of “porosity” (Figure ).…”