Interaction of catalytic chemistry and transport inside and around porous catalyst pellets for CO2 methanation under enforced dynamic operation

未来燃料和化学品的生产将面临能源和原材料供应的波动。在power-to-X等工艺应用中，与目前使用化石燃料和能源的反应器相比，催化反应器更容易受到动态边界条件的影响，例如启动、关闭或负载变化。碳氧化物的动态加氢生成甲烷（甲烷化）就是这样一个例子，催化反应器必须动态运行。为了正确地设计这一动态过程，需要对所有相关长度和时间尺度上的物理和化学过程有深刻的理解。虽然过去有许多理论和实验工作致力于纳米尺度（催化剂和活性位点动力学）和宏观尺度（瞬态条件下的反应器动力学）的催化过程，但相对而言，很少有研究关注中尺度（颗粒间和颗粒内动力学）的动力学效应。特别是，在强制瞬态操作下，单个催化球团内部与周围流场耦合的扩散和反应之间的相互作用知之甚少。因此，我们假设只有结合详细的操作实验和详细的CFD建模，我们才能在球团水平上理解动态甲烷化过程。基于这些详细的单颗粒见解，我们可以得出充填床中发生的时空模式。因此，我们通过实验和CFD模型研究了具有定义的动态进料条件的孤立单颗粒。利用毛细管采样技术，我们量化了在广泛的操作和扰动条件下球团内部和边界气层中的动态局部温度和浓度分布。此外，红外热像仪量化了颗粒的表面温度。利用这一庞大的数据集，我们开发并验证了一个瞬态单颗粒CFD模型，该模型将周围的气体流动与颗粒内部的三维反应扩散模型相耦合。此外，实验和CFD装置扩展到模拟填充床岩心部分的颗粒阵列。这将我们的单一颗粒发现与工业操作的甲烷化固定床反应器联系起来。最后，我们应用系统辨识工具来描述摄动下球团的动态响应。

Future production of fuels and chemicals will face fluctuating energy and raw materials supply. In process applications like power-to-X, catalytic reactors will more often be subjected to dynamic boundary conditions such as start-up, shutdown or load changes than current reactors running on fossil fuels and energy. The dynamic hydrogenation of carbon oxides to methane (methanation) is one such example for which catalytic reactors will have to be operated dynamically. A profound understanding of physical and chemical processes is needed on all relevant length and time scales in order to design this dynamic process properly. While much theoretical and experimental work has been devoted in the past to catalytic processes on the nano-scale (catalyst and active site dynamics) and on the macro-scale (reactor dynamics under transient conditions), comparably few studies focused on dynamic effects on the meso-scale (inter- and intraparticle dynamics). In particular, the interplay between diffusion and reaction inside a single catalytic pellet coupled with the surrounding flow field under enforced transient operation is poorly understood. Therefore, we hypothesize that only with a combined approach uniting detailed operando experiments and detailed CFD modeling, we are able to understand the dynamic methanation process on the pellet level. Based on these detailed single pellet insights, we can conclude on spatiotemporal patterns occurring in packed beds. We therefore study an isolated single pellet with defined dynamic feed conditions, both with experiments and with CFD models. With the capillary sampling technique, we quantify the dynamic local temperature and concentration profiles inside the pellet and in the boundary gas layer over a wide range of operating and perturbation conditions. In addition, IR thermography quantifies the surface temperature of the pellet. With this large data set, we develop and validate a transient single pellet CFD model coupling the surrounding gas flow with a three-dimensional reaction-diffusion model inside the pellet. Furthermore, the experimental and CFD setup is extended to an array of pellets mimicking a core section of a packed bed. This bridges our single pellet findings with industrially operating methanation fixed-bed reactors. Finally, we apply system identification tools to describe the dynamic pellet response under perturbation.