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堆相比，催化反应器将更多地受到动态边界条件的影响，如启动、关闭或负荷变化。二氧化碳的动态加氢为甲烷(甲烷化)就是这样一个例子，催化反应器必须动态运行。为了恰当地设计这一动态过程，需要在所有相关的长度和时间尺度上对物理和化学过程有深刻的理解。虽然过去有大量的理论和实验工作致力于纳米尺度(催化剂和活性中心动力学)和宏观尺度(瞬变条件下的反应动力学)的催化过程，但相对较少的研究集中在介观尺度(颗粒间和颗粒内动力学)的动态效应。特别是，在强制瞬变操作下，单个催化颗粒内的扩散和反应与周围流场之间的相互作用还知之甚少。因此，我们假设，只有通过详细的操作实验和详细的CFD模拟相结合的方法，我们才能在颗粒水平上了解动态甲烷化过程。基于这些详细的单粒子洞察，我们可以得出在填充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的单个颗粒。利用毛细管采样技术，我们量化了在各种操作和扰动条件下球团内部和边界气体层内的动态局部温度和浓度分布。此外，红外热像仪还可以量化球团的表面温度。利用这个庞大的数据集，我们建立并验证了一个耦合周围气体流动和球团内部三维反应扩散模型的瞬变单球CFD模型。此外，实验和CFD装置被扩展到模拟填充床的核心部分的颗粒阵列。这将我们的单一颗粒发现与工业化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微扰下的弹丸动态响应。

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.