Dynamic Methanation of CO 2 – Effect of Concentration Forcing

Proposal of an open-source computational toolbox for solving PDEs in the context of chemical reaction engineering using FEniCS and complementary components

In this contribution, an open-source computational toolbox composed of FEniCS and complementary packages is introduced to the chemical and process engineering field by addressing two case studies. First, the oxidation of o-xylene to phthalic anhydride is modelled and used as a FEniCS′ proof-of-concept based on a comparison with the software Aspen Custom Modeler (ACM). The results show a maximum absolute error of 2% and thus a good FEniCS/ACM agreement. Second, synthetic natural gas (SNG) production through CO₂ methanation is covered in further detail. In this instance, a parametric study is performed for a tube bundle fixed-bed reactor employing a two-dimensional and transient pseudo-homogeneous model. An operating window for critical variables is evaluated, discussed, and successfully contrasted with the literature. Therefore, the computational toolbox methodology and the consistency of the results are validated, strengthening FEniCS and complements as an interesting alternative to solve mathematical models concerning chemical reaction engineering.

Spray-Dried Ni Catalysts with Tailored Properties for CO2 Methanation

A catalyst production method that enables the independent tailoring of the structural properties of the catalyst, such as pore size, metal particle size, metal loading or surface area, allows to increase the efficiency of a catalytic process. Such tailoring can help to make the valorization of CO2 into synthetic fuels on Ni catalysts competitive to conventional fossil fuel production. In this work, a new spray-drying method was used to produce Ni catalysts supported on SiO2 and Al2O3 nanoparticles with tunable properties. The influence of the primary particle size of the support, different metal loadings, and heat treatments were applied to investigate the potential to tailor the properties of catalysts. The catalysts were examined with physical and chemical characterization methods, including X-ray diffraction, temperature-programmed reduction, and chemisorption. A temperature-scanning technique was applied to screen the catalysts for CO2 methanation. With the spray-drying method presented here, well-organized porous spherical nanoparticles of highly dispersed NiO nanoparticles supported on silica with tunable properties were produced and characterized. Moreover, the pore size, metal particle size, and metal loading can be controlled independently, which allows to produce catalyst particles with the desired properties. Ni/SiO2 catalysts with surface areas of up to 40 m2 g−1 with Ni crystals in the range of 4 nm were produced, which exhibited a high activity for the CO2 methanation.

Dynamically Operated Fischer–Tropsch Synthesis in PtL—Part 2: Coping with Real PV Profiles

Climate change calls for a paradigm shift in the primary energy generation that comes with new challenges to store and transport energy. A decentralization of energy conversion can only be implemented with novel methods in process engineering. In the second part of our work, we took a deeper look into the load flexibility of microstructured Fischer–Tropsch synthesis reactors to elucidate possible limits of dynamic operation. Real data from a 10 kW photovoltaic system is used to calculate a dynamic H2 feed flow, assuming that electrolysis is capable to react on power changes accordingly. The required CO flow for synthesis could either originate from a constantly operated biomass gasification or from a direct air capture that produces CO2; the latter is assumed to be dynamically converted into synthesis gas with additional hydrogen. Thus two cases exist, the input is constantly changing in syngas ratio or flow rate. These input data were used to perform challenging experiments with the pilot scale setup. Both cases were compared. While it appeared that a fluctuating flow rate is tolerable for constant product composition, a coupled temperature-conversion relationship model was developed. It allows keeping the conversion and product distribution constant despite highly dynamic feed flow conditions.