Phosphorus dosing during catalytic n‑butane oxidation in a μ-reactor: a proof of concept

The selective oxidation of n-butane to maleic anhydride over vanadium–phosphorus oxide catalysts is subject to a dynamic change in the catalyst activity. This phenomenon is called phosphorus dynamics and plays a vital role in the prediction of catalytic reaction rates, but to date, no models measured under transport limitation free conditions have been published. This study presents the first investigation of the phosphorus dynamics over extended periods of time (multiple days on stream) under transport limitation free conditions in a μ-fixed-bed reactor. Initially, temperature variation experiments are conducted to investigate whether phosphorus dynamics takes place in a μ-reactor and to determine the onset of phosphorus loss. Then, a setup for dosing of liquid organophosphorous species on the scale of nL min–1 is proposed, and functionality is demonstrated via step test experiments. Results of the temperature variation showed that phosphorus loss occurs in the μ-reactor but starts at temperatures exceeding those of industrial scale reactors by 30–80 K. It was further observed that addition of steam to the feed increases the intensity of the phosphorus dynamics and lowers the onset temperature. Step test results demonstrated the functionality of the dosing setup if a suitable inert material is chosen and the metal surfaces downstream the dosing are treated according to a passivation procedure proposed in this study. The addition of steam appears to be required for appropriate distribution of the dosed organophosphorous species over the catalyst bed

Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

Catalytic fixed‐bed reactors with a low tube‐to‐particle diameter ratio are widely used in industrial applications. The heterogeneous packing morphology in this reactor type causes local flow phenomena that significantly affect the reactor performance. Particle‐resolved computational fluid dynamics has become a predictive numerical method to analyze the flow, temperature, and species field, as well as local reaction rates spatially and may, therefore, be used as a design tool to develop new improved catalyst shapes. Most validation studies which have been presented in the past were limited to simple particle shapes. More complex catalyst shapes are supposed to increase the reactor performance. A workflow for the simulation of fixed‐bed reactors filled with various industrially relevant complex particle shapes is presented and validated against experimental data in terms of bed voidage and pressure drop. Industrially relevant loading strategies are numerically replicated and their impact on particle orientation and bed voidage is investigated.TU Berlin, Open-Access-Mittel – 202

3D-printed micro bubble column reactor with integrated microsensors for biotechnological applications: from design to evaluation

With the technological advances in 3D printing technology, which are associated with ever-increasing printing resolution, additive manufacturing is now increasingly being used for rapid manufacturing of complex devices including microsystems development for laboratory applications. Personalized experimental devices or entire bioreactors of high complexity can be manufactured within few hours from start to finish. This study presents a customized 3D-printed micro bubble column reactor (3D-µBCR), which can be used for the cultivation of microorganisms (e.g., Saccharomyces cerevisiae) and allows online-monitoring of process parameters through integrated microsensor technology. The modular 3D-µBCR achieves rapid homogenization in less than 1 s and high oxygen transfer with kLa values up to 788 h-1 and is able to monitor biomass, pH, and DOT in the fluid phase, as well as CO2 and O2 in the gas phase. By extensive comparison of different reactor designs, the influence of the geometry on the resulting hydrodynamics was investigated. In order to quantify local flow patterns in the fluid, a three-dimensional and transient multiphase Computational Fluid Dynamics model was successfully developed and applied. The presented 3D-µBCR shows enormous potential for experimental parallelization and enables a high level of flexibility in reactor design, which can support versatile process development

3D-printed micro bubble column reactor with integrated microsensors for biotechnological applications: From design to evaluation

With the technological advances in 3D printing technology, which are associated with ever-increasing printing resolution, additive manufacturing is now increasingly being used for rapid manufacturing of complex devices including microsystems development for laboratory applications. Personalized experimental devices or entire bioreactors of high complexity can be manufactured within few hours from start to finish. This study presents a customized 3D-printed micro bubble column reactor (3D-µBCR), which can be used for the cultivation of microorganisms (e.g., Saccharomyces cerevisiae) and allows online-monitoring of process parameters through integrated microsensor technology. The modular 3D-µBCR achieves rapid homogenization in less than 1 s and high oxygen transfer with kLa values up to 788 h−1 and is able to monitor biomass, pH, and DOT in the fluid phase, as well as CO2 and O2 in the gas phase. By extensive comparison of different reactor designs, the influence of the geometry on the resulting hydrodynamics was investigated. In order to quantify local flow patterns in the fluid, a three-dimensional and transient multiphase Computational Fluid Dynamics model was successfully developed and applied. The presented 3D-µBCR shows enormous potential for experimental parallelization and enables a high level of flexibility in reactor design, which can support versatile process development. © 2021, The Author(s)

Non-Idealities in Lab-Scale Kinetic Testing: A Theoretical Study of a Modular Temkin Reactor

The Temkin reactor can be applied for industrial relevant catalyst testing with unmodified catalyst particles. It was assumed in the literature that this reactor behaves as a cascade of continuously stirred tank reactors (CSTR). However, this assumption was based only on outlet gas composition or inert residence time distribution measurements. The present work theoretically investigates the catalytic CO2 methanation as a test case on different catalyst geometries, a sphere, and a ring, inside a single Temkin reaction chamber under isothermal conditions. Axial gas-phase species profiles from detailed computational fluid dynamics (CFD) are compared with a CSTR and 1D plug-flow reactor (PFR) model using a sophisticated microkinetic model. In addition, a 1D chemical reactor network (CRN) model was developed, and model parameters were adjusted based on the CFD simulations. Whereas the ideal reactor models overpredict the axial product concentrations, the CRN model results agree well with the CFD simulations, especially under low to medium flow rates. This study shows that complex flow patterns greatly influence species fields inside the Temkin reactor. Although residence time measurements suggest CSTR-like behavior, the reactive flow cannot be described by either a CSTR or PFR model but with the developed CRN model

Synthetic Packed-Bed Generation for CFD Simulations: Blender vs. STAR-CCM+

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved computational fluid dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete element method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles

Local structure effects on hydrodynamics in slender fixed bed reactors: Spheres and rings

Fixed bed reactors play a crucial role in the chemical industry, and their performance is influenced by the unique structural effects observed in the small tube-to-particle diameter ratio range ($1.5<D/d_\mathrm{p}<9.3$). Experimental void fraction data for beds made of spherical and ring-shaped particles reveal sudden changes, deviating significantly from theoretical calculations. These effects, categorized into four zones for spherical particles, i.e., single particle string, central channel, annular gap, and central channel + annular gaps, exhibit varying impacts on pressure drop. To describe this, the factors of the Ergun equation are modified accordingly. Furthermore, tortuosity is introduced as an additional parameter to describe the structural effects on fixed bed behavior. Classic correlations prove inadequate, leading to the adaptation of the Millington correlation for random beds, as well as those with a central channel and/or annular gaps. With particle-resolved Computational Fluid Dynamics (PRCFD) simulations, the residence time behavior is quantified of differently structured beds of spheres and rings, revealing deviations from plug flow and the presence of stagnation zones in beds containing a central channel. Notably, beds with an annular gap displays residence time behavior akin to plug flow, with lower pressure drop and an ordered, reproducible structure. These results highlight the importance of the $D/d_\mathrm{p}$ ratio as an additional descriptor to characterize transport phenomena in slender fixed-bed reactors

Enhancing the Thermal Performance of Slender Packed Beds through Internal Heat Fins

Slender packed beds are widely used in the chemical and process industry for heterogeneous catalytic reactions in tube-bundle reactors. Under safety and reaction engineering aspects, good radial heat transfer is of outstanding importance. However, because of local wall effects, the radial heat transport in the vicinity of the reactor wall is hindered. Particle-resolved computational fluid dynamics (CFD) is used to investigate the impact of internal heat fins on the near wall radial heat transport in slender packed beds filled with spherical particles. The simulation results are validated against experimental measurements in terms of particle count and pressure drop. The simulation results show that internal heat fins increase the conductive portion of the radial heat transport close to the reactor wall, leading to an overall increased thermal performance of the system. In a wide flow range (100&lt;Rep&lt;1000), an increase of up to 35% in wall heat transfer coefficient and almost 90% in effective radial thermal conductivity is observed, respectively