Modeling the Drying Process of Porous Catalysts: Impact of the Pore Size Distribution.

The distribution of catalytically active species in heterogeneous porous catalysts strongly influences their performance and durability in industrial reactors. A drying model for investigating this redistribution was developed and implemented using the finite volume method. This model embeds an analytical approach regarding the permeability and capillary pressure from arbitrary pore size distributions. Subsequently, a set of varying pore size distributions are investigated, and their impact on the species redistribution during drying is quantified. It was found that small amounts of large pores speed up the drying process and reduce internal pressure build up significantly while having a negligible impact on the final distribution of the catalytically active species. By further increasing the amount of large pores, the accumulation of species at the drying surface is facilitated.

Direct Numerical Simulation of Reactive Fluid-Particle Systems Using an Immersed Boundary Method.

In this paper, direct numerical simulation (DNS) is performed to study coupled heat and mass-transfer problems in fluid-particle systems. On the particles, an exothermic surface reaction takes place. The heat and mass transport is coupled through the particle temperature, which offers a dynamic boundary condition for the thermal energy equation of the fluid phase. Following the case of the unsteady mass and heat diffusion in a large pool of static fluid, we consider a stationary spherical particle under forced convection. In both cases, the particle temperatures obtained from DNS show excellent agreement with established solutions. After that, we investigate the three-bead reactor, and finally a dense particle array composed of hundreds of particles distributed in a random fashion is studied. The concentration and temperature profiles are compared with a one-dimensional heterogeneous reactor model, and the heterogeneity inside the array is discussed.

Direct Numerical Simulation of Fluid Flow and Mass Transfer in Particle Clusters.

In this paper, an efficient ghost-cell based immersed boundary method is applied to perform direct numerical simulation (DNS) of mass transfer problems in particle clusters. To be specific, a nine-sphere cuboid cluster and a random-generated spherical cluster consisting of 100 spheres are studied. In both cases, the cluster is composed of active catalysts and inert particles, and the mutual influence of particles on their mass transfer performance is studied. To simulate active catalysts the Dirichlet boundary condition is imposed at the external surface of spheres, while the zero-flux Neumann boundary condition is applied for inert particles. Through our studies, clustering is found to have negative influence on the mass transfer performance, which can be then improved by dilution with inert particles and higher Reynolds numbers. The distribution of active/inert particles may lead to large variations of the cluster mass transfer performance, and individual particle deep inside the cluster may possess a high Sherwood number.

Kinetic Monte Carlo simulation of the photodegradation process of polyester-urethane coatings.

A numerical method to simulate reactions in a cross-linked polymer is developed and applied to the photodegradation process of polyester-urethane clearcoats during artificial exposure in a Weather-Ometer. This coarse-grained simulation method, which is based on a kinetic Monte Carlo scheme, is verified with experimental data on the depth-resolved changes in optical properties and chemical composition that have been previously determined. By modelling the depth-dependency of physical processes that occur in the coating, such as the absorption of photons and the diffusion of oxygen, the experimentally observed evolution of depth gradients in chemical composition can be well described by the simulation. A sensitivity analysis of individual simulation input parameters with respect to a set of resulting observables is performed and the results provide insight into the influence of specific reaction mechanisms on the overall degradation process and help to distinguish essential from less important processes. The values of input parameters that result in the most accurate simulation of the experimental data are determined with an optimisation procedure. In this way, the numerical values of several kinetic and physical parameters that are difficult to determine directly in an experimental way, such as various reaction rate constants, can be obtained from the simulations.

Hierarchical multi-scale simulations of adhesion at polymer-metal interfaces: dry and wet conditions.

We performed hierarchical multi-scale simulations to study the adhesion properties of various epoxy-aluminium interfaces in the absence and presence of water. The epoxies studied differ from each other in their hexagonal ring structures where one contains aromatic and the other aliphatic rings. As aluminium is unavoidably covered with alumina, a cross-linked epoxy structure near an alumina substrate is created and relaxed by performing coarse-grained simulations. To that purpose, we employ a recently developed parameterization method for variable bead sizes. For polymer-metal interactions, a multi-scale parameterization scheme is applied where the relative adsorption of each bead type is quantified. At the mesoscopic scale, the adhesion properties of different epoxy systems are discussed in terms of their interfacial structure and adsorption behavior. To further perform all-atom simulations, the mesoscopic structures are transformed into atomistic coordinates by applying a reverse-mapping procedure. Interface internal energies are quantified and the simulation results observed at different scales are compared with each other as well as with the available experimental data. The good agreement between observations from simulations and experiments shows the usefulness of such an approach to better understand polymer-metal oxide adhesion.