Mass and heat transfer effects in catalytic monolith reactors

On the Use of Dual Cell Density Monoliths

Monolith-type substrates are extensively used in automotive catalytic converters and have gained popularity in several other industrial processes. Despite their advantages over traditional unstructured catalysts, such as large surface area and low pressure drop, novel monolith configurations have not been investigated in depth. In this paper, we use a detailed computational model at the reactor scale, which considers entrance length, turbulence dissipation and internal diffusion limitations, to investigate the impact of using a dual cell substrate on conversion efficiency, pressure drop, and flow distribution. The substrate is divided into two concentric regions, one at its core and one at its periphery, and a different cell density is given to each part. According to the results, a difference of 40% in apparent permeability is sufficient to lead to a large flow maldistribution, which impacts conversion efficiency and pressure drop. The two mentioned variables show a positive or negative correlation depending on what part of the substrate—core or ring—has the highest permeability. This and other results contribute relevant evidence for further monolith optimization.

A Review of the Critical Aspects in the Multi-Scale Modelling of Structured Catalytic Reactors

Structured catalytic reactors are enjoying an increasingly important role in the reaction engineering world. At the same time, there are large and growing efforts to use advanced computational models to describe such reactors. The structured reactor represents a multi-scale problem that is typically modelled at the largest scale only, with sub-models being used to improve the model granularity. Rather than a literature review, this paper provides an overview of the key factors that must be considered when choosing these sub-models (or scale bridges). The example structured reactor selected for illustration purposes is the washcoated honeycomb monolith design. The sub-models reviewed include those for pressure drop, inter- and intra-phase mass and heat transfer, and effective thermal conductivity.

Spatially-resolved investigation of the water inhibition of methane oxidation over palladium

Pd/Al₂O₃ catalysts are known to be active for low temperature methane oxidation reactions, however it has been shown that gases normally associated with methane gas streams (H₂O, CO₂, H₂S) can have an inhibitory effect on the total oxidation reaction.

Mass and Heat Transfer Coefficients in Automotive Exhaust Catalytic Converter Channels

Mass and heat transfer coefficients (MTC and HTC) in automotive exhaust catalytic monolith channels are estimated and correlated for a wide range of gas velocities and prevailing conditions of small up to real size converters. The coefficient estimation is based on a two dimensional computational fluid dynamic (2-D CFD) model developed in Comsol Multiphysics, taking into account catalytic rates of a real catalytic converter. The effect of channel size and reaction rates on mass and heat transfer coefficients and the applicability of the proposed correlations at different conditions are discussed. The correlations proposed predict very satisfactorily the mass and heat transfer coefficients calculated from the 2-D CFD model along the channel length. The use of a one dimensional (1-D) simplified model that couples a plug flow reactor (PFR) with mass transport and heat transport effects using the mass and heat transfer correlations of this study is proved to be appropriate for the simulation of the monolith channel operation.

3D printing in chemical engineering and catalytic technology: structured catalysts, mixers and reactors

Computer-aided fabrication technologies combined with simulation and data processing approaches are changing our way of manufacturing and designing functional objects. Also in the field of catalytic technology and chemical engineering the impact of additive manufacturing, also referred to as 3D printing, is steadily increasing thanks to a rapidly decreasing equipment threshold. Although still in an early stage, the rapid and seamless transition between digital data and physical objects enabled by these fabrication tools will benefit both research and manufacture of reactors and structured catalysts. Additive manufacturing closes the gap between theory and experiment, by enabling accurate fabrication of geometries optimized through computational fluid dynamics and the experimental evaluation of their properties. This review highlights the research using 3D printing and computational modeling as digital tools for the design and fabrication of reactors and structured catalysts. The goal of this contribution is to stimulate interactions at the crossroads of chemistry and materials science on the one hand and digital fabrication and computational modeling on the other.

Network models of dissolution of porous media

We investigate the chemical dissolution of porous media using a 2D network model in which the system is represented as a series of interconnected pipes with the diameter of each segment increasing in proportion to the local reactant consumption. Moreover, the topology of the network is allowed to change dynamically during the simulation: As the diameters of the eroding pores become comparable with the interpore distances, the pores are joined together, thus changing the interconnections within the network. With this model, we investigate different growth regimes in an evolving porous medium, identifying the mechanisms responsible for the emergence of specific patterns. We consider both the random and regular network and study the effect of the network geometry on the patterns. Finally, we consider practically important problem of finding an optimum flow rate that gives a maximum increase in permeability for a given amount of reactant.