Scaling Relations for Autothermal Operation of Catalytic Reactors

Optimizing hierarchical membrane/catalyst systems for oxidative coupling of methane using additive manufacturing

The advantage of a membrane/catalyst system in the oxidative coupling of methane compared with conventional reactive systems is that by introducing oxygen into the catalytic sites through a membrane, the parasitic gas-phase reactions of O2(g)-responsible for lowering product selectivity-can be avoided. The design and fabrication of membrane/catalyst systems has, however, been hampered by low volumetric chemical conversion rates, high capital cost and difficulties in co-designing membrane and catalyst properties to optimize the performance. Here we solve these issues by developing a dual-layer additive manufacturing process, based on phase inversion, to design, fabricate and optimize a hollow-fibre membrane/catalyst system for the oxidative coupling of methane. We demonstrate the approach through a case study using BaCe0.8Gd0.2O3-δ as the basis of both catalyst and separation layers. We show that by using the manufacturing approach, we can co-design the membrane thickness and catalyst surface area so that the flux of oxygen transport through the membrane and methane activation rates in the catalyst layer match each other. We demonstrate that this 'rate matching' is critical for maximizing the performance, with the membrane/catalyst system substantially overperforming conventional reactor designs under identical conditions.

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Ignition–extinction analysis of catalytic reactor models

A detailed analysis of the ignition–extinction and hysteresis behavior of the two widely used catalytic reactor models (packed-bed and monolith) for the case of a single exothermic reaction is presented. First, limiting models are used to determine the minimum adiabatic temperature rise and/or catalyst activity needed to observe hysteresis behavior. Next, explicit expressions are provided for estimating the feed temperature or space time at ignition (light-off) and extinction (blow-out) as a function of the adiabatic temperature rise (or inlet concentration of limiting reactant), effective thermal conductivity, time and length scales (reactor, tube/channel diameter, effective diffusion length and pore size), catalyst activity (or dilution) and heat loss. It is shown that various limiting reactor models such as the thin-bed, long-bed, lumped thermal, adiabatic and strongly cooled cases that are defined in terms of various inter- and intraphase heat and mass dispersion time scales can be used to derive scaling relations that are useful in predicting the ignition/extinction loci for both laboratory scale (with heat exchange) and large scale (near adiabatic) reactors.