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Updated: Oct 10, 2026

Millifluidics for Chemical Synthesis and Time-resolved Mechanistic Studies
Published on: November 27, 2013
Interfacial reaction-network catalysis: steering complex transformations through physical mixing
Guo Tian1,2,3, Zining Wang2, Chenxi Zhang2,3
1School of Chemical Engineering/Key Laboratory of Coal Clean Conversion & Chemical Engineering Process, Xinjiang University, Urumqi 830046, China.
Abstract:
Physical mixing is one of the simplest ways to combine catalytic components, yet it has often been treated as an empirical formulation strategy rather than a rational design principle. This Review states that, when distinct solids are arranged to exchange intermediates, products, inhibitors, heat or local chemical potentials, a physical mixture can function as an interfacial reaction network rather than as a simple sum of independent catalysts. We define this concept as interfacial reaction-network catalysis (IRNC), in which complex transformations are spatially partitioned into coupled functional domains and steered through measurable interdomain exchange. After clarifying the boundaries between physical mixing, conventional bifunctional catalysis and chemically integrated architectures, we introduce three network-control modes: intermediate relay, catalytic shunting and thermodynamic cascading. Intermediate relay connects source and receiving domains through relayed intermediates. Catalytic shunting allocates branch-point flux among desired, side, escape and deactivation pathways. Thermodynamic cascading regulates local activities, residence times and deactivation exposure through enrichment, product removal and inhibitor buffering. We then discuss how these functions operate in oxide-zeolite, Fischer-Tropsch-zeolite and multicomponent systems, and how physical separation and chemical integration provide complementary coupling regimes. Finally, we highlight descriptor quantification, operando characterization, multiscale simulation and catalyst-reactor co-design as key requirements for moving IRNC from empirical combination to predictive network programming. This framework establishes physical mixing as a modular and scalable strategy for steering complex catalytic transformations across molecular, particle and reactor scales.
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