The mathematical catalyst deactivation models: a mini review

Area of Science:

• Chemical Engineering
• Catalysis Science
• Reaction Engineering

Background:

• Catalyst deactivation is a significant challenge in the chemical industry, impacting process efficiency and catalyst design.
• Understanding deactivation mechanisms, such as coke and metal deposition, is vital for developing accurate predictive models.
• Existing models often require refinement to precisely represent catalyst activity decay over time.

Purpose of the Study:

• To review and discuss various catalyst deactivation models relevant to key industrial processes.
• To highlight the importance of accurate deactivation modeling for optimizing catalytic reactors and processes.
• To provide a framework for selecting appropriate models for diverse catalytic systems.

Main Methods:

• Discussion of different deactivation mechanisms (coke, metal deposition) and their impact on kinetic models.
• Integration of reaction kinetics with deactivation kinetic equations in mathematical reactor models.
• Design and application of selective and nonselective deactivation kinetic models for heterogeneous reactions.

Main Results:

• Different deactivation mechanisms result in distinct catalyst activity decay patterns.
• Coupling reaction and deactivation kinetics allows for accurate prediction of product distribution over conversion time.
• Developed models can identify catalyst deactivation through the propagation of heterogeneous chemical reactions.

Conclusions:

• Accurate catalyst deactivation models are essential for optimizing catalytic processes and catalyst design.
• The reviewed models offer a pathway to better represent catalyst activities in CO2 hydrogenation, Fischer-Tropsch synthesis, and biofuel/fossil fuel conversion.
• This work facilitates improved catalyst performance evaluation and process optimization in various catalytic applications.