Predicting Product Distribution of Propene Dimerization in Nanoporous Materials

Area of Science:

• Catalysis
• Materials Science
• Chemical Engineering

Background:

• Propene dimerization produces C6 olefin isomers, with linear olefins being valuable industrial feedstocks.
• Metal-Organic Frameworks (MOFs), particularly MOF-74, show potential for catalyzing propene dimerization with high selectivity.
• Understanding how catalyst structure affects product distribution is crucial for optimizing olefin production.

Purpose of the Study:

• To develop a theoretical framework for predicting product distribution in propene dimerization using porous catalysts.
• To identify key structural features of porous materials that enhance selectivity for linear olefin isomers.
• To screen a wide range of MOF and zeolite structures for optimal catalytic performance.

Main Methods:

• Development of a theoretical model based on the contribution of pores to the free energy of formation.
• Utilizing molecular simulation to compute pore contributions and predict product distribution.
• Screening a library of 118 existing and hypothetical MOF and zeolite structures.

Main Results:

• Experimentally observed product distributions are explained by the computed free energy contributions of pores.
• Pore size, shape, and composition significantly influence the selectivity of propene dimerization.
• Optimal catalyst designs feature pore sizes matching linear products and open metal sites for favorable binding.

Conclusions:

• The developed theoretical framework accurately predicts product distribution in propene dimerization.
• Catalyst design, specifically pore dimensions and open metal sites, can be tuned to maximize linear olefin selectivity.
• This work provides molecular descriptors for designing efficient catalysts for valuable industrial feedstocks.