Computational screening of heterogeneous catalysts for energy-efficient production of olefins and CO2 reduction

Research question

The project aims to use large-scale computational modeling to identify two-dimensional transition metal carbides, nitrides, and borides as catalysts for transforming alkanes into olefins using CO₂ as a light oxidant. The primary questions to be addressed include understanding how the combination of various transition metals with carbon, nitrogen, and/or boron influences catalytic activity, how catalyst states can be controlled, and how the chemical environment affects reaction kinetics. The goal is to predict materials with optimal performance for dehydrogenation and CO₂ reduction.

Sustainability aspects

The project strongly aligns with UN Sustainable Development Goals 12, focusing on responsible consumption and production by enhancing the energy efficiency of shale gas olefin production. In addition, utilizing CO₂ as an oxidant introduces a circular aspect, potentially reducing around 15 % of the total chemical industry CO₂ emissions per year. This reduction is achievable if the global demand for ethylene, propylene, and butylene is met through CO₂-oxidized dehydrogenation.  Overall, the project contributes to more efficient, circular, and environmentally conscious olefin production from shale gas while simultaneously decreasing CO2 emissions in the chemical industry.