Project Description

This Ph.D. project focuses on the integrated carbon capture and utilization (CCU) of CO₂ for the sustainable production of value-added C1 and C2+ chemicals and fuels. The research will employ high-throughput molecular simulations, density functional theory (DFT), molecular dynamics (MD), and machine learning techniques to accelerate the discovery and optimization of advanced carbon capture materials such as zeolites, metal-organic frameworks (MOFs) and transition metal catalysts. The project aims to identify materials with high CO₂ adsorption capacity, selectivity, and catalytic efficiency for integrated capture and conversion processes.

The study will investigate thermocatalytic and/or electrocatalytic pathways for converting captured CO₂ into products such as methanol, methane, ethanol, propanol, olefins, and higher hydrocarbons. Particular emphasis will be placed on transition metal and bimetallic catalysts capable of promoting selective CO₂ reduction and carbon-carbon coupling reactions. By integrating computational screening, catalytic design, and AI-driven materials discovery, the project seeks to develop scalable and energy-efficient CCU technologies with strong potential for industrial deployment and sustainable chemical manufacturing.