on‐line optimization of integrated carbon capture and conversion process via the Ratings concept: A combined DFT and microkinetic modeling approach

The integrated carbon capture and conversion (ICCC) is a promising catalytic process to produce syngas from CO2 and CH4 via a combined separation and reactor unit. Besides, its performance can fluctuate from the inconsistent feed ratio resulting from the flue gas unit. Herein, the ratings concept based on density functional theory (DFT) is applied to overcome these problems in a two-step protocol: (i) catalyst identification, which designates the catalyst characteristics and predicts performance based on reactivity (RT-R) and stability (RT-S) ratings calculated based on activation energies obtained either from experiments or DFT, and (ii) catalyst optimization that optimized a catalyst’s performance via the determination of new operating condition accounted for its deactivation over time. Moreover, temperature and feed ratio sensitivity were investigated, revealing that most catalysts are more sensitive to temperature change than the feed ratio.