4.7 Article

A multi-scale model for syngas combustion on NiO oxygen carrier for chemical looping combustion: The role of nearest neighbors

期刊

FUEL PROCESSING TECHNOLOGY
卷 229, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.fuproc.2022.107172

关键词

Chemical looping combustion; Nickel oxide; Density functional theory; Kinetic Monte Carlo; Neighboring effects

资金

  1. China Scholarship Council (CSC)

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A multi-scale modelling study was conducted to investigate the neighboring effects on syngas combustion in a NiO oxygen carrier-based CLC process. The study found that CO oxidation was slightly weakened by CO neighbors, while it was enhanced by H-2 neighbors. The neighboring effects were also found to benefit the three-step H-2 oxidation process. Experimental results verified the predictions of a DFT-based kMC multi-scale model, which estimated the neighboring effects under practical operating conditions. Furthermore, a DFT-based MF multi-scale model that considered the neighboring effects was developed to accurately predict the system's behavior at larger time scales.
A multi-scale modelling study was conducted to determine the neighboring effects on syngas combustion on a NiO oxygen carrier-based CLC process. According to the activation energy analysis, CO oxidation was slightly weakened by CO neighbors and enhanced by H-2 neighbors. The three-step H-2 oxidation process generally benefits from the neighboring effects. A combined electronic analysis confirmed these observations. A DFT-based kMC multi-scale model, verified by experimental results, was developed to estimate the neighboring effects under practical operating conditions. The results showed that the system was most significantly affected by the neighboring effects on CO adsorption, whereas the neighboring effects on the CO oxidation led to an almost negligible change. The effects caused by the neighboring effects showed that this phenomenon is critical to capture the system performance. A DFT-based MF multi-scale model that considers neighboring effects was built to quantitatively predict the system's behavior at larger time scales.

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