Hybrid genetic algorithm and model-free coupled direct search methods for kinetics of nanocrystalline ZSM-5-catalyzed decomposition of PP

Catalytic decomposition of polypropylene over nanocrystalline HZSM-5 was investigated. The optimum catalyst composition was found to be 50 wt.%, where the reduction in maximum decomposition temperature is around 161 °C. Kinetics parameters were estimated based on different decomposition models and multi-heating rate experimental data. We employed the hybrid genetic algorithm (HGA) and the model-free coupled direct search (MFCDS) methods to obtain the optimized kinetics triplet values. Both the methods employed in the present study gave almost the same optimized kinetics triplet values. According to Akaike’s Information Criteria, the nucleation and growth model with reaction order n = 2/3 and the first-order chemical reaction model were found to be the most suited models. The nucleation and growth model with reaction order n = 2/3 very well predicted the experimental TGA data. The catalyst was fairly active even after its use for the 20th cycle without regeneration. Catalytic decomposition produced more lighter hydrocarbons compared to noncatalytic decomposition.

Kinetics analysis of catalytic decomposition of polypropylene over nanocrystalline HZSM-5 at its optimum composition, 50 wt.%, revealed that a nucleation and growth model with reaction order n = 2/3 and a first-order chemical reaction model were the most suited models. The catalyst was fairly active even after its use for the 20th cycle. Catalytic decomposition produces lighter hydrocarbons than noncatalytic decomposition.Figure optionsDownload as PowerPoint slide