Modelling, optimization and characterization of carbon black derived from waste tyre pyrolysis - Odunayo T. Ore; Festus M. Adebiyi (Discover Materials)
Abstract This study explores how to maximise the yield of carbon black from waste tyre pyrolysis, paying particular attention to important process parameters including feedstock mass, residence time, and temperature. The study employed the use of the central composite design of the response surface methodology to investigate the relationship between the process parameters (feedstock mass, residence time, and temperature) and the carbon black yield. With an R2 and adjusted R2 of 0.99, and a highly significant F-value of 389.62, the model demonstrated excellent accuracy. Analysis of perturbation plots revealed that feedstock mass had the most significant influence on carbon black yield. The interplay of process parameters was illustrated by the 3D surface plots, which showed a positive correlation between the combined effects of feedstock mass and temperature and carbon black yield. The following parameters were found to be optimal for obtaining a maximum carbon black yield: 40 g of feedstock mass, 350 °C temperature, and 60 min of residence time. This produced a carbon black yield of 25.25 wt.%. This was remarkably comparable to the experimental yield of 25 wt.%, confirming the validity of the response surface methodology model. The characterisation of carbon black generated from waste tyre pyrolysis using FT-IR and SEM reveals a compact structure with little porosity and different functional groups. These characteristics increase the material's reliability, thermal stability, and resilience to environmental degradation, making it ideal for long-term applications like rubber reinforcement and composite manufacturing. The findings indicate the optimal production of carbon black at lower temperatures and shorter residence times. The present study establishes the foundation for further investigation into the optimisation of the pyrolysis process, suggesting that different process conditions be explored.