Multi-Scale Model to Predict the Growth of Carbon Nanotubes (CNT) in Diffusion Flame Conditions

Abstract

Flame synthesis provides a quick and affordable option for the prediction of carbon nanotubes (CNT), however laboratory test is often hampered by the difficulty of predicting the position of CNT growth within a non homogeneous flame environment. The simple chemistry (SC) technique used in the published multi-scale model requires further refinement to accurately predict the physio-chemical properties of the gas phase. Therefore, the primary goal of the current research is to improve upon the multi-scale model that previously combined computational fluid dynamics (CFD) with a growth rate (GR) model through the implementation of detail chemistry (DC). An inverse diffusion flame (IDF) powered by a blend of 30% methane and 5% ethylene is implemented in the present study. Using the flamelet method implemented in the CFD tool OpenFOAM, at horough validation of the CFD flame model of the IDF is performed for a baseline situation with 30% O2. As compared to the prediction made by the prior SC model, the accuracy of the predicted flame temperature and CNT growth region has increased by around 15% and 25%, respectively. A comparison of the DC model and the SC model reveals that, CNT growth and carbon density on catalyst particles are distributed at the fuel side of the flame when the DC model is implemented. This said observation indicates an improvement in the physical modelling of CNT growth since the SC model had previously predicted that CNT growth would occur in the oxidizer region which is not physical. Additionally, using the DC model eliminates the necessity for an artificial threshold for CNT growth truncation as predicted in the SC model, presenting another advancement in the physical modelling of the multi-scale model.