Development of a numerical model to simulate carbon black synthesis and predict the aggregate structure in flow reactors

Carbon black (CB) has diverse applications which depend on the physical structure of the particle, especially aggregate structure. CB manufacturers can benefit from a predictive tool which estimates the mean properties and the aggregate shape of the final product. The number of CB numerical models that can predict the aggregate structure is limited. However, in the soot research field, these tools have been developed and validated extensively. Therefore, this work seeks the implementation of a recently developed soot model into a plug flow reactor code to simulate the CB synthesis in flow reactors to predict the aggregate structure. The aerosol dynamics model used in this study includes reversible particle inception, reversible surface polycyclic aromatic hydrocarbon (PAH) addition, hydrogen abstraction carbon addition (HACA), oxidation, and particle aggregation. The modeling results are validated with experimental gas-phase species measurements, particle volume fraction (F-V), particle size distribution (PSD), and the aggregate structure. Four gas-phase chemical kinetic mechanisms are compared which all show a reasonably good agreement with the gas-phase species measurements. Two chemical kinetic mechanisms when coupled to the aerosol dynamics model predict F-V and PSD profiles fairly well. The models capability of predicting the number of primary particles per aggregate is promising. The modeling results show that PAH addition is more important than HACA growth, and aggregation significantly reduces the number density of the particles below 10 nm. (C) 2019 The Combustion Institute. Published by Elsevier Inc. All rights reserved.