Deepak Kumar, Milin Shah, Daniele Marchisio, Vishnu Pareek, J J Eksteen
The world is shifting to green energy to protect the environment. However, there is a need for high-performance and more efficient batteries to store and use that energy. Li-ion batteries(LIBs) are widely used, but to meet the future energy storage demands, the production of battery materials will have to increase tenfold in the next decade and will have to increasingly rely on recycling. To meet these pressing requirements, it is essential to develop a computational modelling tool to design, optimise, and scale-up production processes for battery materials within narrow bounds. In this work, the focus is on the production of a cathode material precursor, based on Nickel (Ni), Manganese (Mn), and Cobalt (Co) mixed hydroxide (NMC), also known as pCAM (precursor cathode material). This research examines the nucleation, growth, and agglomeration mechanisms of NMC particles, described via a population balance model (PBM), as influenced by the chemistry of the reactants and mixing conditions (described via computational fluid dynamics, CFD), which in turn dictate particle morphology and size distribution (PSD). PSD is predicted for different mixing conditions and chemical composition of the reaction environment. Subsequently, model predictions are validated using experimental results. This research observes that the reaction environment is very small compared to the reactor size, and that a small volume is a high supersaturation zone, which results in a very high nucleation rate. Whereas the rest of the reactor volume acts as the growth zone. The predicted PSD is closely related to the measured PSD, implying the accuracy of model predictions.