Simplified Computational Model for Evolution of Particle Morphology during Coprecipitation

For enhanced energy and power density, most of the commercially available lithium ion batteries use LiNi x Mn y Co (1-x-y) O 2 (where, x and y are some fraction between 0.0 and 1.0) based active materials in the cathode side[1]. Synthesis of these cathode active materials are conducted through the calcination of transition metal hydroxide (Ni x Mn y Co (1-x-y) (OH) 2 ) precursors with lithium hydroxides or carbonates[2]. Size, shape and internal porosity of the cathode active particles significantly impact the overall performance and cycle life experienced by the lithium ion cell[3]. Morphology of the cathode active particle is usually determined by the size and shape of the transition metal hydroxide precursors[4]. Hence, appropriate understanding of the synthesis mechanism of the hydroxide precursors (Ni x Mn y Co (1-x-y) (OH) 2 ) is necessary for developing better quality cathode active particles for usage in the next generation lithium ion batteries. Coprecipitation reaction at constant pH in continuous stirred tank reactors (CSTR) is the most commonly used technique for developing battery grade transition metal hydroxide precursors in a large scale[2, 4-6]. Focused ion beam scanning electron microscopy (FIB-SEM) images of the cathode active materials clearly reveals the presence of sub-micron sized primary crystalline particles, which aggregates to form micron sized secondary particles[3]. Morphology of these primary and secondary particles are determined during the coprecipitation process, which depends on the solution pH, ammonia content and stirring speed maintained within the reactor[4, 5]. A computational methodology has been developed as part of the present research effort, which successfully captures the nucleation, growth and aggregation of the crystalline primary particles observed during the coprecipitation process within the chemical reactor. Evolution of the primary particle nucleus density occurs according to the magnitude of super-saturation ratio[7]. Growth of the crystalline primary particles happen in a rate limited fashion, which leads to a linear increase in the primary particle diameter with time. Agglomeration of these primary particles lead to the formation of secondary particles[4, 5], which has been simulated using an energy minimization technique. Presence of ammonia within the reactor increases the solubility of the transition metal hydroxides through the formation of metal ammonia complexes[5]. As described by van Bommel and Dahn[5], primary particle growth and aggregation happens through a dissolution-recrystallization mechanism via formation of this metal-ammonia complex. Concentration of this complex depends on the pH and ammonia content of the solution, which has been determined by solving appropriate mass balance equations and equilibrium relations for transition metal ions and ammonia, maintained under constant pH conditions[5, 6]. Figure 1 (black solid line) demonstrates the computationally predicted secondary particle size with respect to the magnitude of solution pH. The particle size distribution is shown by the error-bars, which indicates the first standard deviation. Ammonia content have been kept constant at 1.6M for this particular simulation. Good correlation between the experimentally obtained secondary particle sizes (denoted by red squares in Figure 1)[4] and that predicted by the computational results clearly demonstrates the capability of the developed methodology to capture the real physical phenomena with reasonable accuracy. All the particle sizes and size-distributions reported here have been obtained at the end of the coprecipitation process. Dependence of the particle morphology (such as, size and shape) on the reaction parameters (such as, solution pH, ammonia content) will be elucidated in this study. References Thackeray, M.M., et al., Advances in manganese-oxide 'composite' electrodes for lithium-ion batteries. Journal of Materials Chemistry, 2005. 15 (23): p. 2257-2267. Lee, M.H., et al., Synthetic optimization of Li[Ni1/3Co1/3Mn1/3]O-2 via co-precipitation. Electrochimica Acta, 2004. 50 (4): p. 939-948. Gilbert, J.A., I.A. Shkrob, and D.P. Abraham, Transition Metal Dissolution, Ion Migration, Electrocatalytic Reduction and Capacity Loss in Lithium-Ion Full Cells. Journal of the Electrochemical Society, 2017. 164 (2): p. A389-A399. Noh, M. and J. Cho, Optimized Synthetic Conditions of LiNi0.5Co0.2Mn0.3O2 Cathode Materials for High Rate Lithium Batteries via Co-Precipitation Method. Journal of the Electrochemical Society, 2013. 160 (1): p. A105-A111. van Bommel, A. and J.R. Dahn, Analysis of the Growth Mechanism of Coprecipitated Spherical and Dense Nickel, Manganese, and Cobalt-Containing Hydroxides in the Presence of Aqueous Ammonia. Chemistry of Materials, 2009. 21 (8): p. 1500-1503. Wang, D.P., et al., Growth mechanism of Ni0.3Mn0.7CO3 precursor for high capacity Li-ion battery cathodes. Journal of Materials Chemistry, 2011. 21 (25): p. 9290-9295. Karthika, S., T.K. Radhakrishnan, and P. Kalaichelvi, A Review of Classical and Nonclassical Nucleation Theories. Crystal Growth & Design, 2016. 16 (11): p. 6663-6681. Figure 1