CFD-PBE modelling of continuous Ni-Mn-Co hydroxide co-precipitation for Li-ion batteries

[Display omitted] •Population balance equation is coupled with CFD to simulate continuous precipitation.•Multi-inlet vortex mixer is suitable to study co-precipitation of Ni-Mn-Co hydroxide.•Measurements can be leveraged to develop kinetic models for particle precipitation. A modelling framework is...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Chemical engineering research & design 2022-01, Vol.177, p.461-472
Hauptverfasser: Shiea, Mohsen, Querio, Andrea, Buffo, Antonio, Boccardo, Gianluca, Marchisio, Daniele
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:[Display omitted] •Population balance equation is coupled with CFD to simulate continuous precipitation.•Multi-inlet vortex mixer is suitable to study co-precipitation of Ni-Mn-Co hydroxide.•Measurements can be leveraged to develop kinetic models for particle precipitation. A modelling framework is proposed to simulate the co-precipitation of Ni-Mn-Co hydroxide as precursor of cathode material for lithium-ion batteries. It integrates a population balance equation with computational fluid dynamics to describe the evolution of the particle size in (particularly continuous) co-precipitation processes. The population balance equation is solved by employing the quadrature method of moments. In addition, a multi-environment micromixing model is employed to consider the potential effect of molecular mixing on the fast co-precipitation reaction. The modelling framework is used to investigate the co-precipitation of Ni0.8Mn0.1Co0.1(OH)2 in a multi-inlet vortex micromixer, as a suitable candidate for the study of fast co-precipitation processes in continuous mode. Finally, the simulation results are discussed, and the role of the different phenomena involved in the formation and evolution of particles is identified by inspecting the predicted trends.
ISSN:0263-8762
1744-3563
DOI:10.1016/j.cherd.2021.11.008