A macroscopic agglomeration kernel model for gibbsite precipitation in turbulent and laminar flows

A macroscopic agglomeration kernel model has been developed that is capable of describing gibbsite agglomeration over a broad range of process conditions, including both the laminar and turbulent flow regimes. The agglomeration kernel model was derived using chemical reaction engineering principles and data from an extensive experimental program covering a wide range of temperatures, supersaturations, seed sizes, shear rates and mixing regimes. The experimental precipitation data in the laminar flow regime were generated using a novel Taylor–Couette precipitator. Data in the turbulent regime were generated in a stirred reactor. The developed agglomeration kernel model incorporates terms for the collision, capture, rupture and cementation rates affecting the formation of agglomerates. The model is shown to be able to predict the data from independent experiments. The proposed model also captures the complex non-linear shear rate and size-dependency observed experimentally, e.g. (1) for small particles the agglomeration kernel exhibits a maximum with respect to the shear rate, increasing at low shear rates in the laminar flow, but decreasing in the unstable Taylor–Couette flows and turbulent regimes; (2) for large particles the agglomeration kernel decreases monotonically with increasing shear.