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Here, we seek to develop mechanistic and predictive models of particulate processes such as granulation, mixing, and milling. We are working to develop sub-models (kernels) that describe the dynamics as a function of key material properties and process parameters. The models are validated against experimental data at the lab scale and are tested for their predictive capability. Such validated models are able to reduce the time and cost associated with tedious experimental trials.

Batch Processes

Batch Processes

High Shear Granulation

Schematic showing the formulation of the compartments within the granulator.

Fluid Bed Granulation

Schematic of the algorithm for solving the coupled heat/mass balance and PBM using a mechanistic kernel.

Reactive Granulation

Agglomeration of Sodium carbonate primary particles. As the HLAS droplets come into contact with Sodium carbonate particles, a product (passivation) layer forms around the particle which aids in the agglomeration by forming strong liquid bridges which bind the particles together.


Schematic draft of the modeled well mixed seeded batch cooling crystallization process.

Continuous Processes

Drum Granulation

A comprehensive systems representation of the granulation process


Residence Time Distribution (RTD) versus time for feedrate of 30 kg/h

Twin Screw Granulation

Three regions of the twin-screw granulator based on the experimental setup


Experimental and simulated steady-state mass hold-up values.