Scale-up Approach with Dimensional Numbers • The effect of process parameter (i.e., impeller speed, liquid addition rate) on the process and thus on granule characteristics are evaluated based on mechanistic understanding. • Use dimensional numbers as variables rather than individual process parameters. This will decrease the number of variables need to be varied, thus the number of experiments ( includes explicitly includes liquid addition rate, implicitly includes impeller speed and liquid addition mode). • Determine the design space at the smallest scale for the given formulation based on dimensional numbers and validate the design space for larger scales with ...
Materials design and optimization A major goal of the Materials Genome Initiative and “Materials-by- Design” is the acceleration of materials property optimization. 2 Learning properties of a material Another important problem is to learn the underlying Kinetic pathways of controlled release physics of a new material or system Materials specific physical parameters Dominant processes during fabrication or reactions to Compositional Ripening external stimuli. Optimization and learning Coalescence with external phase are two sides to the same Adsorption coin. In order to do either, we need to perform experiments to obtain Flocculation Coalescence Droplet-droplet coalescence measurements that tell us information ...
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