(299a) Understanding Particle Breakage Using Population Balance Modeling and Grain Texture Analysis | AIChE

(299a) Understanding Particle Breakage Using Population Balance Modeling and Grain Texture Analysis

Today's customized industrial particles are a combination of variously sized primary particles mixed together and put through an agglomeration step to produce a larger size particle with the free flowing behaviors of coarse particles and the chemical functionality of finer particles. Unfortunately, maintaining these fine particle functionalities often requires the production of porous materials which are sensitive to particle breakage effects. To design robust particles, details of particle breakage mechanisms must be understood so as to understand how to change agglomeration processes, thereby facilitating robust particle production. Combining population balance modeling and grain texture analysis provides a detailed description of the cause of agglomerated particles, allowing targeted particle scale modification to optimize degradation resistance. Population balance modeling determines if fine particles are created directly by the breakage of coarse particles. Texture analysis determines the effective characteristic particle size of the agglomerated particle. It is important to note that agglomeration techniques and subsequent post processing can modify grain structure. Also, the primary particle size distribution of the agglomeration feed may not describe the effective grain structure of the final agglomerate. Combining the results of the population balance modeling and the texture analysis allows engineers to change processing and optimize production of key bonds between agglomerated particles. This paper looks at the particle size degradation of agglomerated bran as an example of the usefulness of this method. The population balance modeling indicates the type of breakage bran is subjected to. The texture analysis combined with the population balance model targets bonds between a particular size of particles as the key indicator for making more robust particles.


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