Particle Production and Characterization

Session 358 - Population Balance Modeling for Particle Formation Processes I: Nucleation, Aggregation and Breakage Kernels
Contributions are sought in the general area of population balance modeling and control of particle formation processes. Topics of interest include, but are not limited to: (1) the identification of nucleation kinetics and kernels for coalescence, aggregration, agglomeration, and breakage; (2) numerical algorithms for efficiently solving the associated population balance equations with complex particle dynamics; (3) model reduction methods and their application to optimization and feedback control; (4) experimental design methods, to focus experimental efforts on identifying kernels and nucleation kinetics; (5) nonlinear control methods designed to optimize distributions; and (6) mathematical methods for analyzing the sensitivities of the distributions to model uncertainties and disturbances. All application areas involving population balance modeling are of interest including nanoparticle formation, solids flows, granulation processes, solution crystallization, spray drying, precipitation, and emulsion and suspension polymerization.
Chair:Roger Place
CoChair:Edward P. Gatzke
 A Mechanistic Kernel for the Aggregation Phenomenon in Population Balance Models of Granulation Processes
Rohit Ramachandran, Francis J. Doyle III, Frantisek Stepanek, Charles D. Immanuel
 Evolution of Particle Size Distribution for Yeast Flocculation by Polymer Bridging: Experiment and Modeling
Zhen Chen, Ranil Wickramasinghe, Y. K. Leong, Jong Leng Liow
 Non-Quasi-Steady Single Particle Rate Laws (Evaporation or Growth) and Population Balance Simulation Methods
Daniel E. Rosner, Manuel Arias-Zugasti
 Fluctuations in Solutions to the Fragmentation Equation
Robert M. Ziff
 Dynamic Evolution of Multi-Variate Particle Size Distributions in Particulate Processes: a Population Balance Perspective
Aleck Alexopoulos, Costas Kiparissides
 Fcmom: Moments and Moving Boundaries for an Accurate and Convergent Psd Reconstruction
Matteo Strumendo, Hamid Arastoopour

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