Population Balance Modeling and Optimization of an Integrated Batch Crystallizer–Wet Mill System for Crystal Size Distribution Control
Author:
Affiliation:
1. Department of Chemical Engineering, Loughborough University, Leichestershire, Loughborough Le11 3TU, United Kingdom
2. School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907-2100, United States
Funder
FP7 Ideas: European Research Council
International Fine Particle Research Institution
Publisher
American Chemical Society (ACS)
Subject
Condensed Matter Physics,General Materials Science,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.cgd.7b01331
Reference49 articles.
1. Crystallization Technology Handbook
2. Advances and New Directions in Crystallization Control
3. Real-time feasible multi-objective optimization based nonlinear model predictive control of particle size and shape in a batch crystallization process
4. Robust nonlinear model predictive control of batch processes
5. Nonlinear Model-Based Control of a Semi-Industrial Batch Crystallizer Using a Population Balance Modeling Framework
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