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Updated: Jun 27, 2025

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Optimization of Crystal Growth for Neutron Macromolecular Crystallography
Published on: March 13, 2021
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Single and Multiobjective Shutdown Optimization of a Multistage Continuous Crystallizer
1Chemical Engineering Department, Loughborough University, Epinal Way, Loughborough, Leicestershire LE11 3TU, U.K.
Summary
This study introduces an optimal shutdown method for continuous crystallization, maximizing product yield and minimizing waste. The procedure achieves steady-state productivity and reduces waste by over 80% compared to standard methods.
Area of Science:
- Chemical Engineering
- Process Control
- Crystallization Technology
Background:
- Continuous crystallization processes require efficient shutdown procedures to maintain productivity and minimize waste.
- Existing shutdown methods often lead to significant product loss and waste generation.
Purpose of the Study:
- To develop the first model-based optimal shutdown procedure for multistage continuous crystallization.
- To maximize on-spec production and minimize shutdown time.
- To reduce waste generated during the shutdown phase.
Main Methods:
- Aspirin (acetylsalicylic acid) cooling antisolvent crystallization in a three-stage continuous crystallizer was used as a case study.
- Single optimization scenarios were employed to evaluate degrees of freedom, discretization schemes, and optimization settings.
- Multiobjective optimization and a multiattribute utility theory-based decision-aiding method were used to address conflicting objectives.
Main Results:
- Optimal shutdown procedures can produce significant amounts of on-spec crystals at both fixed and variable shutdown times.
- The shutdown-to-steady-state productivity ratio (STSPR) can reach 100%, matching steady-state productivity.
- Residual waste material was reduced by over 80% compared to standard shutdown procedures.
Conclusions:
- Model-based optimal shutdown procedures offer a significant improvement over standard methods for continuous crystallization.
- The developed method effectively balances on-spec production maximization and shutdown time minimization.
- The approach provides a robust framework for decision-making in optimizing crystallization shutdown operations.
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