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In-silico amine screening is a fast, low-cost and promising way of efficiently evaluating new amine molecules which are proposed for carbon-dioxide capture purposes. In order to implement the screening environment, reliable and robust absorber models are required. This contribution presents the modeling and validation results of a CO2 capture pilot absorber operated with monoethanolamine (MEA), as the first step of the in-silico solvent screening framework. The simulation results have shown that the outlet amine loading can be predicted with a 10% deviation from the experimental values for one column, with larger deviations for the second. In addition the model was extended to include the calculation of the overall mass transfer coefficient from laboratory based wetted-wall experiments completed at CSIRO Newcastle, Australia. This further improved the overall model prediction and significantly reduced the amine loading prediction error for the column 1. Note that no parameter fitting was performed on the pilot plant experimental data, other than to include a heat loss to the atmosphere term, and the model relies entirely on engineering and property correlations available in the scientific literature. [ABSTRACT FROM AUTHOR]

Crystallization is one of the most important unit operations used for the separation and purification of crystalline solid products. Appropriate design and control of the crystallization process is paramount to produce crystalline products with tailor-made-properties. This paper provides an overview of selected recent developments in the modelling, monitoring and control of crystallization processes. We consider the topics discussed in this review to be enabling technologies for the development of the next generation of crystallization processes with significantly improved predictability, robustness and controllability. [ABSTRACT FROM AUTHOR]