A methodology for
a model-based simultaneous solvent screening
and dimensioning of extraction columns is presented. Therefore, a
rate-based extraction model is combined with a distillation model
for solvent recovery and product purification to consider the whole
extraction process. The optimal operating point and the required column
dimensions are determined for each solvent candidate specifically
to minimize total costs, which are used as a basis for solvent ranking.
The methodology is applied to the extraction of levulinic acid from
an aqueous feed with a special focus on the influence of mutual solubility
between the solvent candidates and water. It is shown that using mixture
properties for both phases in accordance with the mutual solubility
significantly impacts the calculation of fluid dynamics, mass transfer,
and thereby on the required extraction column height. Furthermore,
additional costs due to solvents solubilized in the aqueous raffinate
strongly affect the economic evaluation of the solvents.
In extractive-reaction processes, product formation and separation are integrated to increase the overall process performance. The design of an efficient extractive-reaction process requires optimal solvent selection. However, nowadays the solvent selection is still based on simple performance indicators such as the partition coefficient. Thereby, the influence of fluid dynamics and mass transfer on the overall reaction performance is not considered. To overcome this drawback, we develop a modelbased approach to screen multiple solvents. The developed model requires solely solvent property data, which were generated by COSMO-RS. By minimizing the production costs, optimal operating conditions and process design are determined for each solvent. Thereby, over 100 solvents are screened and evaluated at the example process of the biphasic production of 5-hydroxymethylfurfural. It is shown that there is a unique optimal process for each solvent. Moreover, fluid dynamics and mass transfer influence the optimal extractive-reaction process design and affect the solvent choice.
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