Distillation in special chemistry

•Special challenges are high purity and recovery in non-ideal reactive systems.•Many distillation designs are outside of the limits of existing correlations.•Thermally sensitive components are distilled at deep vacuum and very low liquid load.•Parameter uncertainties in reactive distillation need to...

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Bibliographic Details
Published inChemical engineering research & design Vol. 99; pp. 220 - 227
Main Authors Hiller, C., Meier, R., Niggemann, G., Rix, A.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.07.2015
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Summary:•Special challenges are high purity and recovery in non-ideal reactive systems.•Many distillation designs are outside of the limits of existing correlations.•Thermally sensitive components are distilled at deep vacuum and very low liquid load.•Parameter uncertainties in reactive distillation need to be considered in design.•Laboratory or plant data in similar service is invaluable to reduce process risk. In the final product, special chemicals are minor ingredients by volume, but essential for performance and function. Distillation is the separations workhorse. Specific challenges arise from the nature of special chemicals. High product purity or tight control of trace impurities have to be achieved in non-ideal, often aqueous systems. Foaming, fouling and three-phase systems are often encountered. This paper addresses two typical challenges in special chemicals distillation and practical solution methods. One example is distillation in deep vacuum in order to minimize thermal degradation of temperature-sensitive components. Enlarging column diameter to meet a maximum allowable pressure drop specification instead of a certain flooding factor entails designs with low liquid loads well below the limits given in literature. Special care should be given to distributor design to ensure acceptable efficiency. In multi-step special chemicals synthesis, reactive distillation is an elegant operation to increase conversion and selectivity or to reduce recycle rate. However, additional design interactions arise, which increase the sensitivity to parameter uncertainty. Sensitivity analysis is a powerful tool to assess the process risk arising from incomplete design information and to devise fallback options. In both examples, plant data from similar processes is invaluable to validate designs.
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ISSN:0263-8762
1744-3563
DOI:10.1016/j.cherd.2015.04.010