6. Conclusions

The different theoretical and practical settings related to azeotropy within the context of chemical engineering, have been described taking into account the experience of our research group in this area. The relationship between the presence of azeotropes, the non-ideality of the solution and the difference in vapor pressures of the pure compounds has been exposed. This information, together with some additional knowledge about the compounds involved in a solution, can be used to estimate the appearance of the azeotrope.

<sup>h</sup>E, Jmol<sup>1</sup> excess enthalpy

T, K system temperature

, m<sup>3</sup> mol<sup>1</sup> molar excess volume

zi active fraction of i-th component

aze relative to azeotropic conditions

V vapor phase

Sub/Supercripts

Greek letters

NS number of stages in distillation column

pi, kPa partial pressure of i-th component

, kPa vapor pressure of pure component i

PN / P<sup>j</sup> polynomial of order N / Coefficient of polynomial PN

SS solvent feed stage in extractive distillation column

u number of carbons in alkyl substituent of esters

x<sup>i</sup> molar fraction of i-th component in the solution

Z<sup>n</sup> product of active fractions up to nth-component

exp denotes an experimentally determined property

αij non-randomness parameter of NRTL model

γ<sup>i</sup> activity coefficient of i-th component

rated vapor

v number of carbons in alkanols

τij τ-function of NRTL model

est denotes a property estimated by a model

S/F solvent-To-Feed ratio in extractive distillation column

<sup>R</sup> or R gas constant Pam3 mol<sup>1</sup> / Reflux ratio in distillation column

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y<sup>i</sup> generic thermodynamic quantity/vapor composition of i-th component

δij function of second Virial coefficients in the mixture ( 2Bij Bii Bjj)

Φ<sup>i</sup> ratio between fugacity coefficient of component "i" in solution and as satu-

L liquid phase

p, kPa pressure

pi o

vE

The combination of direct and indirect measuring techniques, together with suitable treatment of the results, is an excellent way to generate experimental data on which to base the studies. On the other hand, the polynomial equation proposed and used here would seem to be the best option to model the systems, provided that the parameters are optimized using all the experimental data available by means of a combined correlation procedure.

For the prediction of azeotropes, COSMO-RS method produces the best results, although in some cases the quantitative values produced by UNIFAC-DM approximate real values. Simulation of a process by pressure-swing-distillation and another by extractive-distillation allow verify the impact of the modeling and selection of the design parameters on the results of the separation operation.
