Quality Assessment Algorithm for Vapor−Liquid Equilibrium Data

Abstract

A quality assessment algorithm for vapor−liquid equilibrium (VLE) data has been developed. The proposed algorithm combines four widely used tests of VLE consistency based on the requirements of the Gibbs−Duhem equation, with a check of consistency between the VLE binary data and the pure compound vapor pressures. A VLE data-quality criterion is proposed based on the developed algorithm, and it has been implemented in a software application in support of dynamic data evaluation. VLE predictions (NRTL and UNIFAC) were deployed to detect possible anomalies in the data sets. The proposed algorithm can be applied to VLE data sets with at least three state variables reported (pressure, temperature, plus liquid and/or vapor composition) and is applicable to all nonreacting chemical systems at subcritical conditions. Application of the developed algorithms to identification of erroneous published VLE data sets is demonstrated.