Estimation of (vapour + liquid) equilibrium of binary systems (tert-butanol + 2-ethyl-1-hexanol) and (n-butanol + 2-ethyl-1-hexanol) using an artificial neural network

(Vapour + liquid) equilibrium (VLE) data are important for designing and modelling of process equipment. Since it is not always possible to carry out experiments at all possible temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of VLE. In this paper, an alternate tool, i.e. the artificial neural network technique has been applied for estimation of VLE for the binary systems viz. (tert-butanol + 2-ethyl-1-hexanol) and (n-butanol + 2-ethyl-1-hexanol). The temperature range over which these models are valid is (353.2 to 458.2) K at atmospheric pressure. The average absolute deviation for the temperature output was in range 2% to 3.3%. The results were then compared with experimental data.