Vapor-liquid equilibrium correlations for systems containing amines using a lattice fluid equation of state with hydrogen bonding

Abstract

The nonrandom lattice equation of state with hydrogen bonding (NLF-HB EOS) was examined for the correlation of vapor-liquid equilibria (VLE) for binary amine and hydrocarbon mixture at various temperatures. For these mixtures, the consideration of hydrogen bondings in the lattice equation of state clearly improves the prediction for VLE. The amines were divided into four groups due to the different strength of the hydrogen bonding. For all groups, different hydrogen bonding parameters were obtained and evaluated. The effects of varying hydrogen bonding energies for NLF-HB EOS are discussed. For systems containing lower amines, the NLF-HB EOS showed excellent agreement with the experimental data. For the correlation of systems containing tertiary amine molecules, binary interaction parameter had to be involved instead of hydrogen bonding parameters.

Nonrandom lattice fluid group contribution parameter for vapor-liquid equilibrium of esters and their mixtures

“…Mixtures can be described as follows: (9) where, x i stand for the mole fraction of the component i. The chemical potential has been derived by Klamt [21] through the summation of N different ensembles of charged surface segments: (10) The expression µ(σ) appears on both sides of the equation so that it has to be solved iteratively. Thus, with the implementation of COSMO-RS, it is possible to calculate a mixture's equilibrium properties, such as vapor pressure, solubility, activity coefficients and phase diagrams [22].…”

“…In the NLF-EOS framework the implicit nonrandom contribution was made explicit by an expansion method, and the association contribution derived from Veytsmann statistics [6] was extended to include dimer formation [7,8]. The resulting hydrogen bonding nonrandom lattice fluid equation of state (NLF-HB EOS) has been proven to accurately describe various mixture properties [9], including mixtures of associating components [10], making it a suitable foundation for the group contribution approach.…”