Molecular Structure-Based Methods of Property Prediction in Application to Lipids: A Review and Refinement

Larissa Cunico, Amol Hukkerikar, Roberta Ceriani, Bent Sarup, Rafiqul Gani

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The paper is a review of the combined group contribution (GC)–atom connectivity index (CI) approachfor prediction of physical and thermodynamic properties of organic chemicals and their mixtures withspecial emphasis on lipids. The combined approach employs carefully selected datasets of different purecomponent properties to develop simultaneously two parallel models, one based on group contribu-tion and another based on atom connectivity, for each property. The lipids present in the databaseare regarded as a separate class, for which special models for pure component properties, primary andtemperature dependent, have been developed. For mixtures, properties related to phase equilibria aremodeled with GE-based models (UNIQUAC, UNIFAC, NRTL, and combined UNIFAC-CI method). The col-lected phase equilibrium data for VLE and SLE have been tested for thermodynamic consistency togetherwith a performance evaluation of the GE-models. The paper also reviews the role of the databases andthe mathematical and thermodynamic consistency of the measured/estimated data and the predictivenature of the developed models.
Original languageEnglish
JournalFluid Phase Equilibria
Volume357
Issue numberSpecial Issue: SI
Pages (from-to)2-18
ISSN0378-3812
DOIs
Publication statusPublished - 2013

Keywords

  • Group contribution+(GC+) approach
  • Property modeling
  • Lipids
  • Pure component properties
  • Mixture properties

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