Development of corresponding states model for estimation of the surface tension of chemical compounds

Farhad Gharagheizi, Ali Eslamimanesh, Mehdi Sattari, Amir H. Mohammadi, Dominique Richon

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The gene expression programming (GEP) strategy is applied for presenting two corresponding states models to represent/predict the surface tension of about 1,700 compounds (mostly organic) from 75 chemical families at various temperatures collected from the DIPPR 801 database. The models parameters include critical temperature or temperature/critical volume/acentric factor/critical pressure/reduced temperature/reduced normal boiling point temperature/molecular weight of the compounds. Around 1,300 surface tension data of 118 random compounds are used for developing the first model (a four‐parameter model) and about 20,000 data related to around 1,600 compounds are applied for checking its prediction capability. For the second one (a five‐parameter model), about 10,000 random data are applied for its development, and 11,000 data are used for testing its prediction ability. The statistical parameters including average absolute relative deviations of the results form dataset values (25 and 18% for the first and second models, respectively) demonstrate the accuracy of the presented models. © 2012 American Institute of Chemical Engineers AIChE J, 59: 613–621, 2013
Original languageEnglish
JournalA I Ch E Journal
Volume59
Issue number2
Pages (from-to)613-621
ISSN0001-1541
DOIs
Publication statusPublished - 2013

Bibliographical note

Theme: Thermodynamics and Molecular-Scale Phenomena

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