{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T19:48:34Z","timestamp":1791229714706,"version":"4.1.0"},"reference-count":131,"publisher":"AIP Publishing","issue":"23","content-domain":{"domain":["pubs.aip.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2007,12,21]]},"abstract":"<jats:p>A predictive group-contribution statistical associating fluid theory (SAFT-\u03b3) is developed by extending the molecular-based SAFT-VR equation of state [A. Gil-Villegas et al.\u2008J. Chem. Phys.\u2008106, 4168 (1997)] to treat heteronuclear molecules which are formed from fused segments of different types. Our models are thus a heteronuclear generalization of the standard models used within SAFT, comparable to the optimized potentials for the liquid state OPLS models commonly used in molecular simulation; an advantage of our SAFT-\u03b3 over simulation is that an algebraic description for the thermodynamic properties of the model molecules can be developed. In our SAFT-\u03b3 approach, each functional group in the molecule is modeled as a united-atom spherical (square-well) segment. The different groups are thus characterized by size (diameter), energy (well depth) and range parameters representing the dispersive interaction, and by shape factor parameters (which denote the extent to which each group contributes to the overall molecular properties). For associating groups a number of bonding sites are included on the segment: in this case the site types, the number of sites of each type, and the appropriate association energy and range parameters also have to be specified. A number of chemical families (n-alkanes, branched alkanes, n-alkylbenzenes, mono- and diunsaturated hydrocarbons, and n-alkan-1-ols) are treated in order to assess the quality of the SAFT-\u03b3 description of the vapor-liquid equilibria and to estimate the parameters of various functional groups. The group parameters for the functional groups present in these compounds (CH3, CH2, CH3CH, ACH, ACCH2, CH2\ue5fb, CH\ue5fb, and OH) together with the unlike energy parameters between groups of different types are obtained from an optimal description of the pure component phase equilibria. The approach is found to describe accurately the vapor-liquid equilibria with an overall %AAD of 3.60% for the vapor pressure and 0.86% for the saturated liquid density. The fluid phase equilibria of some larger compounds comprising these groups, which are not included in the optimization database and some binary mixtures are examined to confirm the predictive capability of the SAFT-\u03b3 approach. A key advantage of our method is that the binary interaction parameters between groups can be estimated directly from an examination of pure components alone. This means that as a first approximation the fluid-phase equilibria of mixtures of compounds comprising the groups considered can be predicted without the need for any adjustment of the binary interaction parameters (which is common in other approaches). The special case of molecular models comprising tangentially bonded (all-atom and united-atom) segments is considered separately; we comment on the adequacy of such models in representing the properties of real molecules.<\/jats:p>","DOI":"10.1063\/1.2813894","type":"journal-article","created":{"date-parts":[[2007,12,21]],"date-time":"2007-12-21T23:42:16Z","timestamp":1198280536000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":230,"title":["A group contribution method for associating chain molecules based on the statistical associating fluid theory (SAFT-\u03b3)"],"prefix":"10.1063","volume":"127","author":[{"given":"Alexandros","family":"Lymperiadis","sequence":"first","affiliation":[{"name":"Imperial College London Department of Chemical Engineering, Centre for Process Systems Engineering, , South Kensington Campus, London SW7 2AZ, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claire S.","family":"Adjiman","sequence":"additional","affiliation":[{"name":"Imperial College London Department of Chemical Engineering, Centre for Process Systems Engineering, , South Kensington Campus, London SW7 2AZ, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amparo","family":"Galindo","sequence":"additional","affiliation":[{"name":"Imperial College London Department of Chemical Engineering, Centre for Process Systems Engineering, , South Kensington Campus, London SW7 2AZ, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Jackson","sequence":"additional","affiliation":[{"name":"Imperial College London Department of Chemical Engineering, Centre for Process Systems Engineering, , South Kensington Campus, London SW7 2AZ, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"317","published-online":{"date-parts":[[2007,12,21]]},"reference":[{"key":"2023073122455980900_c1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/S0098-1354(00)00628-1","volume":"25","year":"2001","journal-title":"Comput. 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