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dc.contributor.authorChung, Yunsie
dc.contributor.authorGillis, Ryan J.
dc.contributor.authorGreen Jr, William H
dc.date.accessioned2020-06-02T18:32:07Z
dc.date.available2020-06-02T18:32:07Z
dc.date.issued2020-03-27
dc.identifier.issn0001-1541
dc.identifier.issn1547-5905
dc.identifier.urihttps://hdl.handle.net/1721.1/125628
dc.description.abstractWe present a new strategy to estimate the temperature‐dependent vapor–liquid equilibria and solvation free energies of dilute neutral molecules based on only their estimated solvation energy and enthalpy at 298 K. These two pieces of information coupled with matching conditions between the functional forms developed by Japas and Levelt Sengers for near critical conditions and by Harvey for low and moderate temperature conditions allow the fitting of a piecewise function that predicts the temperature‐dependent solvation energy for dilute solutes up to the critical temperature of the solvent. If the Abraham and Mintz parameters for the solvent and solute are available or can be estimated from group contributions, this method requires no experimental data and can still provide accurate estimates with an error of about 1.6 kJ/mol. This strategy, which requires minimal computational resources, is shown to compare well with other methods of temperature‐dependent solvation free energy prediction.en_US
dc.description.sponsorshipEni S.p.A. (Award 5210000949)en_US
dc.publisherWileyen_US
dc.relation.isversionofhttps://dx.doi.org/10.1002/aic.16976en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Greenen_US
dc.subjectBiotechnologyen_US
dc.subjectEnvironmental Engineeringen_US
dc.subjectGeneral Chemical Engineeringen_US
dc.titleTemperature‐dependent vapor–liquid equilibria and solvation free energy estimation from minimal dataen_US
dc.typeArticleen_US
dc.identifier.citationChung, Yunsie, Ryan Gillis and William H. Green. “Temperature‐dependent vapor–liquid equilibria and solvation free energy estimation from minimal data.” AIChE Journal 66 (2020): e16976 © 2020 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.relation.journalAIChE Journalen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2020-05-11T17:35:08Z
mit.journal.volume66en_US
mit.journal.issue6en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusComplete


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