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Group contribution and atomic contribution models for the prediction of various physical properties of deep eutectic solvents

2021-12Artigo científico Acesso aberto
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dc.contributor.authorHaghbakhsh, Reza
dc.contributor.authorRaeissi, Sona
dc.contributor.authorDuarte, Ana Rita C.
dc.contributor.institutionLAQV@REQUIMTE
dc.contributor.pblNature Publishing Group
dc.date.accessioned2022-10-13T22:17:59Z
dc.date.available2022-10-13T22:17:59Z
dc.date.issued2021-12
dc.descriptionPublisher Copyright: © 2021, The Author(s).
dc.description.abstractThe urgency of advancing green chemistry from labs and computers into the industries is well-known. The Deep Eutectic Solvents (DESs) are a promising category of novel green solvents which simultaneously have the best advantages of liquids and solids. Furthermore, they can be designed or engineered to have the characteristics desired for a given application. However, since they are rather new, there are no general models available to predict the properties of DESs without requiring other properties as input. This is particularly a setback when screening is required for feasibility studies, since a vast number of DESs are envisioned. For the first time, this study presents five group contribution (GC) and five atomic contribution (AC) models for densities, refractive indices, heat capacities, speeds of sound, and surface tensions of DESs. The models, developed using the most up-to-date databank of various types of DESs, simply decompose the molecular structure into a number of predefined groups or atoms. The resulting AARD% of densities, refractive indices, heat capacities, speeds of sound and surface tensions were, respectively, 1.44, 0.37, 3.26, 1.62, and 7.59% for the GC models, and 2.49, 1.03, 9.93, 4.52 and 7.80% for the AC models. Perhaps, even more importantly for designer solvents, is the predictive capability of the models, which was also shown to be highly reliable. Accordingly, very simple, yet highly accurate models are provided that are global for DESs and needless of any physical property information, making them useful predictive tools for a category of green solvents, which is only starting to show its potentials in green technology.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent4643205
dc.identifier.doi10.1038/s41598-021-85824-z
dc.identifier.issn2045-2322
dc.identifier.otherPURE: 45571328
dc.identifier.otherPURE UUID: 52859072-d048-41d8-9886-1925f19b2a4e
dc.identifier.otherScopus: 85103217763
dc.identifier.otherPubMed: 33758262
dc.identifier.otherWOS: 000634971200001
dc.identifier.otherPubMedCentral: PMC7988013
dc.identifier.otherORCID: /0000-0003-0800-0112/work/116347717
dc.identifier.urihttp://hdl.handle.net/10362/144677
dc.identifier.urlhttps://www.scopus.com/pages/publications/85103217763
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/725034/EU
dc.relationWhen solids become liquids: natural deep eutectic solvents for chemical process engineering
dc.subjectGeneral
dc.titleGroup contribution and atomic contribution models for the prediction of various physical properties of deep eutectic solventsen
dc.typejournal article
degois.publication.issue1
degois.publication.titleScientific Reports
degois.publication.volume11
dspace.entity.typePublication
oaire.awardNumber725034
oaire.awardTitleWhen solids become liquids: natural deep eutectic solvents for chemical process engineering
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/725034/EU
oaire.fundingStreamH2020
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsopenAccess
relation.isProjectOfPublicationc3c7a420-917d-40d1-8eee-26b6ad145ebd
relation.isProjectOfPublication.latestForDiscoveryc3c7a420-917d-40d1-8eee-26b6ad145ebd

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