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dc.contributor.authorSalam, M.A.
dc.contributor.authorAbdullah, B.
dc.contributor.authorRamli, A.
dc.contributor.authorMujtaba, Iqbal M.
dc.date.accessioned2016-11-15T15:30:54Z
dc.date.available2016-11-15T15:30:54Z
dc.date.issued2016-12
dc.identifier.citationSalam Abdus M, Abdullah B, Ramli A and Mujtaba IM (2016) Structural feature based computational approach of toxicity prediction of ionic liquids: Cationic and anionic effects on ionic liquids toxicity. Journal of Molecular Liquids. 224, A: 393–400.en_US
dc.identifier.urihttp://hdl.handle.net/10454/10342
dc.descriptionyesen_US
dc.description.abstractThe density functional theory (DFT) based a unique model has been developed to predict the toxicity of ionic liquids using structural-feature based quantum chemical reactivity descriptors. Electrophilic indices (ω), the energy of highest occupied (EHOMO) and lowest unoccupied molecular orbital, (ELUMO) and energy gap (∆ E) were selected as the best toxicity descriptors of ILs via Pearson correlation and multiple linear regression analyses. The principle components analysis (PCA) demonstrated the distribution and inter-relation of descriptors of the model. A multiple linear regression (MLR) analysis on selected descriptors derived the model equation for toxicity prediction of ionic liquids. The model predicted toxicity values and mechanism are very consistent with observed toxicity. Cationic and side chains length effect are pronounced to the toxicity of ILs. The model will provide an economic screening method to predict the toxicity of a wide range of ionic liquids and their toxicity mechanism.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttp://dx.doi.org/10.1016/j.molliq.2016.09.120en_US
dc.rights© 2016 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.en_US
dc.subjectIonic liquid; Density functional theory (DFT); Toxicity; Electrophilicity index; EHOMO; ELUMO; Cations; Anionsen_US
dc.titleStructural feature based computational approach of toxicity prediction of ionic liquids: Cationic and anionic effects on ionic liquids toxicityen_US
dc.status.refereedyesen_US
dc.date.Accepted2016-09-29
dc.date.application2016-10-01
dc.typeArticleen_US
dc.type.versionAccepted Manuscripten_US
refterms.dateFOA2018-07-27T02:06:06Z


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