@article{scholars19543,
           title = {New correlations for screening of ionic liquids for efficient gas hydrate inhibition},
          number = {3},
          volume = {41},
            note = {cited By 2},
             doi = {10.1080/10916466.2022.2055065},
         journal = {Petroleum Science and Technology},
           pages = {257--301},
            year = {2023},
        keywords = {Gas hydrates; Hydration; Hydrogen bonds; Ionic liquids; Thermodynamic properties, Analysis techniques; Bonding energies; Dissociation temperature; Energy; Hydrate inhibition; Imidazolium; Inhibitor; Multicollinearity; New correlations; Temperature shift, Regression analysis},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129724649&doi=10.1080\%2f10916466.2022.2055065&partnerID=40&md5=bef1b4723a182d49ceb9b51f40eb2f87},
        abstract = {Regression analysis techniques were employed to develop correlations for the average temperature shift of hydrates ({\^I}?Tav) as a function of seven thermophysical properties of the ILs. These predictors are; hydrogen bonding energy (EHB), Vander Waal's energy (EvdW), the energy of misfit (EMF), the energy of interaction (EINT), density ({\"I}?), viscosity ({\^I}1/4), and molecular weight (MW). Multicollinearity effects among the variables were resolved by adopting the ridge regression approach. The regression models were developed from over 200 experimental data points involving 1-methyl-3-propyl-imidazolium ILs (PMIM-ILs), 1-(3-cyanopropyl)-3-methylimidazolium ILs (CPMIM-ILs), 1,3-dimethyl-imidazolium ILs (DMIM-ILs), 1-butyl-3-methylimidazolium ILs (BMIM-ILs), and 1-Ethyl-3-methylimidazolium ILs (EMIM-ILs). The predictive models were developed in three categories: Several ILs, BMIM-ILs, and the EMIM-IL models. Analysis shows that the prediction of {\^I}?Tav from models developed from the thermophysical data obtained from specific IL models is more accurate than those obtained from Several ILs models. Except for 1-Ethyl-3-methylimidazolium dicyanamide (EMIM-DCN) IL, the percentage accuracy of the models ranges between 81.56 and 99.91. The new models present a significantly simpler and more accurate way to optimize the inhibitor synthesis, selection, and validation process for practical purposes. {\^A}{\copyright} 2022 Taylor \& Francis Group, LLC.},
          author = {Sulaimon, A. A. and Murungi, P. I. and Mohshim, D. F. B.}
}