Abstract
-Viscosity estimation of ionic liquid (IL) containing mixtures is highly demanded due to increasing application of ILs in different industrial fields. This study investigates the capability of adaptive neuro fuzzy inference system (ANFIS) strategy in the estimation of the viscosity of mixtures containing ionic liquids. A database containing 12 ternary mixtures including Ethyl acetate (1) + ethanol (2) + [Omim][BTI], Methyl acetate + methanol+ [Omim][BTI], Isopropyl acetate+ 2-propanol + [Omim][BTI], Ethyl acetate + ethanol+ [Bmim][BTI], Ethanol + water+ [Emim][C2H5SO4], 1-Propanol + water + [Emim][C2H5SO4], 2-Propanol + water + [Emim][C2H5SO4], Water + ethanol + [Emim][OAC], Ethanol + water+ [Bmim][CH3SO4], Ethanol + water+ [Mmim][CH3SO4], [MEDA][CH3SO4] + water + methanol, and [MEDA][CH3SO4]+ water + ethanol was used which is comprised of 800 data points. The proposed ANFIS model estimates the viscosity of mixtures as a function of 11 input parameters. Results are then compared to three thermodynamic results namely Eyring-UNIQUAC, Eyring-NRTL, and Eyring-Wilson equations and the great accuracy of ANFIS strategy over thermodynamic models is confirmed with an average absolute relative deviation (AARD%) value of 0.945% for the total data set.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
