On the Viscosity and Pipe Transport Behavior of Pure Ionic Liquids and Their Mixtures with Conventional Solvents

Abstract

This work addresses two interconnected topics: the viscosity-temperature behavior of ionic liquids and the techno-economic aspects of their pipe transport. A diverse selection of ionic liquids, conventional solvents, and their mixtures—covering a wide viscosity range—was analyzed under transport conditions representative of industrial processes. Based on an extensive experimental database compiled from the literature, new empirical correlations were developed to estimate the viscosity-temperature relationships of ionic liquids, using only their viscosities at 298.15 K. Rigorous simulations of pipe transport were conducted using the Pipe Segment model in Aspen HYSYS. A continuous transition in transport behavior was observed, ranging from highly viscous ionic liquids to low-viscosity solvents and their mixtures. This observation enables the use of heuristics developed for conventional fluids in the design of transport operations involving ionic liquids, provided that their specific characteristics are appropriately considered. Under the conditions and economic scenarios analyzed, the most cost-effective strategy for transporting viscous fluids involves using pipes with the largest feasible internal diameter, regardless of whether they are constructed from carbon steel or stainless steel. The use of conventional solvents as viscosity reducers does not appear to be economically viable, except when they are already present as impurities in the ionic liquid following purification. This may, additionally, reduce the cost associated with ionic liquid recovery. Leveraging heat integration instead of relying on external heating fluids for the thermal conditioning of ionic liquids can reduce transport costs by enabling operation at higher temperatures, which increases fluid velocity without exceeding the pressure drop limit.

Keywords

ionic liquids / solvent mixtures / viscosity / fluid transport / process modeling

References

[1] Singh P.; Rajkhowa S.; Sen A.; et al. Handbook of Ionic Liquids:Fundamentals, Applications, And sustainability; John Wiley & Sons: Hoboken, NJ USA, 2024. https://doi.org/10.1002/9783527839520.

[2] Kalb R.S. Commercial applications of ionic liquids. In Toward Industrialization of Ionic Liquids; Springer: Berlin/Heidelberg, Germany, 2020.

[3] Gao N.; Yang Y.; Wang Z.; et al. Viscosity of ionic liquids: Theories and models. Chem. Rev. 2023, 124, 27-123. https://doi.org/10.1021/acs.chemrev.3c00339.

[4] Jiang S.; Hu Y.; Wang Y.; et al. Viscosity of typical room-temperature ionic liquids: A critical review. J. Phys. Chem. Ref. Data 2019, 48, 033101. https://doi.org/10.1063/1.5090486.

[5] Mota-Martinez M.T.; Brandl P.; Hallett J.P.; et al. Challenges and for the utilisation of ionic liquids as solvents for CO2 capture. Mol. Syst. Des. Eng. 2018, 3, 560-571. https://doi.org/10.1039/c8me00009c.

[6] Hospital-Benito D.; Lemus J.; Moya C.; et al. Process analysis overview of ionic liquids on CO2 chemical capture. Chem. Eng. J. 2020, 390, 124509. https://doi.org/10.1016/j.cej.2020.124509.

[7] Palomar J.; Larriba M.; Lemus J.; et al. Demonstrating the key role of kinetics over thermodynamics in the selection of ionic liquids for CO2 physical absorption. Sep. Purif. Technol. 2019, 213, 578-586. https://doi.org/10.1016/j.seppur.2018.12.059.

[8] Mota-Martinez M.T.; Hallett J.P.; Mac Dowell N. Solvent selection and design for CO2 capture—How we might have been missing the point. Sustain. Energy Fuels 2017, 1, 2078-2090. https://doi.org/10.1039/c7se00404d.

[9] Zhang X.-M.; Huang K.; Xia S.; et al. Low-viscous fluorine-substituted phenolic ionic liquids with high performance for capture of CO2. Chem. Eng. J. 2015, 274, 30-38. https://doi.org/10.1016/j.cej.2015.03.052.

[10] Meindersma G.W.; de Haan A.B. Cyano-containing ionic liquids for the extraction of aromatic hydrocarbons from an aromatic/aliphatic mixture. Sci. China-Chem. 2012, 55, 1488-1499. https://doi.org/10.1007/s11426-012-4630-x.

[11] Muhammad N.; Man Z.B.; Bustam M.A.; et al. Synthesis and thermophysical properties of low viscosity amino acid-based ionic liquids. J. Chem. Eng. Data 2011, 56, 3157-3162. https://doi.org/10.1021/je2002368.

[12] Gonzalez E.J.; Alonso L.; Dominguez A. Physical properties of binary mixtures of the ionic liquid 1-methyl-3-octylimidazolium chloride with methanol, ethanol, and 1-propanol at T = (298.15, 313.15, and 328.15) K and at P = 0.1 MPa. J. Chem. Eng. Data 2006, 51, 1446-1452. https://doi.org/10.1021/je060123k.

[13] Gomez E.; Gonzalez B.; Dominguez A.; et al. Dynamic viscosities of a series of 1-alkyl-3-methylimidazolium chloride ionic liquids and their binary mixtures with water at several temperatures. J. Chem. Eng. Data 2006, 51, 696-701. https://doi.org/10.1021/je050460d.

[14] Seddon K. Ionic liquids: Designer solvents for green synthesis. Chem. Eng. 2002, 33-35.

[15] Freemantle M. Designer solvents—Ionic liquids may boost clean technology development. Chem. Eng. News 1998, 76, 32-37. https://doi.org/10.1021/cen-v076n013.p032.

[16] Palomar J.; Lemus J.; Navarro P.; et al. Process simulation and optimization on ionic liquids. Chem. Rev. 2024, 124, 1649-1737. https://doi.org/10.1021/acs.chemrev.3c00512.

[17] de Riva J.; Ferro V.R.; del Olmo L.; et al. Statistical refinement and fitting of experimental viscosity-to-temperature data in ionic liquids. Ind. Eng. Chem. Res. 2014, 53, 10475-10484. https://doi.org/10.1021/ie5014426.

[18] Ferro V.R.; Moya C.; Moreno D.; et al. Enterprise ionic liquids database (ILUAM) for use in Aspen ONE programs suite with COSMO-based property methods. Ind. Eng. Chem. Res. 2018, 57, 980-989. https://doi.org/10.1021/acs.iecr.7b04031.

[19] Andrade E.N.C. The viscosity of liquids. Nature 1930, 125, 309-310.

[20] Aspen Technology. Aspen Plus (v 15.0) Help; Aspen Technology Inc: Bedfordm, MA, USA, 2025.

[21] Lin S.T.; Sandler S.I. A priori phase equilibrium prediction from a segment contribution solvation model. Ind. Eng. Chem. Res. 2002, 41, 899-913. https://doi.org/10.1021/ie001047w.

[22] Payne G.A.; Palmer C.M.; Brill J.P.; et al. Evaluation of inclined pipe, 2-phase liquid holdup and pressure loss correlations using experimental data. J. Pet. Technol. 1979, 31, 1198-1208.

[23] Beggs H.D.; Brill J.P. Study of 2-phase flow in inclined pipes. J. Pet. Technol. 1973, 25, 607-617.

[24] Ulrich, G.D.; Vasudevan P.T. Chemical Engineering Process Design and Economics:A Practical Guide, 2nd, ed.; Process Publishing: Port Townsend, WA, USA, 2004.

[25] Towler G.; Sinnot R. Chemical Engineering Design:Principles, Practice and Economics of Plant and Process Design; Elsevier: Boston, MA, USA, 2008.

[26] Woods D.R. Rules of Thumb in Engineering Practice; John Wiley & Sons: Hoboken, NJ, USA, 2008.

[27] Turton R.; Bailie R.C.; Whiting W.B.; et al. Analysis, Synthesis and Design of Chemical Processes; Prentice Hall: Upper Saddle River, NJ, USA, 2012.

[28] Branan C. Rules of Thumb for Chemical Engineers; Elsevier: Burlington,MA USA, 2005.

[29] Gouveia A.S.L.; Tome L.C.; Marrucho I.M. Density, viscosity, and refractive index of ionic liquid mixtures containing cyano and amino acid-based anions. J. Chem. Eng. Data 2016, 61, 83-93. https://doi.org/10.1021/acs.jced.5b00242.

[30] Lundstedt T.; Seifert E.; Abramo L.; et al. Experimental design and optimization. Chemom. Intell. Lab. Syst. 1998, 42, 3-40. https://doi.org/10.1016/s0169-7439(98)00065-3.

[31] Bezerra M.A.; Santelli R.E.; Oliveira E.P.; et al. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 2008, 76, 965-977. https://doi.org/10.1016/j.talanta.2008.05.019.

[32] Doehlert D.H. Uniform shell designs. J. R. Stat. Society. Ser. C 1970, 19, 231-239.

[33] Marquardt D.W. An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 1963, 11, 431-441. https://doi.org/10.1137/0111030.

[34] de Oña J.; Garrido C. Extracting the contribution of independent variables in neural network models: A new approach to handle instability. Neural Comput. Appl. 2014, 25, 859-869. https://doi.org/10.1007/s00521-014-1573-5.

[35] Eiden P.; Bulut S.; Koechner T.; et al. In silico predictions of the temperature-dependent viscosities and electrical conductivities of functionalized and nonfunctionalized ionic liquids. J. Phys. Chem. B 2011, 115, 300-309. https://doi.org/10.1021/jp108059x.

[36] COSMOThermX,version 20.0.0, Revision 5273M;Dassault Systems: Waltham, MA, USA, 2019.

[37] Omar Valderrama J.; Makarena Munoz J.; Erasmo Rojas R. Viscosity of ionic liquids using the concept of mass connectivity and artificial neural networks. Korean J. Chem. Eng. 2011, 28, 1451-1457. https://doi.org/10.1007/s11814-010-0512-0.

[38] Luyben W.L. Principles and Case Studies of Simultaneous Design; John Wiley & Sons: Hoboken, NJ, USA, 2010.

[39] Seider W.D.; Seader J.D.; Lewin D.R. Process Design & Principles: Synthesis, Analysis and Evaluation, 2nd ed.; John Wiley & Sons, Inc.: New York, NY USA, 1999.