Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Group contribution method for the residual entropy scaling model for viscosities for branched alkanes

Published

Author(s)

Erik Mickoleit, Andreas Jaeger, Constantino Grau Turelo, Monika Thol, Ian Bell, Cornelia Breitkopf

Abstract

In this work it is shown how the entropy scaling paradigm introduced by Rosenfeld can be extended to calculate the viscosities of branched alkanes by group contribution methods, making the technique more predictive. Two equations of state (EOS) requiring only a few adjustable parameters (Lee-Kesler-Plöcker and PC-SAFT) were used to calculate the thermodynamic properties of linear and branched alkanes. These EOS models were combined with first-order and second-order group contribution methods to obtain the fluid-specific scaling factor allowing the scaled viscosity values to be mapped onto the generalized correlation developed by Yang et al. The second order scheme offers a more accurate estimation of the fluid-specific scaling factor, and overall the method yields an AARD of 10 % versus 8.8 % when the fluid-specific scaling factor is fit directly to the experimental data. More accurate results are obtained when using the PC-SAFT EOS, and the GCM generally out-performs other estimation schemes proposed in the literature for the fluid-specific scaling factor.
Citation
International Journal of Thermophysics
Volume
44

Citation

Mickoleit, E. , Jaeger, A. , Grau Turelo, C. , Thol, M. , Bell, I. and Breitkopf, C. (2023), Group contribution method for the residual entropy scaling model for viscosities for branched alkanes, International Journal of Thermophysics, [online], https://doi.org/10.1007/s10765-023-03289-w, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956627 (Accessed April 27, 2024)
Created November 16, 2023, Updated December 1, 2023