Time-Concentration Superposition for Linear Viscoelasticity of Polymer Solutions

Can-Qi Li; Horst Henning Winter; Yuan-Qi Fan; Geng-Xin Xu; Xue-Feng Yuan

doi:10.3390/polym15071807

Time-Concentration Superposition for Linear Viscoelasticity of Polymer Solutions

Polymers (Basel). 2023 Apr 6;15(7):1807. doi: 10.3390/polym15071807.

Authors

Can-Qi Li¹, Horst Henning Winter², Yuan-Qi Fan¹, Geng-Xin Xu¹, Xue-Feng Yuan¹

Affiliations

¹ Institute for Systems Rheology, Guangzhou University, No. 230 West Outer Ring Road, Higher Education Mega-Center, Panyu District, Guangzhou 510006, China.
² Chemical Engineering and Polymer Science & Engineering, University of Massachusetts Amherst, Silvio O. Conte National Center for Polymer Research, 120 Governors Drive, Amherst, MA 01003-3110, USA.

Abstract

The concentration dependence of linear viscoelastic properties of polymer solutions is a well-studied topic in polymer physics. Dynamic scaling theories allow qualitative predictions of polymer solution rheology, but quantitative predictions are still limited to model polymers. Meanwhile, the scaling properties of non-model polymer solutions must be determined experimentally. In present paper, the time-concentration superposition (TCS) of experimental data is shown to be a robust procedure for studying the concentration scaling properties of binary and ternary polymer solutions. TCS can not only identify whether power law scaling may exist or not, and over which concentration range, but also unambiguously estimate the concentration scaling exponents of linear viscoelastic properties for a range of non-model polymer solutions.

Keywords: polymer solutions; time–concentration superposition principle; viscoelastic properties.

Grants and funding

This research was supported by the Ministry of Science and Technology of the People’s Republic of China under the research grant 2020AAA0104804. H.H.W. also acknowledges the support of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office under Award Number DEEE0009285.