Pincus, I.Rodger, A.Prakash, J. Ravi2025-06-302025-06-300148-6055ORCID:/0000-0002-7111-3024/work/168398435WOS:000914694400001http://www.scopus.com/inward/record.url?scp=85146833130&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733765637Although the nonequilibrium behavior of polymer solutions is generally well understood, particularly in extensional flow, there remain several unanswered questions for dilute solutions in simple shear flow, and full quantitative agreement with experiments has not been achieved. For example, experimental viscosity data exhibit qualitative differences in shear-thinning exponents, the shear rate for the onset of shear-thinning, and high-shear Newtonian plateaus depending on polymer semiflexibility, contour length, and solvent quality. While polymer models are able to incorporate all of these effects through various spring force laws, bending potentials, excluded volume (EV) potentials, and hydrodynamic interaction (HI), the inclusion of each piece of physics has not been systematically matched to experimentally observed behavior. Furthermore, attempts to develop multiscale models (in the sense of representing an arbitrarily small or large polymer chain) which can make quantitative predictions are hindered by the lack of ability to fully match the results of bead-rod models, often used to represent a polymer chain at the Kuhn-step level, with bead-spring models, which take into account the entropic elasticity. In light of these difficulties, this work aims to develop a general model based on the so-called FENE-Fraenkel spring, originally formulated by Larson and co-workers [J. Chem. Phys. 124 (2006)], which can span the range from rigid rod to traditional entropic spring, as well as include a bending potential, EV, and HI. As we show, this model can reproduce, and smoothly move between, a wide range of previously observed polymer solution rheology in shear flow.This research was supported by an Australian Government Research Training Program (RTP) Scholarship. Simulations were performed on the MonARCH HPC Cluster through the Monash eResearch Centre and eSolutions-Research Support Services, as well as the MASSIVE HPC facility (www.massive.org.au), and the Gadi supercomputing cluster through resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government. The authors would also like to thank Aritra Santra, Dominic Robe, and R. Kailasham for helpful advice on the efficient implementation of several algorithms used in the paper.30enPublisher Copyright: © 2023 The Society of Rheology.Broken vertical bar2023-01-1310.1122/8.000051710.1122/8.000051785146833130