ABSTRACT Accurate prediction of viscosity reduction is a prerequisite for optimizing advanced polymer recycling and processing technologies, particularly, when dealing with complex fluids such as postconsumer (PCRs) or diluted melts. This study presents a comprehensive rheological framework characterizing the flow behavior of high‐density polyethylene (PE‐HD) and low‐density polyethylene PCR diluted with ‐decane (C10), a specialty recycling solvent from the CreaSolv‐technology (CS), and supercritical carbon dioxide () using an in‐line slit‐die rheometer. By systematically evaluating three modeling approaches of increasing physical depth, we bridge the gap between fundamental thermodynamics and practical process control. While parallel‐plate rheometry confirmed the absence of wall slip in the investigated shear rate regime, the modeling analysis revealed distinct trade‐offs between physical fidelity and predictive capability. A semiempirical model utilizing an exponential (Arrhenius‐like) concentration term demonstrated good performance for the observed diluent concentration regime, achieving mean relative errors for all diluent systems below 5%. In contrast, a fundamental approach coupling the Sanchez–Lacombe Equation of State (EOS) with the Kelley–Bueche theory successfully validated the functional form of dilution but consistently underestimated the magnitude of viscosity reduction. Ultimately, this work derives a physically validated, four‐parameter semiempirical model that eliminates the need for complex molecular weight data as needed for the reptation‐based Schausberger model, enabling the direct integration of rheological predictions for variable PCR feedstocks into digital twins and real‐time process optimization tools.
Viehböck et al. (Sat,) studied this question.