Affiliation:
1. Univ Lyon, Ens de Lyon, CNRS, Laboratoire de Physique 1 , 69342 Lyon, France
2. Groupe CFL, CEMEF, Mines Paris PSL 2 , 1 Rue Claude Daunesse, 06904 Sophia Antipolis, France
3. CEA, DES, ISEC, DE2D, SEAD, LCBC, Université of Montpellier 3 , Marcoule, France
Abstract
The rheological behavior of colloidal dispersions is of paramount importance in a wide range of applications, including construction materials, energy storage systems, and food industry products. These dispersions consistently exhibit non-Newtonian behaviors, a consequence of intricate interplays involving colloids morphology, volume fraction, and interparticle forces. Understanding how colloids structure under flow remains a challenge, particularly in the presence of attractive forces leading to cluster formation. In this study, we adopt a synergistic approach, combining rheology with ultra small-angle x-ray scattering, to probe the flow-induced structural transformations of attractive carbon black (CB) dispersions and their effects on the viscosity. Our key findings can be summarized as follows. First, testing different CB volume fractions, in the high shear rate hydrodynamic regime, CB particles aggregate to form fractal clusters. Their size conforms to a power law of the shear rate, ξc∝γ˙−m, with m≃0.5. Second, drawing insights from the fractal structure of clusters, we compute an effective volume fraction ϕeff and find that microstructural models adeptly account for the hydrodynamic stress contributions. We identify a critical shear rate γ∗˙ and a critical volume fraction ϕeff∗, at which the clusters percolate to form a dynamical network. Third, we show that the apparent yield stress measured at low shear rates inherits its properties from the percolation point. Finally, through data scaling and the integration of Einstein’s viscosity equation, we revisit and discuss the Caggioni–Trappe–Spicer model, revealing a significant connection between its empirical parameters and the structural properties of CB dispersions under flow.
Funder
Agence Nationale de la Recherche
Marie Skłodowska-Curie Industrial Doctoral Network