Rheologica Acta最新文献

Nonlinear shear and elongational start-up data of three entangled PS solutions consisting of the same weight fraction of a linear long-chain polystyrene PS-600 k and three different styrene oligomeric solvents were recently reported by Cui et al. (Rheol Acta 64:97-105, 2025). The solvents are two linear styrene oligomers of different molecular weights as well as a star styrene oligomer. We show that start-up of shear viscosity and apparent normal stress difference as well as start-up of elongational viscosity can consistently be described by the Rotation Zero Stretch (RZS) model (Rheol Acta 63:573, 2024; Phys Fluids 36:093124, 2024), which is based on the tube model and a flow-strength sensitive evolution equation of stretch. In extensional flows, the RZS model reduces to the Enhanced Relaxation of Stretch (ERS) model (J Rheol. 65:1413, 2021). The modeling is based exclusively on the linear-viscoelastic characterization of the solutions and a consistent set of Rouse stretch relaxation times for PS-600 k.

Graphical Abstract

Dense suspensions with high solid volume fractions ((phi ge 0.5)) are prevalent in nature and throughout industry. These highly loaded suspensions can exhibit complex rheological behaviors, including both shear thinning and subsequent thickening with increasing shear rate. Understanding the mechanisms behind these rheological behaviors can improve the design of materials systems to behave as predicted and desired under process flows. Here, we present a study on an industrially relevant, dense ((phi =0.55)), colloidal alumina suspension and show how the addition and loading of a non-adsorbing polyvinylpyrrolidone (PVP) at different molecular weights can be used to tune and control its rheological properties. PVP was added at varying concentrations spanning the dilute and semi-dilute non-entangled regimes for each molecular weight. The addition of PVP at concentrations in the dilute regime was shown to increase the viscosity of the suspension and induce discontinuous shear thickening (DST). However, further increases in PVP loading particularly within the semi-dilute non-entangled regime and at higher PVP molecular weights also increased the dynamic yield stress of the material, made the suspension more shear thinning, and delayed the onset of DST. Rheological measurements were coupled with insights on the relevant particle and polymer length scales from small angle neutron scattering (SANS), including Rheo-SANS measurements, to inform on the mechanisms by which non-adsorbing polymers influence suspension rheology across multiple flow regimes.

Graphical abstract

Clay-polymer mixtures, characterised by high mechanical stiffness, are widely utilised in strengthening soft and easy-to-break materials. Here, we present microrheological results on shake-gels made of natural (montmorillonite) and synthetic (Laponite) disk-shaped clay particles in combination with poly(ethyleneoxide). These clay-polymer suspensions represent shear-thickening fluids that display a large increase in viscosity upon large-amplitude shaking. By performing both bulk and microrheology experiments, we probe the phase behaviour and mechanical response of these nanocomposites. Slight tuning of either the particle or polymer concentration leads to dramatic changes in the macroscopic appearance of the mixture, transitioning from a low-viscosity fluid to a stiff gel, capable of sustaining its own weight. We relate these observations to microscopic measurements, providing insight into the local reorganisation of the constituting building blocks and the time-evolution of each phase.

In this paper, the temperature and frequency sweep experiments for ethylene propylene diene monomer (EPDM) samples are performed, and the master curves of the dynamic mechanical properties of EPDM rubber are built by using time–temperature superposition principle (TTSP). It shows that the EPDM rubber exhibits temperature- and frequency-dependent properties, and its temperature T_α at which the dissipation is maximum for a given frequency increases with the frequency. The constructed master curve can characterize the dynamic mechanical properties of EPDM rubber covering 12 decades on the angular frequency scale. Then, the fractional derivative Kelvin (FDK) model and the fractional derivative Zener (FDZ) model are introduced, and a fractional derivative five-element (FDFE) model is proposed. The master curves of EPDM rubber are fitted by using these models. The results indicate that compared with the FDK and FDZ models, the FDFE model has more discrete relaxation times due to its multiple parallel branches, which enables it to accurately describe the dynamic mechanical behavior of EPDM rubber and well characterize the asymmetric characteristics of the loss factor curve. Finally, the influences of parameters in the FDFE model on the dynamic mechanical performance curves of polymers are investigated. It suggests that both fractional parameters and relaxation times control the dynamic response mechanisms, and the proposed FDFE model has a potential broad applicability in characterizing the dynamic mechanical properties of polymers. 

Graphical Abstract

We numerically evaluate the performance of two pendant drop techniques — Capillary Pressure Tensiometry (CPT) and Stress-Fitting Elastometry (SFE) — based on their ability to calculate the interfacial stress and dilatational rheological properties of complex interfaces. Although both methods incorporate simultaneous shape and pressure measurements, CPT assumes a spherical cap shape with isotropic deformations, allowing the interface to be fully characterized by a single scalar value for the surface stress. On the contrary, SFE accounts for mechanically resistant interfaces that exhibit non-uniform tensorial strain and stress fields. To compare these methods, we numerically generate drops with perfectly elastic (non-dissipative) interfaces and subject them to step-strain compressions of varying magnitudes. The calculations span a range of dimensionless parameters representing realistic drop volumes, geometries, and physical properties. We show that the local strain and/or stress vary along the surface, depending on the relative magnitude of the shear versus dilatational moduli. We analyze the strained interfaces using CPT and SFE, quantitatively evaluating their ability to predict the interfacial strains, stresses, and dilatational moduli. We then identify the configurations and analysis methods that yield the most accurate results. Finally, we assess the robustness of these methods by introducing random Gaussian noise to the interface profiles, with a magnitude comparable to experimental errors from image acquisition and processing. The performance of both methods is compared under both idealized and experimentally realistic (noisy) conditions.

The interaction between the slow and fast eigenmodes of a viscoelastic material gives rise to “dampened elasticity,” playing a crucial role in both technical applications and natural processes. This phenomenon occurs during the flow of a viscoelastic liquid or the deformation of a viscoelastic solid, as slow eigenmodes work to elastically restore the material’s previous shapes, while fast relaxation modes resist any such elastic recovery by attempting to preserve the material’s current shape. In this way, fast modes create a viscous background that dampens elastic recovery. Elastic-dominated and viscous-dominated stress components act across a sequence of process times, 0 < s < ∞, when probing eigenmodes with a spectrum of relaxation times spanning 0 < τ < τ_max. Classification of an eigenmode as fast or slow depends on the respective value of the Deborah function, D(τ;s) = τ/s, a key parameter introduced here. The critical value D = 1 separates the eigenmodes into two groups, those dominated by elasticity (D > 1) and those dominated by viscosity (D < 1). The resulting ratio of elastic to viscous stress, referred to as elastic-to-viscous ratio EVR, defines the viscoelastic state of soft matter under specific flow or strain conditions. The EVR(x,t) can vary with position (x) and/or evolve over time. Additionally, the damping potential, P_d, defines the ratio of transient to permanent elasticity in solids. Illustrating examples involve gels and the process of gelation with its characteristic evolution of relaxation times. The distinction between elasticity-dominated and viscosity-dominated stress is equally applicable to linear and non-linear viscoelasticity.

Graphical Abstract

Accurately resolving spatially inhomogeneous flows is one of the essential roles of computational rheology. Compared to conventional flow predictions using constitutive models (CMs), multiscale simulations (MSSs), where mesoscopic models are embedded in macroscopic computational domains, offer accurate predictions but are accompanied by high computational costs. To avoid the computational issue in these MSSs (which we refer to as “full”-MSSs), we employed machine learning (ML) techniques, which we denote as “ML”-MSS, to predict spatially inhomogeneous flows. We obtained approximate CMs using a sparse identification algorithm for training data numerically generated by the dumbbell-based mesoscopic model with the Hookean or finite extensible nonlinear elastic (FENE) spring. Our sparse identification algorithm accurately identifies the CM for the dumbbell model with the Hookean spring and provides an approximate CM that reproduces the shear rheology of the dumbbell model with the FENE spring. The ML-MSSs with these CMs were compared to the full-MSSs for a flow between parallel plates driven by an external force. We confirmed that the relative error in the primary velocity along the centerline between ML-MSS and full-MSS is within approximately 20%, indicating the fundamental validity of our data-driven approach, with a computational time equivalent to that of a conventional approach employing CMs.