Pier Luca Maffettone

The morphology of immiscible polymer blends generated during twin-screw extrusion depends on the deformation history of the dispersed phase and on the matrix rheology. Here, this effect is investigated numerically in a two-dimensional, co-rotating, fully intermeshing batch twin-screw extruder. A Newtonian dispersed phase is considered, while the matrix is modeled as Newtonian, a Generalized Newtonian Fluid (GNF) accounting for shear thinning, and a Generalized Newtonian Fluid with Flow-Type dependence (GNFFTy), which combines shear thinning in shear-dominated regions and elongational thickening in extension-dominated regions. Velocity-gradient histories along tracer trajectories are used in a morphology model including droplet deformation, breakup, filament stretching, and coalescence. The three rheologies give similar gross flow structures but different local viscosity fields. The GNF model reduces viscosity in high shear regions, whereas GNFFTy predicts localized viscosity enhancement in extensional screw-screw gaps. These differences affect breakup, showing that shear-rate-based morphology predictions may miss topology-dependent viscosity effects.

The behavior of charged vesicle suspensions, commonly encountered in biological and industrial contexts, is largely governed by screened electrostatic repulsions. However, the addition of depletants such as polymers can induce attractive interactions and lead to gel formation. Here, we investigate the rheology and yielding behavior of such a vesicle gel, relevant to a class of consumer products. The combination of experiments and Brownian dynamics simulations enables us to establish connections between macroscopic rheology and microstructural features. Oscillatory tests reveal a predominantly elastic response at small deformations, followed by yielding upon increasing the strain amplitude. With increasing shear rate, the flow curves feature a yield stress regime, followed by shear thinning and, eventually, a Newtonian-like response (viscosity plateau). We find that, in both oscillatory and shear-rate-controlled tests, the yielding transition is accompanied by nonmonotonic trends in structural heterogeneity. Fitting the flow curves with the recently introduced three-component model reveals that structural heterogeneity peaks near the crossover from the yield stress plateau to shear thinning, while homogeneity is recovered in the Newtonian-like regime. Numerical creep tests exhibit rich phenomenology, including Andrade-like deformation, delayed yielding, and resolidification, whose persistence even above the dynamic yield stress highlights the ductile nature of gels with competing attractive and repulsive interactions. Overall, our study highlights distinctive rheological and structural features of gels with competing attractive and repulsive interactions, providing insight into how microscopic heterogeneity controls yielding and flow.

Scanning large tissue slides for digital pathology, while necessary for large area coverage, can suffer from ambiguities, biased interpretations, and the inherent limitations of the staining procedure. Here we show that phase-shifting space-time digital holography (PS-STDH) could serve as an efficient digitalization of histopathology slides, encoding their 3D content into 2D wide-field quantitative phase images, while avoiding staining processes. In fact, PS-STDH approach, unlike other interferometric scanning modalities, provides an unambiguous and continuous phase distribution across the entire slide. It resolves phase unwrapping issues as it enables seamless stitching of multiple space-time holograms without phase ambiguities, directly resulting from perfect fringe matching in our hybrid hologram reprojection. Reported results demonstrate a continuous, unambiguous phase mapping over cm-long scans tested on breast cancer and fibroadenoma histopathology slides, while achieving a resolution of 0.98 μ m along the scanning direction and 1.38 μ m perpendicular to it.

We present an experimental microfluidic platform capable of reconstructing full three-dimensional trajectories of single particles in viscoelastic fluids by exploiting oscillatory flow. The system combines synchronized high-speed imaging from orthogonal perspectives with a custom-fabricated square microchannel and optical correction techniques, enabling high-resolution, time-resolved observation of particle dynamics. The device is applied to study the migration of spherical particles in Polyethylene Oxide solutions, providing the first complete measurements of particle trajectories in such flows. The effects of initial particle position, flow rate, oscillation period, and fluid rheology are systematically analyzed.

The blending of homopolymers is commonly used to create polymeric materials with synergistic properties. Most polymer blends are immiscible, consequently they have a multiphase structure, conferring them highly tunable properties. The twin-screw extruder is the most common device used for polymer compounding. In this work, the evolution of a disperse polymer blend morphology in a twin-screw extruder is studied by numerical simulations. The fluid dynamics of the blend, treated as a pseudo-homogeneous Newtonian fluid, is solved by the finite element method under quasi-steady and isothermal conditions. The velocity gradient obtained along several trajectories of the flow field is used as input in a previously developed model able to predict the blend morphology. The history of deformation of the droplets and their topological changes in terms of evolution of the stretch ratio and the unstretched droplet radius are investigated. The average blend morphology is computed for a population of droplets, highlighting the effect of the screw rotation speed and the blend viscosity ratio.

The rheological characterization of complex liquids is of great importance in many applications. Among the properties that can be measured, the relaxation time has great relevance, as it provides a measure of fluid elasticity. In this work, we propose a novel method to estimate the longest relaxation time of viscoelastic fluids by applying machine learning to microfluidics. Specifically, we train a long-short term memory (LSTM) neural network to identify the Weissenberg number that characterizes the dynamics of trains of rigid particles suspended in a viscoelastic liquid flowing in a cylindrical microchannel. We first study the effect of the Weissenberg number on the evolution of the microstructure through numerical simulations. An in silico dataset consisting of the distributions of the interparticle distances at different channel sections is built and used to train the network. The performance of the LSTM model is tested on both classification and regression problems. The proposed method is nonintrusive, requires a simple setup, and can in principle be used to measure other properties of the fluid.

The gravitational sedimentation of solid particles in liquids is important in several applications, many of which involve soft particles (e.g., microplastics, microgels, and biological cells). However, there is still little knowledge on the sedimentation of deformable beads. In this work, we employ fully three-dimensional finite-element numerical simulations to investigate the sedimentation of an initially spherical elastic bead in a Newtonian liquid contained inside a square-cross section vessel. In particular, we carry out a wide parametric analysis to understand the effects of inertia, particle deformability, and geometrical confinement on the particle sedimentation dynamics and settling velocity. In addition, the sedimentation of a particle in a Newtonian liquid close to a vertical wall is studied. When the particle sediments at the center of the vessel, the settling velocity increases at increasing inertia and decreases at increasing confinement and deformability. However, at intermediate inertia, the settling velocity passes through a minimum and then rises as the particle gets softer. Correspondingly, the equilibrium deformed shape of the particle shows the appearance of a concavity at the rear. When the sedimentation occurs close to a vertical wall, the closer the particle to the solid surface, the slower its sedimentation. On the other hand, the hydrodynamic interaction between the particle and the wall makes the particle move away from the wall.