Soft Matter最新文献

Biological barriers protect the human body by selectively blocking foreign material. Designing particles with coatings that efficiently transport across these barriers can increase the effectiveness and feasibility of advanced therapeutics. In particular, the mucus barrier protects the intestines, lungs, eyes, etc., complicating oral, inhaled, or ocular drug delivery. Heuristics for particle design are currently limited to the rate of diffusion within the barrier. Relying on first-principles theories for colloidal scale interactions, a cohesive model of the transport of particles through biological barriers is developed based on the barrier permeability, which incorporates essential contributions from both partitioning and diffusion. Analytical models are developed to predict partition coefficients based on particle-pore interaction potentials. Particle-pore hydrodynamics are considered to predict average diffusivities within mucus barriers. We show that kT-scale attractive interactions, that are either specific or non-specific, can yield optimal delivery of larger particles, to increase the mass flux across mucus barriers by an order of magnitude, and enable delivery of macromolecular cargo, due to enhanced partitioning. Our model indicates drug particle design rules to achieve transport rates comparable to or exceeding what is possible by viruses with highly evolved chemical and physical characteristics.

Clinically, palpation is one of the important diagnostic methods to assess tumor malignancy. In laboratory research, it is well accepted that the bulk stiffness of the tumor and the surrounding tissue is closely correlated with the malignant state of the tumor. Here, we postulate that, in addition to tumor stiffness, tumor viscoelasticity - the fact that tumor tissue takes time to bounce back after compression, can also be used to evaluate the tumor malignancy state. In this work, we characterized the viscoelastic properties of tumor spheroids using a recently developed microfluidic compression device by quantifying their relaxation dynamics upon load removal. Tumor spheroids were made using breast tumor cells spanning various malignancy levels; non-tumorigenic epithelial (MCF10A), moderately malignant tumor (MCF7) and triple negative metastatic tumor (MDA-MB-231) cell line. Spheroids embedded within a 3D extracellular matrix were periodically compressed, and their strain responses were recorded using microscopic imaging. Our results revealed that the measured strain relaxation dynamics can be successfully described by a modified power law model, demonstrated that non-tumorigenic tumor spheroids were more elastic, exhibited shorter relaxation time and less plasticity than those of tumorigenic spheroids. This work highlights that viscoelastic properties in addition to bulk stiffness of the tumor spheroids can serve as a complementary mechanical biomarker of tumor malignancy and demonstrate the validity of a modified power law model for the mechanical characterization of a living tissue.

Needle-based injection techniques are widely used in drug delivery, diagnostics, and soft material characterization, yet the mechanical influence of the insertion process on the ensuing injection behavior remains poorly understood. Here, we demonstrate that both the morphology of the expanded cavity and the resisting pressure are not only governed by material properties, but can be critically influenced, and even reliably modulated, by the preceding needle insertion and retraction processes. To investigate the insertion process, we measure the pressure developed in the droplet that is initially suspended at the tip of the needle and then driven through the material to obtain pressure-depth curves. This offers a local measure of tearing resistance that is not governed by frictional forces along the needle shaft. By systematically varying the insertion and retraction depths and speeds in two contrasting soft materials, we find that features in the pressure-depth curve reliably indicate expected outcomes of the injection procedure, as defined for different use cases. These findings reveal the insertion phase as a critical yet previously underutilized control in drug injection and needle-based mechanical testing, and establishes pressure-depth monitoring as a real-time diagnostic tool. By eliminating reliance on visual confirmation, this approach can improve the robustness, scalability, and automation potential of needle-based injection methods, particularly in opaque, biological, or high-throughput environments.

The pore radius distribution plays a significant role in characterizing the porous structure of powder particles, yet quantifying radii spanning 100 nm-10 µm-including both open and closed pores-remains challenging. Here, we propose a new method to measure the pore radius distribution. The method comprises two parts. First, the cross-section radius distribution is measured by an automated routine combining scanning-electron-microscopy (SEM) and deep-learning models. Second, a novel algorithm was developed to convert the cross-section radius distribution into a pore radius distribution. This requires a numerical solution to Wicksell's corpuscle problem, where the new algorithm outperforms the commonly used Saltikov-GCO method. We apply the proposed method to powder samples and compare the result with data from synchrotron X-ray tomography. Our approach provides more information on the distribution and agrees with the result of synchrotron X-ray tomography at a larger scale. As a secondary outcome, the algorithm can also be applied to geology and metallurgy when 3D grain size distribution is calculated from 2D grain size distributions.

Polymer-clay composites are produced using emulsion polymerization to create water-based formulations that exhibit reversible adhesion, which is triggered by alkaline or acidic aqueous solutions. These adhesives produce lap shear strengths greater than 1 MPa on a variety of substrates. A polyanionic composite is prepared by incorporating negatively charged montmorillonite into an emulsion of styrene and butyl acrylate with poly(acrylic acid) grafted from the particles. An analogue polycationic composite is made by integrating positively charged hydrotalcite into an emulsion stabilized by the physisorption of chitosan. When two substrates are both coated with the polycationic composite, reversibility is observed under acidic conditions, whereas polyanionic composites exhibit similar behaviour under alkaline conditions. Notably, polyanionic composites fully detach from the substrates, eliminating the need for additional washing. Clays also enhance the rheological behaviour of the emulsions, increasing the viscosity at low shear rates by up to 8 and 800 times, for polyanionic and polycationic formulations, respectively. These composite adhesives are a key development for facilitating the dismantling of products and enhancing recycling efficiency.

Aqueous foams are subject to coarsening, whereby gas from the bubbles diffuses through the liquid phase. Gas is preferentially transported from small to large bubbles, resulting in a gradual decrease of the number of bubbles and an increase in the average bubble size. Coarsening foams are expected to approach a scaling state at late times in which their statistical properties are invariant. However, a model predicting the experimentally observed bubble-size distribution in the scaling state of foams with moderate liquid content, as a function of the liquid fraction ϕ, has not yet been developed. To this end, we propose a three-dimensional mean-field bubble growth law for foams without inter-bubble adhesion, validated against bubble-scale simulations, and use it to derive a prediction of the scaling-state bubble-size distribution for any ϕ from zero up to the unjamming transition ϕ_c ≈ 36%. We verify that the derived scaling state is approached from a variety of initial conditions using mean-field simulations implementing the proposed growth law. Comparing our predicted bubble-size distribution with previous simulations and experimental results, we likewise find a large population of small bubbles when ϕ > 0, but there are qualitative differences from prior results which we attribute to the absence of rattlers, i.e. bubbles not pressed into contact with their neighbours, in our model.

Cells release vesicles that serve important roles in long-range signaling and intercellular communication. These vesicles are released not just in response to stress, inflammation, injury, and chemoresistance, but also during homeostatic regulation. A particular class of vesicles called ectosomes or microparticles are released by the outward budding of the plasma membrane, a process which requires both the detachment of the membrane from the cortex and the exposure of negatively charged, curvature-inducing lipids such as phosphatidylserine from the inner leaflet to the outer leaflet. In this work, we develop a biophysical model that accounts for the interaction between these different factors. Using our model, we predict how linker properties influence outward budding of the plasma membrane and identify conditions that can promote or inhibit membrane curvature generation. These findings provide insight into the fundamental mechanisms underlying microparticle formation, elucidating the basic biology of this critical process. Further, these mechanistic insights may inspire techniques for inhibiting microparticles where they are harmful, such as chemoresistant drug efflux by tumor cells.

Understanding the buried interface between silica and epoxy resin is crucial for improving the performance and reliability of epoxy composites and adhesives. Here, molecular dynamics simulations were used to reveal a heterogeneous molecular picture of aggregation and curing at the amorphous silica/epoxy interface. A density increase was observed within 2 nm of the interface, driven by the orientation and packing of epoxy and amine molecules. Smaller amines segregated near the substrate, accelerating interfacial curing in the early stages. However, subsequent reactions slowed due to restricted mobility, resulting in a ∼10% lower conversion than in the bulk. Unreacted monomers and isolated fragments accumulated near the interface, indicating adverse effects on adhesion. These findings provide molecular-level insights into buried interfaces and inform strategies for improving adhesion and reliability in epoxy-based composites and adhesives.

Polymer based electrolytes allow the absence of volatile components in batteries thus increasing their safety. Yet, they exhibit drawbacks based on their low conductivity. We have used an alternating polymer consisting of dimethyl siloxane (DMS) and ethylene glycol (EG) blocks to circumvent known disadvantages of the usually used polyethylene glycol (PEG). Incorporating dimethyl siloxane lowers the glass-transition temperature and thus reduces the segmental relaxation time, by dynamic asymmetry or internal plasticization of the constituting polymer blocks. The alternating structure ensures miscibility of the different components and hinders crystallization. Furthermore, the pure polymer, P(DMS₃-alt-EG₄), shows a segmental relaxation time well in the range needed for polymer electrolytes. Mixtures of LiClO₄ and P(DMS₃-alt-EG₄) show a drastically reduced temperature dependence of their DC conductivity in comparison to PEG based systems, resulting in an increase by two orders of magnitude at T = 5 °C and even three to four orders of magnitude at T = 0 °C. Addition of coordinating (acetonitrile) or non-coordinating (toluene) solvent increases conductivity either via additional plasticization or by weakening the Li-binding yet looking at the dynamics at low concentrations of additional solvent the mobility of the polymer is reduced. The solvent addition leads only at higher solvent concentration to a reduction in relaxation time.

Soft and deformable objects are widespread in natural and synthetic systems, including micellar domains, microgel particles, foams, and biological cells. Understanding their phase behavior at high concentrations is crucial for controlling long-range order. Here, we employ a Voronoi-based model to study the packing of deformable particles in two dimensions under thermal fluctuations. Particles are represented as interconnected polygons, with the system energy comprising penalties for deviations in area and perimeter from preferred values. The strengths of these penalties capture two key features of packing: dynamic size dispersity, mimicking chain exchange in block copolymer micelles or solvent exchange in microgels, and particle line tension, reflecting the energy cost of shape changes. The model exhibits an order-disorder transition (ODT): low perimeter penalties yield disordered states, while higher penalties produce a hexagonal crystal lattice. Large dynamic size dispersity shifts the ODT to higher perimeter penalties. We explain this by analyzing particle sizes, defect formation barriers, and Voronoi entropy, which show that defect formation is easier when the area penalty term is smaller, providing a mechanistic basis for the ODT trends. In regimes far from ODT, deviations from the hexagonal lattice are accurately described by normal mode displacement fields, confirming that thermal fluctuations rather than defects govern the structure.