Soft Matter最新文献

Bacteria inhabit complex environments rich in macromolecular polymers that exhibit viscoelastic properties. While the influence of viscoelasticity on bacterial swimming is recognized, its impact on chemotaxis—a critical behavior for bacterial survival and colonization—remains elusive. In this study, we employed a microfluidic device to establish attractant gradients and observed the chemotactic behavior of Escherichia coli in both viscoelastic solutions containing carboxymethyl cellulose (CMC) and Newtonian buffers. Our results reveal that E. coli demonstrates markedly enhanced chemotactic efficiency in viscoelastic media. Notably, bacteria achieved faster migration velocities and higher steady-state accumulation in areas with higher attractant concentrations compared to those in Newtonian conditions. Through 3D tracking, we determined that changes in bulk motility parameters alone do not account for the observed enhancements. Further investigations through theoretical analysis and stochastic simulations suggested that the main enhancement mechanisms are mitigation of surface hydrodynamic hindrance resulting from solid surfaces commonly present in bacterial habitats, and the induction of a lifting force in viscoelastic solutions. These findings highlight the significant role of the rheological properties of bacterial habitats in shaping their chemotactic strategies, offering deeper insights into bacterial adaptive mechanisms in both natural and clinical settings.

Eukaryotic cells sense and follow electric fields during wound healing and embryogenesis – this is called galvanotaxis. Galvanotaxis is believed to be driven by the redistribution of “sensors” – potentially transmembrane proteins or other molecules – through electrophoresis and electroosmosis. Here, we update our previous model of the limits of galvanotaxis due to the stochasticity of sensor movements to account for cell shape and orientation. Computing the Fisher information shows that, in principle, cells have more information about the electric field direction when their long axis is parallel to the field. However, for weak fields, maximum-likelihood estimators may have lower variability when the cell's long axis is perpendicular to the field. In an alternate possibility, we find that if cells instead estimate the field direction by taking the average of all the sensor locations as its directional cue (“vector sum”), this introduces a bias towards the short axis, an effect not present for isotropic cells. We also explore the possibility that cell elongation arises downstream of sensor redistribution. We argue that if sensors migrate to the cell's rear, the cell will tend to expand perpendicular the field – as is more commonly observed – but if sensors migrate to the front, the cell will tend to elongate parallel to the field.

A confined bicontinuous C₁₀E₄–D₂O–n-octane microemulsion is studied using neutron spin echo spectroscopy (NSE). Controlled pore glasses serve as confining matrices with pore diameters ranging from 24 to 112 nm. Firstly, the microemulsion in bulk is investigated by NSE and dynamic light scattering, which allows the determination of the unperturbed collective dynamics as well as the observation of the undulation of the surfactant film. In confinement, it is observed that the collective modes are drastically slowed down in all investigated pore sizes. The undulations of the surfactant film in the largest pores are found to be comparable to those of the bulk and decrease with decreasing pore diameter. Fitting procedures of the intermediate scattering function revealed that the long wavelength undulations are cut off from the spectrum of fluctuation modes due to the interactions with the pore walls.

This study reports the fabrication of non-woven fibrous membranes from electrospinning blended solutions of PVDF with polyampholytes in N,N-dimethylformamide and methanol. Polyampholytes are macromolecules that have both positive and negative charged units in different side groups attached to the backbone. In this study, we used a random polyampholyte amphiphilic copolymer (r-PAC) synthesized by co-polymerizing a hydrophobic monomer in addition to the positive and negative charged monomer units, to reduce the fouling propensity of PVDF electrospun membranes while preserving its inherent hydrophobicity. Blends of PVDF/r-PAC were electrospun across the full range of compositions from 0/100 to 100/0. Scanning electron microscopic analysis showed formation of beaded fibers with average fibril diameters from 0.09–0.18 μm. The variation in the fiber diameters is caused by the change in surface charge density, dynamic viscosity of the solution, and the instability of the Taylor cone. Bead formation was observed in the mats electrospun from less viscous solutions. Wide angle X-ray scattering showed that electrospun fibers of PVDF crystallized into the electro-active β and γ crystal phases, whereas polyampholytes were amorphous. Thermogravimetry showed that the PVDF/r-PAC blends have a multi-step thermal degradation mechanism while PVDF homopolymer showed single-step thermal degradation. Sessile drop contact angle measurements confirmed that fibers possess high hydrophobicity and super-oleophilicity. Adsorptive fouling experiments with a fluorescently labeled protein confirmed that the fiber mats obtained from the PVDF/r-PAC blends resist protein adsorption, exhibiting highly enhanced fouling resistance compared to the fibers obtained from homopolymer PVDF.

This work investigates the design of stimuli-responsive Pickering emulsions (PEs) for transdermal drug delivery applications, by exploring the impact of stabilising microgels size and interactions on their rheological and release properties. Temperature-responsive poly(N-isopropylacrylamide) microgels modified with 1-benzyl-3-vinylimidazolium bromide (pNIPAM-co-BVI) are synthesized in varying sizes and used to stabilise jojoba oil-in-water concentrated emulsions. The results reveals two distinct behaviours: for small microgels (∼300 nm), the PEs exhibit a smooth, uniform structure characterised by a mild yield stress, characteristic of soft glassy systems. Conversely, larger microgels (∼800 nm) induce droplet clustering, resulting in increased elasticity and a more complex yielding process. Interestingly, transdermal delivery tests demonstrate that microstructure, rather than bulk rheology, governs sustained drug release. The release process can be modelled as diffusion-controlled transport through a porous medium with random traps. At room temperature, the trap size corresponds to the droplet size, and the release time scales with the total dispersed phases volume fraction. However, at physiological temperature (37 °C), above the volume-phase transition temperature of the microgels, the release time increases significantly. The trap size approaches the microgel size, suggesting that microgel porosity becomes the dominant factor controlling drug release. Overall, the results highlight the critical role of microstructure design in optimising stimuli-responsive PEs for controlled transdermal drug delivery.

Growing monolayers of rod-shaped bacteria exhibit local alignment similarly to extensile active nematics. When confined in a channel or growing inward from a ring, the local nematic order of these monolayers changes to a global ordering with cells throughout the monolayer orienting in the same direction. The mechanism behind this phenomenon is so far unclear, as previously proposed mechanisms fail to predict the correct alignment direction in one or more confinement geometries. We present a strain-based model relating net deformation of the growing monolayer to the cell-level deformation resulting from single-cell growth and rotation, producing predictions of cell orientation behavior based on the velocity field in the monolayer. This model correctly predicts the direction of preferential alignment in channel-confined, inward growing, and unconfined colonies. The model also quantitatively predicts orientational order when the velocity field has no net negative strain rate in any direction. We further test our model in simulations of expanding colonies confined to spherical surfaces. Our model and simulations agree that cells away from the origin cell orient radially relative to the colony's center. Additionally, our model's quantitative prediction of the orientational order agrees with the simulation results in the top half of the sphere but fails in the lower half where there is a net negative strain rate. The success of our model bridges the gap between previous works on cell alignment in disparate confinement geometries and provides insight into the underlying physical effects responsible for large-scale alignment.

In this paper we present a computational method to analyze 2-dimensional (2D) small-angle scattering data obtained from phase-separated soft materials and output three-dimensional (3D) real-space structures of the three types of domains/phases. Specifically, we use 2D small-angle X-ray scattering (SAXS) data obtained from hydrated Nafion^TM membranes and develop a workflow using random fields to build the 3D real-space structure comprised of amorphous hydrophilic domains, amorphous polymer domains, and crystalline polymer domains. We demonstrate the method works well by showing that the reconstructed 3D Nafion^TM structures have a computed scattering profile that matches the input experimental scattering profile. Though not demonstrated in this work, such reconstructions can be used for further analysis of domain shapes and sizes, as well as prediction of transport properties through the structure. Our method in this work extends capabilities beyond the previously published random field small angle scattering reconstruction method introduced by Berk [Phys. Rev. Lett. 1987, 58 (25), 2718–2721] that had been used to reconstruct structures from 1D small angle scattering data of two-phase systems. The method in this work can be used to generate isotropic, two-phase reconstructions, but can also handle 2D SAXS profiles from three-phase systems that have structural anisotropy resulting from material processing effects.

Weak multivalent interactions govern a large variety of biological processes like cell–cell adhesion and virus–host interactions. These systems distinguish sharply between surfaces based on receptor density, known as superselectivity. Present experimental studies typically involve tens or hundreds of interactions, resulting in a high entropic contribution leading to high selectivities. However, if, and if so how, systems with few ligands, such as multi-domain proteins and bacteriophages binding to their host, show superselective behavior is an open question. Here, we address this question with a multivalent experimental model system based on star shaped branched DNA nanostructures (DNA nanostars) with each branch featuring a single stranded overhang that binds to complementary receptors on a target surface. Each DNA nanostar possesses a fluorophore, to directly visualize DNA nanostar surface adsorption by total internal reflection fluorescence microscopy (TIRFM). We observe that DNA nanostars can bind superselectively to surfaces and bind optimally at a valency of three, for a given binding strength and concentration. We explain this optimum by extending the current theory with interactions between DNA nanostar binding sites (ligands). Our results add to the understanding of multivalent interactions, by identifying cooperative mechanisms that lead to optimal selectivity, and providing quantitative values for the relevant parameters. These findings inspire additional design rules which improve future work on selective targeting in directed drug delivery.

By means of computer modelling, the self-assembly of amphiphilic A-graft-B macromolecules, grafted onto a spherical nanoparticle, is studied. In a solvent, that is poor for side pendants, the macromolecules self-assemble into thin membrane-like ABBA bilayers deviated from spherical nanoparticles. The bilayers form morphological structures that depend on the grafting density and macromolecular polymerization degree and can be referred to as the classical family of complete embedded minimal surfaces. The plane disk, catenoid, helicoid, Costa and Enneper surfaces as well as “double” helicoid and “complex minimal surface” were identified, and the fields of their stability were defined. The surfaces can be grouped according to the sequences of conformal transformations that transform them into each other. These surfaces arise in different experiments situationally. Results are summarized in a pie diagram constructed using a machine learning algorithm based on matching grafting points with a specially created planar graphic image.

Active solids, more specifically elastic lattices embedded with polar active units, exhibit collective actuation when the elasto-active feedback, generically present in such systems, exceeds some critical value. The dynamics then condensates on a small fraction of the vibrational modes, the selection of which obeys non trivial rules rooted in the nonlinear part of the dynamics. So far, the complexity of the selection mechanism has limited the design of specific actuation. Here, we investigate numerically how localizing activity to a fraction of modes enables the selection of non-trivial collective actuation. We perform numerical simulations of an agent-based model on triangular and disordered lattices and vary the concentration and the localization of the active agents on the lattice nodes. Both contribute to the distribution of the elastic energy across the modes. We then introduce an algorithm, which, for a given fraction of active nodes, evolves the localization of the activity in such a way that the energy distribution on a few targeted modes is maximized – or minimized. We illustrate on a specific targeted actuation, how the algorithm performs as compared to manually chosen localization of the activity. While, in the case of the ordered lattice, a well-educated guess performs better than the algorithm, and the latter outperform the manual trials in the case of the disordered lattice. Finally, the analysis of the results in the case of the ordered lattice leads us to introduce a design principle based on a measure of the susceptibility of the modes to be activated along certain activation paths.