Soft Matter最新文献

The behavior of topological defects near phase transition in liquid crystals has stimulated research in recent years, which has shown that a certain amount of “memory”' is retained when a defect characteristic of a liquid crystal phase turns into a defect belonging to a different phase. We aim to quantify this “memory effect” at the transition between smectic-A and nematic liquid crystal phases using focal conic domains in topographic confinement. These geometric defects, which spontaneously form in the smectic-A phase, disappear above the phase transition. However, we show that when the system is cooled back into the smectic phase, the defects tend to reform in their original location and that this behavior depends on the temperature at which they are heated, suggesting that the system retains temperature-dependent information about defect configurations across the phase transition despite the difference in the molecular alignment in the two phases.

Liquid–liquid phase separation (LLPS) is a cornerstone of cellular organization, driving the formation of biomolecular condensates that regulate diverse biological processes and inspire innovative applications. This review explores the molecular mechanisms underlying peptide-mediated LLPS, emphasizing the roles of intermolecular interactions such as hydrophobic effects, electrostatic interactions, and π–π stacking in phase separation. The influence of environmental factors, such as pH, temperature, ionic strength, and molecular crowding on the stability and dynamics of peptide coacervates is examined, highlighting their tunable properties. Additionally, the unique physicochemical properties of peptide coacervates, including their viscoelastic behavior, interfacial dynamics, and stimuli-responsiveness, are discussed in the context of their biological relevance and engineering potential. Peptide coacervates are emerging as versatile platforms in biotechnology and medicine, particularly in drug delivery, tissue engineering, and synthetic biology. By integrating fundamental insights with practical applications, this review underscores the potential of peptide-mediated LLPS as a transformative tool for advancing science and healthcare.

Urea is a well-known protein denaturant if added at high concentrations. The unfolding of proteins induced by urea is typically attributed to specific mechanisms; however, the influence of urea on protein–protein interactions, which can give rise to protein crystallization and liquid–liquid phase separation (LLPS), remains less understood. In this study, we examine the modulation of protein–protein interactions by urea at non-denaturing concentrations, in combination with sodium chloride. The effects of these additives on the state diagram and protein–protein interactions in lysozyme solutions are analyzed using optical microscopy and small-angle X-ray scattering (SAXS), respectively. Our findings indicate that the addition of urea diminishes net protein attractions, while the introduction of salt enhances them, resulting in respective shifts of the state boundaries. Moreover, the protein–protein interactions can be effectively characterized by a Derjaguin–Landau–Verwey–Overbeek (DLVO) potential. The impact of urea on these interactions can thus be explained entirely by alterations in the dielectric properties of the solution.

Star polymers are an interesting class of polymers to study based on their shape and dynamics. We use complementary techniques to study the polymer dynamics of star polymers with shorter side chains and compare them with linear counterparts. Using dielectric spectroscopy and rheology allows the extraction of the critical molecular weight using two different approaches. Furthermore, the reduction of the dielectric normal mode relaxation time shows a temperature as well as molecular weight dependent factor. Based on our dielectric spectroscopy results and taking as the limiting case based on theory, a temperature of T = 201.5 K is required which translates into a corresponding factor of for low molecular weight, i.e., M_w < M_c. Fast field cycling NMR together with rheology allowed us to conclude that both techniques track the dynamics of the entire star polymer rather than the dynamics of single arm like dielectric spectroscopy. This is especially seen as the dynamic moduli of linPBO8.5 and starPBO3.7 overlap and therefore have the same relaxation time.

Self-assembly of polymers with crystallizable blocks may lead to micelles with ordered, gel-like or crystalline cores. Here we investigate binary mixtures of n-alkyl-poly(ethylene oxide), C_n-PEOx (n = 28, x = 3–20 kDa) and study their self-assembly to gain insight into the effect of confinement on the core-crystallization and micellar structure. By employing identical core block length but varying corona block lengths, the size of the core can be tuned by variation of the block ratios. The micelles were characterized by small-angle X-ray scattering (SAXS) to gain insight into the overall and internal structure, including aggregation number, core size, and density distribution of the corona. SAXS curves from examined samples showed a characteristic pattern of spherical core–shell micelles but with broader corona distribution in the binary mixtures as compared to the neat samples. The structural parameters of the micelles were extracted from the SAXS data by employing a spherical core–shell model with dual density profiles in the core. We found that the aggregation number decreases as PEO length increases following a power law predicted in the literature. Furthermore, the melting point and melting enthalpy of crystalline alkyl cores were closely inspected by densitometry and differential scanning calorimetry (DSC). Correlating the core radius obtained from SAXS, we found that the melting point depression caused by the self-confinement in the micellar core can be described by the Gibbs–Thomson equation. These results show that the micellar structure and phase transition of the semicrystalline core can be easily tuned through blending diblock copolymers with different corona block lengths.

Drop impact on a wedged structure is a common phenomenon in daily life and industry. Although drop impact has been studied extensively since high-speed cameras have become available, little is known about drop impact on wedge tips of these structures. Here, we combine experiments and volume-of-fluid simulations to determine how velocity, the sharpness of the structure, and the surface wettability influence the outcome. The central impact of water drops onto wedge tips coated with superhydrophobic nanofilaments or with hydrophobic polystyrene (PS) was imaged. On superhydrophobic surfaces, drops fully rebound or split after impact. On hydrophobic PS surfaces, drops are deposited or split. A critical Weber number (We) was used to describe the transition between deposition/rebounding and splitting. It increases with the top width of the wedge tip and its top angle. The critical We and drop behavior is also affected by wetting properties which determine the drop adhesion and lateral drop friction. Our investigations may help to design new structures to prevent icing or produce tiny drops efficiently in applications.

Ion-conducting polymers (ICPs), benefiting from the movement of ions instead of electrons, have attracted significant interest in various scientific and technological fields, including drug delivery, water purification, and electrochemical devices. This review aims to highlight recent advances in the synthesis of ICP thin films, with a particular focus on chemical vapor deposition (CVD) technologies. Traditional solution-based methods for ICP thin film deposition face challenges, including non-uniformity, low-throughput manufacturing, and the generation of hazardous wastes. In comparison, CVD eliminates the drawbacks associated with solution-based processes. They offer precise control film properties, including high purity, conformal coating, delicate control over thickness, etc. This review organizes the latest developments in CVD-based ICP synthesis, based on material properties and the synthesis strategy, into direct deposition and post-polymerization modification, ionogels, hydrogels, and ultrathin siloxane or silazane-based polymer films. By providing an up-to-date review of the materials and synthesis, we aim to position CVD polymerization as an effective strategy for future materials development/production and device fabrication in energy, sustainability, and healthcare where ion conductivity is desired.

The rapid assembly of molecular or nanoscale building blocks into extended arrays is crucial to the construction of functional networks in vivo and in vitro and depends on various factors. One factor seldom considered is the dynamic changes of the building block shape. Folded protein building blocks offer a unique system to investigate dynamic shape changes due to their intrinsic ability to change from a compact and specific folded structure to an extended unfolded structure in response to a perturbation such as force. Here, we use photochemically crosslinked folded protein hydrogels constructed from force labile protein building blocks as a model dynamic shape-changing network system and characterise them by combining time-resolved rheology and small-angle X-ray scattering (SAXS). This approach probes both the load-bearing network structures, using rheology, and network architectures, using SAXS, thereby providing a crosslength scale understanding of the network formation. We propose a triple assembly model for the structural evolution of networks constructed from force labile protein building block consisting of: primary formation where monomeric folded proteins create the preliminary protein network scaffold; a subsequent secondary formation phase, where larger oligomers of protein diffuse to join the preliminary network scaffold; and finally in situ unfolding and relaxation which leads to the mature network structure of connected larger and denser fractal-like clusters. The time-resolved SAXS data provides evidence that protein unfolding occurs on the edges of the fractal-like clusters, resulting in a population of unfolded proteins in the space between clusters. Identifying the key stages of assembly in protein networks constructed from force labile proteins provides a greater understanding of the importance of protein unfolding in hierarchical biomechanics in vivo and creates future opportunities to develop bespoke biomaterials for novel biomedical applications.

Melting in two-dimensional (2D) systems is described by the celebrated Kosterlitz-Thouless-Halperin-Nelson-Young (KTHNY) theory, which explains how the unbinding of two types of topological defects destroys translational and orientational order at distinct temperatures. The intermediate hexatic phase, a fluid with six-fold quasi-long-ranged orientational order, has been observed in 2D colloidal monolayers of isotropic particles. In this study, we investigate the melting of a quadratic crystal with four-fold symmetry, composed of square particles of approximately 4 × 4 μm in size. These anisotropic particles were fabricated from photoresist using 3D nanoprinting. In an aqueous solution, the particles sediment onto a cover slide, forming a monolayer. The adjustable curvature of the cover slide precisely controls the monolayer density. At low densities, the particles exhibit free diffusion, forming a 2D fluid, while at high densities, they assemble into a quadratic crystal. Using a four-fold bond-order correlation function, we identify the tetratic phase with quasi-long ranged orientational order in close analogy to the hexatic phase in systems with six-fold symmetry.

An integrated experimental-computational methodology was developed to study the mechanical behavior of random polymer nanofiber networks with controlled network structural parameters. Random nanofiber networks, comprised of continuous polyethylene oxide (PEO) nanofibers with ∼250 nm diameter and controlled mean fiber segment length, were designed with a computer algorithm and printed via near-field electrospinning. The structure of the same networks served as input to a computational model to obtain predictions of the macroscopic mechanical response. This methodology provides consistency in fabricating, testing and simulating nominally identical random fiber networks. Specimens with 500 to 5000 nanofibers were subjected to uniaxial tension and compared to modeling predictions for the network mechanical behavior. The predictions by the computational model, with inputs from the experimental network structure, the measured single PEO nanofiber properties, and the fiber crimp parameter, agreed with the experimental results both quantitatively and with respect to the dependence of the measured quantities on the network parameters. The network stiffness and strength followed a power-law scaling with the network density, with exponents 2.78 ± 0.15 and 1.59 ± 0.04, respectively, while the network stretch at failure gradually decreased with increasing network fiber density. Finally, the experimentally determined network toughness demonstrated a rather weak power-law dependence on the network fiber density (exponent of 1.18 ± 0.12).