Soft Matter最新文献

Non-equilibrium clustering and percolation are investigated in an archetypal model of two-dimensional active matter using dynamic simulations of self-propelled Brownian repulsive particles. We concentrate on the single-phase region up to moderate levels of activity, before motility-induced phase separation (MIPS) sets in. Weak activity promotes cluster formation and lowers the percolation threshold. However, driving the system further out of equilibrium partly reverses this effect, resulting in a minimum in the critical density for the formation of system-spanning clusters and introducing re-entrant percolation as a function of activity in the pre-MIPS regime. This non-monotonic behaviour arises from competition between activity-induced effective attraction (which eventually leads to MIPS) and activity-driven cluster breakup. Using an adapted iterative Boltzmann inversion method, we derive effective potentials to map weakly active cases onto a passive (equilibrium) model with conservative attraction, which can be characterised by Monte Carlo simulations. While the active and passive systems have practically identical radial distribution functions, we find decisive differences in higher-order structural correlations, to which the percolation threshold is highly sensitive. For sufficiently strong activity, no passive pairwise potential can reproduce the radial distribution function of the active system.

The fabrication of microgels, particularly those ranging from tens to hundreds of micrometers in size, represents a thriving area of research, particularly for biologists seeking controlled and isotropic media for cell encapsulation. In this article, we present a novel and robust method for producing structurally homogeneous alginate beads with a reduced environmental footprint, employing a co-flow focusing microfluidic device. These beads can be easily recovered in an oil-free aqueous medium, making the fabrication method highly suitable for diverse applications. We demonstrate precise control over the production of perfectly spherical beads across a wide range of diameters, from about 30 to 300 μm. We then measure Young's moduli of the beads, revealing a wide accessible range from 90 Pa to 11 kPa, contingent upon controlling the type (e.g. chain length) and concentration of alginate.

Modern materials design strategies take advantage of the increasing amount of materials property data available and increasingly complex algorithms to take advantage of those data. However, viscoelastic materials resist this trend towards increased data rates due to their inherent time-dependent properties. Therefore, viscoelasticity measurements present a roadblock for data collection in an important aspect of material design. For thermorheologically simple (TRS) materials, time–temperature superposition (TTS) made relaxation spectrum measurements faster relative to, for example, very long creep experiments. However, TTS itself currently faces a speed limit originating in the common logarithmic discrete frequency sweep (DFS) mode of operation. In DFS, the measurement time is proportional (by a factor much greater than one) to the lowest frequency of measurement. This state of affairs has not improved for TTS for half a century or more. We utilize recent work in experimental rheometry on windowed chirps to collect three decades of complex modulus data simultaneously, resulting in a ∼500% increase in data collection. In BOTTS, we superpose several isothermal chirp responses to produce a master curve in a fraction of time required by the traditional DFS-TTS technique. The chirp responses have good, albeit nontrivial, signal-to-noise properties. We use linear error propagation and a noise-weighted least squares approach to automatically incorporate all the data into a reliable shifting method. Using model thermoset polymers, we show that DFS-TTS and BOTTS results are comparable, and therefore BOTTS data represent a first step towards a faster method for master curve generation from unmodified rheological measurement instruments.

We studied the influence of trace quantities of divalent metal ions (M²⁺: Ca²⁺, Mg²⁺, and Zn²⁺) on proton concentration (−log[H⁺], designated as pH′) and polarity at the interface of anionic PG-phospholipid membranes comprising saturated and unsaturated acrylic chains. A spiro-rhodamine-6G-gallic acid (RGG) pH-probe was synthesized to monitor the interfacial pH′ of large unilamellar vesicles (LUVs) at a physiologically appropriate bulk pH (6.0–7.5). ¹H-NMR spectroscopy and fluorescence microscopy showed that RGG interacted with the LUV interface. The pH-dependent equilibrium between the spiro-closed and spiro-open forms of RGG at the interface from the bulk phase was compared using fluorescence spectra to obtain interfacial pH′. Interfacial dielectric constant (κ) was estimated using a porphyrin-based polarity-probe (GPP) that exhibits a κ-induced equilibrium between monomeric and oligomeric forms. M²⁺ interaction decreased LUV interfacial κ from ∼67 to 61, regardless of lipid/M²⁺ types. Fluorescence spectral and microscopic analysis revealed that low Ca²⁺ and Mg²⁺ amounts (M²⁺/lipid = 1 : 20 for unsaturated DOPG and POPG and ∼1 : 10 for saturated DMPG lipids), but not Zn²⁺, decreased LUV interfacial acidity from pH′ ∼3.8 to 4.4 at bulk pH 7.0. Although membrane surface charges are normally responsible for pH′ deviation from the bulk to the interface, they cannot explain M²⁺-mediated interfacial pH′ increase since there is little change in surface charges up to a low M²⁺/lipid ratio of <1/10. M²⁺-induced tight lipid headgroup packing and the resulting increased surface rigidity inhibit interfacial H⁺/H₂O penetration, reducing interfacial acidity and polarity. Our findings revealed that in certain cases, essential M²⁺ ion-induced bio-membrane reactivity can be attributed to the influence of interfacial pH′/polarity.

The syntheses of ionic porous organic polymers (iPOPs) via an ionothermal strategy or using solvents with high boiling points are not environmentally friendly approaches. Furthermore, green synthesis of an ionic porous organic polymer has not been reported to date. The azo-coupling reaction is considered a green synthetic strategy and has been used to obtain a new ionic porous organic polymer (iPOP-6) wherein water is used as a solvent. iPOP-6 turns out to be a useful adsorbent that can scavenge toxic water pollutants (MnO₄⁻ and I₃⁻) in an energy efficient manner via an ion exchange based adsorption process. The distribution coefficients (K_d) associated with the removal of MnO₄⁻ and I₃⁻ are greater than 10⁵ mL g⁻¹ – a desirable feature observed in a superior adsorbent. iPOP-6 can remove such pollutants from water samples collected from different water bodies with good capture efficiency. The removal mechanism was also ratified by theoretical studies. Overall, this work presents a new ionic POP with improved features and performance for water purification applications.

In nature, bacteria often swim in complex fluids, but our understanding of the interactions between bacteria and complex surroundings is still evolving. In this work, rod-like Bacillus subtilis swims in a quasi-2D environment with aqueous liquid–liquid interfaces, i.e., the isotropic–nematic coexistence phase of an aqueous chromonic liquid crystal. Focusing on the bacteria motion near and at the liquid–liquid interfaces, we collect and quantify bacterial trajectories ranging across the isotropic to the nematic phase. Despite its small magnitude, the interfacial tension of the order of 10 μN m⁻¹ at the isotropic–nematic interface justifies our observations that bacteria swimming more perpendicular to the interface have a higher probability of crossing the interface. Our force-balance model, considering the interfacial tension, further predicts how the length and speed of the bacteria affect their crossing behaviors. Investigating how a phase change affects bacterial motion, we also find, as soon as the bacteria cross the interface and enter the nematic phase, they wiggle less, but faster, and that this occurs as the flagellar bundles aggregate within the nematic phase. Given the ubiquity of multi-phases in biological environments, our findings will help to understand active transport across various phases.

Polymerization induced self-assembly (PISA) provides a facile platform for encapsulating therapeutics within block copolymer nanoparticles. Performing PISA in the presence of a hydrophobic drug alters both the nanoparticle shape and encapsulation efficiency. While previous studies primarily examined the interactions between the drug and hydrophobic core block, this work explores the impact of the hydrophilic corona block on encapsulation. Poly(ethylene glycol) (PEG) and poly(2-hydroxypropyl methacrylate) (PHPMA) are used as the model corona and core blocks, respectively, and phenylacetic acid (PA) is employed as the model drug. Attachment of a dithiobenzoate end group to the PEG homopolymer – transforming it into a macroscopic reversible addition–fragmentation chain transfer agent – causes the polymer to form a small number of nanoscopic aggregates in solution. Adding PA to the PEG solution encourages further aggregation and macroscopic phase separation. During the PISA of PEG-PHPMA block copolymers, inclusion of PA in the reaction mixture promotes faster nucleation of spherical micelles. Although increasing the targeted PA loading from 0 to 20 mg mL⁻¹ does not affect the micelle size or shape, it alters the drug spatial distribution within the PISA microenvironment. PA partitions into either PEG-PHPMA micelles, deuterium oxide, or other polymeric species – including PEG aggregates and unimer chains. Increasing the targeted PA loading changes the fraction of drug within each encapsulation site. This work indicates that the corona block plays a critical role in dictating drug encapsulation during PISA.

Complex plasmas consist of ionized gas and charged solid microparticles, representing the plasma state of soft matter. We apply machine learning methods to investigate a melting transition in a two-dimensional complex plasma. A convolutional neural network is constructed and trained with the numerical simulation. The hexatic phase is successfully identified and the evolution of topological defects is studied during melting transition in both simulations and experiments.

Particle dynamics simulations are used to study the startup flow of jammed soft particle suspensions in shear flow from a thermodynamic perspective. This thermodynamic framework is established using the concept of the two-body excess entropy extracted from the transient pair distribution function and elastic energy of the suspension as a function of strain at different shear rates and suspension volume fractions. Although the evolution of the elastic energy in these soft particle glasses closely mimics the stress–strain behavior at different shear rates and volume fractions, there are several differences corresponding to their overshoots in terms of the broadness and location of the peaks. The transient excess entropy shows an anisotropic behavior due to the anisotropic distribution of contacts at high shear rates. The excess entropy at high shear rates increases as a function of the strain and attains a steady state. On the other hand, it is nearly constant and isotropic in the quasi-static regime, where the stress response is close to the dynamic yield stress. Using the transient elastic energy and excess entropy, a transient temperature is defined to establish a relationship between thermodynamics and the static yield stress data. This transient temperature increases with the strain and then diverges at strains close to the static yield point at high shear rates.