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We describe an improvement to the photoacoustic method for determining diffusion coefficients of dyes in soft matter, such as agar hydrogels. The proposed method is based on the properties of thermal wave formed due to a heat transfer at the interface of the two media: the gel and polyethylene film. It is inherently simple, requires a small number of reagents and relatively fast, since samples are small. To assess the obtained results, we independently determined diffusion coefficients of the dyes using an optical image analysis method and found both sets of results to be in a good agreement. [ABSTRACT FROM AUTHOR]

A novel design and approach for the realization of liquid crystal optical waveguides using photopatterning as a manufacturing method is presented. The developed method is used to demonstrate straight waveguides of different widths and curved waveguides with different radius of curvature. The waveguides are terminated with +1 or −1 surface defects through which the light incouples/outcouples. The effect of the straight waveguide thickness and the radius of curvature of the curved waveguides on the attenuation of the light in the waveguide is experimentally explored. The experiments are supported with numerical simulations of light propagation through both types of waveguides and outcoupling out of the straight waveguides. Furthermore, the effect of the size of the −1 defect terminations on the outcoupling efficiency is explored using simulations. Based on the presented design and manufacturing approach, liquid crystal optical waveguides of various shapes can be realized accurately with low‐cost. [ABSTRACT FROM AUTHOR]

The porous core of the marine mussel provides mechanical advantages of achieving substantial deformation and high toughness. Inspired by the unique mechanical behaviours of mussel plaque cores, the present study develops ultra-soft, stretchable and tough cellular solids by bio-mimicking their porosity and properties. Although scaling laws to correlate the mechanical properties of cellular solids with bulk materials have been established, they are primarily based on experimental data from stiff cellular solids. In this article, the scaling law for soft cellular solids is studied to relate tensile properties and toughness with volume fractions. Unlike conventional stiff cellular solids, the scaling law shows that soft lattices experience bending-dominated deformation at the elastic state and fail under stretching-dominated deformation. Uniaxial and planar tensile tests demonstrate that the proposed soft lattices achieved Young's modulus of 0.04∼0.17 MPa, failure strain of 135.5∼213.9% and toughness of 582∼941 J m−2 by manipulating the volume fraction (0.2∼0.5), positioning them as softer, more stretchable and tougher than the majority of engineering foams in the Ashby diagram. In addition, the toughness of soft lattices is found to be sensitive to volume fraction but insensitive to initial crack length, thickness and height (≥20mm). Two distinct failure modes, truss failure and joint failure, are correlated with volume fraction. The soft lattice with a volume fraction (around 0.4) similar to mussel plaque fails at the transition of these two failure modes and achieves the highest toughness. This study contributes new insights to the materials science community and lays the foundation for the development of lightweight, damage-tolerant and high-performance metamaterials. [ABSTRACT FROM AUTHOR]

Polar liquid crystals possess 3D orientational order coupled with unidirectional electric polarity, yielding fluid ferroelectrics. Such polar phases are generated by rod‐like molecules with large electric dipole moments. 2,5‐Disubstituted 1,3‐dioxane is commonly employed as a polar motif in said systems, and herein it is shown to suffer from thermal instability as a consequence of equatorial‐trans to axial‐trans isomerism at elevated temperatures. Isosteric building blocks are utilized as potential replacements for the 1,3‐dioxane unit, and in doing so new examples of fluid ferroelectric systems are obtained. For binary mixtures of certain composition, the emergence of a new fluid antiferroelectric phase, a finding not observed for either of the parent molecules, is observed. This study also reveals a critical tipping point for the emergence of polar order in otherwise apolar systems. These results hint at the possibility for uncovering new highly ordered polar liquid‐crystalline phases and delineate distinct transition mechanisms in orientational and polar ordering. [ABSTRACT FROM AUTHOR]

We report the use of wet‐spinning to 3D‐print gels from low‐molecular‐weight gelators (LMWGs) based on the 1,3 : 2,4‐dibenzylidenesorbitol (DBS) scaffold. Gel stripes assembled from DBS‐CONHNH2 and DBS‐COOH are printed, and their conductivities assessed. Printed gels based on DBS‐CONHNH2 can be loaded with Au(III), which is reduced in situ to form embedded gold nanoparticles (AuNPs). The conductivity of these gels increases because of electron transport mediated by the AuNPs, whereas the conductivity of DBS‐COOH, which does not promote AuNP formation, remains lower. We then fabricate multi‐component gel patterns comprised of spatially well‐defined domains of printed DBS‐CONHNH2/AuNP (higher conductivity) and DBS‐COOH (lower conductivity) resulting in soft multi‐domain materials with differential conductivity. Such materials have future prospects in applications such as soft nanoelectronics or tissue engineering. [ABSTRACT FROM AUTHOR]

AbstractVarious intriguing morphological patterns emerge on the surfaces of growing, developing, or aging tissues, organs, and colonies of microorganisms. Our research draws inspiration from biological growth processes and applies differential growth to film-substrate systems. The strain mismatch induced by this approach leads to distinctive buckling patterns. Through a combination of finite element analysis (FEA) and theoretical analysis, we derive a comprehensive expression for the strain energy in a buckled film-substrate system subjected to differential growth. By solving the energy equations, our study investigates the intricate interplay of material properties, growth functions, and geometric characteristics. This exploration provides valuable insights into the deformations induced by growth in membrane structures and soft materials. Additionally, we establish a phase diagram that characterizes the buckling patterns. It opens avenues for innovative geometric design and 3D self-assembly techniques. Furthermore, our findings have the potential to inspire applications in fields such as soft robotics and flexible electronics. [ABSTRACT FROM AUTHOR]

As a member of soft matter, hydrogel is a new type of functional polymer material with a three-dimensional network structure. Due to the properties of high water content, fast swelling, good biocompatibility, and sensitive responsiveness to external stimuli, hydrogels have been widely used in various different fields. Starting from the common jellies and water-elf toys in life, this project gradually goes deep into 3D-printing technology hydrogels, deformable hydrogel, and memorizing-forgetting hydrogel based on thermal stimulation. For different audiences, we have popularized the knowledge of hydrogels at different levels, experienced the preparation and properties of different types of the hydrogels, and explained the related chemical principles, so as to improve the public chemical literacy. [ABSTRACT FROM AUTHOR]

The analysis of the impact of the star polymer topology on depletion interaction potentials, depletion forces, and monomer density profiles is carried out analytically using field theory methods and techniques as well as molecular dynamic simulations. The dimensionless depletion interaction potentials and the dimensionless depletion forces for a dilute solution of ideal star polymers with three and five legs (arms) in a Θ -solvent confined in a slit between two parallel walls with repulsive surfaces and for the case where one of the surfaces is repulsive and the other inert are obtained. Furthermore, the dimensionless layer monomer density profiles for ideal star polymers with an odd number ( f ˜ = 3, 5) of arms immersed in a dilute solution of big colloidal particles with different adsorbing or repelling properties in respect of polymers are calculated, bearing in mind the Derjaguin approximation. Molecular dynamic simulations of a dilute solution of star-shaped polymers in a good solvent with N = 901 (3 × 300 + 1 -star polymer with three arms) and 1501 (5 × 300 + 1 -star polymer with five arms) beads accordingly confined in a slit with different boundary conditions are performed, and the results of the monomer density profiles for the above-mentioned cases are obtained. The numerical calculation of the radius of gyration for star polymers with f ˜ = 3, 5 arms and the ratio of the perpendicular to parallel components of the radius of gyration with respect to the wall orientation for the above-mentioned cases is performed. The obtained analytical and numerical results for star polymers with an odd number ( f ˜ = 3, 5) of arms are compared with our previous results for linear polymers in confined geometries. The acquired results show that a dilute solution of star polymer chains can be applied in the production of new functional materials, because the behavior of these solutions is strictly correlated with the topology of polymers and also with the nature and geometry of confined surfaces. The above-mentioned properties can find extensive practical application in materials engineering, as well as in biotechnology and medicine for drug and gene transmission. [ABSTRACT FROM AUTHOR]

Abstract Nanotechnology has opened new avenues for advanced research in various fields of soft materials. Materials scientists, chemists, physicists, and computational mathematicians have begun to take a keen interest in soft materials due to their potential applications in nanopatterning, membrane separation, drug delivery, nanolithography, advanced storage media, and nanorobotics. The unique properties of soft materials, particularly self-assembly, have made them useful in fields ranging from nanotechnology to biomedicine. The discovery of new morphologies in the diblock copolymer system in curved geometries is a challenging problem for mathematicians and theoretical scientists. Structural frustration under the effects of confinement in the system helps predict new structures. This mathematical study evaluates the effects of confinement and curvature on symmetric diblock copolymer melt using a cell dynamic simulation model. New patterns in lamella morphologies are predicted. The Laplacian involved in the cell dynamic simulation model is approximated by generating a 17-point stencil discretized to a polar grid by the finite difference method. Codes are programmed in FORTRAN to run the simulation, and IBM open DX is used to visualize the results. Comparison of computational results with existing studies validates this study and identifies defects and new patterns.

Cells self-organize into functional, ordered structures during tissue morphogenesis, a process that is evocative of colloidal self-assembly into engineered soft materials. Understanding how intercellular mechanical interactions may drive the formation of ordered and functional multicellular structures is important in developmental biology and tissue engineering. Here, by combining an agent-based model for contractile cells on elastic substrates with endothelial cell culture experiments, we show that substrate deformation-mediated mechanical interactions between cells can cluster and align them into branched networks. Motivated by the structure and function of vasculogenic networks, we predict how measures of network connectivity like percolation probability and fractal dimension as well as local morphological features including junctions, branches, and rings depend on cell contractility and density and on substrate elastic properties including stiffness and compressibility. We predict and confirm with experiments that cell network formation is substrate stiffness dependent, being optimal at intermediate stiffness. We also show the agreement between experimental data and predicted cell cluster types by mapping a combined phase diagram in cell density substrate stiffness. Overall, we show that long-range, mechanical interactions provide an optimal and general strategy for multicellular self-organization, leading to more robust and efficient realizations of space-spanning networks than through just local intercellular interactions.

[Display omitted] Soft materials, particularly elastomers, are extensively studied, but investigations into purely soft gel contact systems are limited due to their complex dual phases consisting of polymer and free liquids. While Dual Wavelength-Reflection Interference Confocal Microscopy (DW-RICM) is effective for noninvasively visualizing interfaces from a bottom view, it faces challenges in gel studies due to close refractive indices of polymeric networks and free liquids. We hypothesize that modulating the refractive index of soft gels using nanoparticles (NPs) enhances the visualization of contact zone beneath the free surface, providing insights into the configuration of phase-separated free oil within gel-on-gel contact systems. Gel-on-gel contact systems were fabricated using immiscible organogels and hydrogels. Titanium dioxide (TiO 2) NPs were introduced into the organogel to modulate refractive indices. Given the lack of prior studies on the hidden contact zone between gels, various techniques, including DW-RICM, side-view imaging, and inverted optical microscopy, were employed to observe and validate our findings. Comparative analyses were conducted with elastomer-on-rigid, elastomer-on-gel, and gel-on-rigid contact systems. Our investigation demonstrated that a minimal amount of TiO 2 NPs effectively delineates the direct contact radius between organogel polymeric networks and hydrogel surfaces. Comparative experiments showed that TiO 2 addition did not alter the gels' mechanical and surface properties but significantly enhanced information on gel contact deformation. This enhanced visualization technique has the potential to advance our understanding of adhesive contacts in gels, providing valuable insights into interface phenomena involving biological soft tissues and cells. [ABSTRACT FROM AUTHOR]

The natural polymer cellulose exhibits significant potential for various applications due to its unique optical, electronic, and chemical properties. However, the use of cellulose materials in luminescent applications has been relatively limited. This study aims to develop a simple and efficient method to enhance the fluorescence of cellulose materials by incorporating rare earth elements, thereby expanding their range of applications. In this work, we synthesized hybrid cellulose materials by grafting Eu‐bpy (H2bpydc=2,2‐bipyridine‐5,5‐dicarboxylic acid) onto the surface of cellulose fibers through a straightforward post‐processing procedure, resulting in materials with excellent fluorescence properties. By leveraging the abundant hydroxyl groups on the surface of cellulose fibers, Eu‐bpy@CF exhibits high luminescence in response to relative humidity and pH changes, with a noticeable color shift from light red to red visible to the naked eye. Consequently, these materials were further applied in the construction of smart fluorescent switches for the highly accurate and selective detection of phenylenediamine. Our research provides a simple approach to creating environmentally responsive handheld fluorescent papers and expands the diversity of rare‐earth cellulose fibers for developing new fluorescent materials with smart functions. [ABSTRACT FROM AUTHOR]

Adhesives can be made by patterning surfaces with discrete adhesive elements. Nature uses this approach to provide animals with highly adaptive and robust approaches towards gaining an effective grip on surfaces. The mechanism of patterned surface adhesion involve many different attachment principles, adhesive site interactions, and probabilistic effects, the interplay of which is not understood. This limits our ability to design patterned surface adhesives for engineering applications. In this work, we quantify how a mechanically patterned adhesive based on passive mushroom-shaped elements performs. We explore a range of surface design features and model the mechanical adhesion dynamics with an approach based on the fiber bundle model (FBM). We find that the fiber bundle model can be used to rationalize the observations after modifying it to capture the initial non-linear force response of the adhesives. Additionally, we investigate the behavior of the system's elastic energy and damage energy, as it is stretched under strain-controlled conditions. Our experimental data indicates that the elastic energy has a maximum that appears after the macroscopic strength (σc), corresponding to strains where a full rupture of the system can no longer be prevented. Moreover, we observed that below the maximum of the constitutive curve σc, the elastic energy consistently exceeds the damage energy. Finally, we found that the derivative of the elastic energy has a maximum, which always appears before σc. Therefore, the derivative of the elastic energy would serve as a reliable signal of upcoming catastrophic failure in experiments under stress-controlled conditions. [ABSTRACT FROM AUTHOR]

The formulation of more accurate models to describe tissue mechanics necessitates the availability of tools and instruments that can precisely measure the mechanical response of tissues to physical loads and other stimuli. In this regard, neuroscience has trailed other life sciences owing to the unavailability of representative live tissue models and deficiency of experimentation tools. We previously addressed both challenges by employing a novel instrument called the cantilevered-capillary force apparatus (CCFA) to elucidate the mechanical properties of mouse neurospheres under compressive forces. The neurospheres were derived from murine stem cells, and our study was the first of its kind to investigate the viscoelasticity of living neural tissues in vitro. In the current study, we demonstrate the utility of the CCFA as a broadly applicable tool to evaluate tissue mechanics by quantifying the effect that oxidative stress has on the mechanical properties of neurospheres. We treated mouse neurospheres with non-cytotoxic levels of hydrogen peroxide and subsequently evaluated the storage and loss moduli of the tissues under compression and tension. We observed that the neurospheres exhibit viscoelasticity consistent with neural tissue and show that elastic modulus decreases with increasing size of the neurosphere. Our study yields insights for establishing rheological measurements as biomarkers by laying the groundwork for measurement techniques and showing that the influence of a particular treatment may be misinterpreted if the size dependence is ignored. [ABSTRACT FROM AUTHOR]

The pull-off of a sphere from an elastic substrate follows the well-known JKR solution, and a similar but less known solution is valid for a cone. The two differ qualitatively in the parametric dependences of the pull-off load, so we study the case of a viscoelastic substrate using a well-known Gent and Schultz approach for the effective work of adhesion, with the assumption that the elastic modulus in the bulk of the specimen is the relaxed one. The rate of peeling of the contact line (for given remote withdrawing speed) depends on elastic modulus for the spherical case, and not for the cone. However, for the spherical geometry, we predict that the highest load amplification should be actually smaller than the highest work of adhesion amplification, while for the cone the opposite is true, although of a smaller factor. [ABSTRACT FROM AUTHOR]

Standard deep learning algorithms require differentiating large nonlinear networks, a process that is slow and power-hungry. Electronic contrastive local learning networks (CLLNs) offer potentially fast, efficient, and fault-tolerant hardware for analog machine learning, but existing implementations are linear, severely limiting their capabilities. These systems differ significantly from artificial neural networks as well as the brain, so the feasibility and utility of incorporating nonlinear elements have not been explored. Here, we introduce a nonlinear CLLN--an analog electronic network made of selfadjusting nonlinear resistive elements based on transistors. We demonstrate that the system learns tasks unachievable in linear systems, including XOR (exclusive or) and nonlinear regression, without a computer. We find our decentralized system reduces modes of training error in order (mean, slope, curvature), similar to spectral bias in artificial neural networks. The circuitry is robust to damage, retrainable in seconds, and performs learned tasks in microseconds while dissipating only picojoules of energy across each transistor. This suggests enormous potential for fast, low-power computing in edge systems like sensors, robotic controllers, and medical devices, as well as manufacturability at scale for performing and studying emergent learning. [ABSTRACT FROM AUTHOR]

The compressibility of soft colloids influences their phase behavior and flow properties, especially in concentrated suspensions. Particle compressibility, which is proportional to the reciprocal of the bulk modulus K, is a key parameter for soft polymer‐based particles that can be compressed in crowded environments. Here, microgels with different degrees of cross‐linking, i.e., softness, are investigated below and above their volume phase transition temperature (VPTT). By combining molecular dynamics simulations with small‐angle neutron scattering with contrast variation, a change in the particle bulk moduli of two orders of magnitude is observed. The degree of cross‐linking has a significant impact on the bulk modulus of the swollen microgel, while above the VPTT the values of K are almost independent of the cross‐linking density. The excellent agreement between experimental results and simulations also highlight that the model microgels from computer simulations possess both the internal architecture and the elastic properties of real polymeric networks. This paves the way to a systematic use of simulations to investigate the behavior of dense microgel suspensions below and above their VPTT. [ABSTRACT FROM AUTHOR]

We introduce a novel numerical method for the simulation of soft granular materials, in which the particles can undergo large strains under load without rupture. The proposed approach combines an explicit total Lagrangian formulation of Material Point Method (TLMPM) with the Contact Dynamics (CD) method. The TLMPM resolves particle bulk deformations whereas the CD treats contact interactions between soft particles. The efficiency and accuracy of this approach are illustrated by analyzing diametral compression of a soft circular particle and the compaction of an assembly of soft particles up to very high levels of packing fraction. We show that although the assembly undergoes a jamming transition, the particles continue to rearrange as they get increasingly distorted under load. Interestingly, as the packing fraction increases, a transition occurs to a regime fully governed by particle shape change. The evolution of the global stress as well as the connectivity of the particles as a function of the packing fraction are discussed and a predictive model relating stress to packing fraction beyond jamming transition is proposed. [ABSTRACT FROM AUTHOR]

In the first paper in this series, we presented asymptotic results for the effective wavenumber of the coherent longitudinal waves propagating through a system of pseudo-randomly distributed spherical elastic scatterers in a viscous medium. The analysis was based on multi-modal multiple scattering theory to account for both longitudinal and shear waves in the viscous embedding medium, arising from wave conversions at the scatterers surface, and identified asymptotic results in the long wavelength limit of the longitudinal waves. In this second paper, we present numerical validation of the various asymptotic approximations presented previously, including truncation of the number of partial wave orders and the use of the low concentration expansion of the dispersion relation. We explore the important contributions of wave conversion and of correlations in particle positions to the effective attenuation and to the frequency of the dipolar resonance of the scatterers. A comparison of the experimental results obtained with water containing sub-micrometric silica beads shows the very good validity of the model, particularly in the vicinity of the dipolar resonance. [ABSTRACT FROM AUTHOR]

The propagation of coherent longitudinal waves in a viscous liquid containing a random distribution of spherical elastic particles is analysed using a model based on multiple scattering theory. This model, initially developed to describe the propagation of coupled longitudinal and transverse elastic waves in isotropic solid materials, takes into account wave conversions at the particle surface as well as positional correlations between particles via the pair correlation function. By modelling a Newtonian viscous liquid through complex frequency-dependent elastic moduli (i.e. using an imaginary shear modulus), the model is adapted to the case of viscous fluids and we show that conversions of longitudinal waves into transverse waves are important to take into account. We present asymptotic results from the model for case of long wavelength for the longitudinal waves, without assumptions on the shear wavelength. For high concentrations, these wave conversions are reinforced by the contribution of position correlations between the particles. In a subsequent paper, we present numerical validation of the asymptotic approximations and compare them with experimental results for solid particles in water. [ABSTRACT FROM AUTHOR]

Soft matter with diverse functionalities that are easily designable has fascinated tremendous research interests in the past several decades. Nevertheless, the inherent confluence of time and length scale ubiquitous in soft matter immensely complicates the elucidation of the structure–property relationship and thereby severely impedes the function exploration of soft materials. Recently, the emergent machine learning (ML) techniques open new paradigms in property prediction and molecular design of functional materials, due to their extraordinarily distinguished performance in the aspect of trend identity and pattern extraction from data, and objective optimization by accelerating the guided search in high‐dimensional spaces. This review exclusively focuses on the current state‐of‐the‐art progress in the development of ML techniques applied in the realms of soft matter, ranging from coarse‐grained simulations to theoretical prediction on the structural formation and macroscopic properties, as well as the optimization and algorithm‐aided design in experiments. Finally, an outlook on the challenges and opportunities for this rapidly evolving field is discussed. [ABSTRACT FROM AUTHOR]

A self-healing gel with self-healing kinetics that can be regulated by heat is developed. The gel is composed of a polymer having benzophenone (BP) substituents, which are cross-linked with a main alkyl chain via ester bonds, titanium chloride, and zinc. This gel material shows a self-healing property at room temperature. Also, its self-healing behavior can be accelerated by heating the gel. This gel having self-healing kinetics that can be regulated by heat is favorable for practical use. When we want to use a self-healing property as a stop-gap measure, a rapid self-healing property is demanded. On the other hand, when we want materials repaired beautifully or decomposed surfaces need to be attached beautifully, a slow self-healing property is favorable. These opposite demands can be answered by the gel with self-healing kinetics that can be regulated by heat. [ABSTRACT FROM AUTHOR]

Polar liquid crystals possess 3D orientational order coupled with unidirectional electric polarity, yielding fluid ferroelectrics. Such polar phases are generated by rod‐like molecules with large electric dipole moments. 2,5‐Disubstituted 1,3‐dioxane is commonly employed as a polar motif in said systems, and herein it is shown to suffer from thermal instability as a consequence of equatorial‐trans to axial‐trans isomerism at elevated temperatures. Isosteric building blocks are utilized as potential replacements for the 1,3‐dioxane unit, and in doing so new examples of fluid ferroelectric systems are obtained. For binary mixtures of certain composition, the emergence of a new fluid antiferroelectric phase, a finding not observed for either of the parent molecules, is observed. This study also reveals a critical tipping point for the emergence of polar order in otherwise apolar systems. These results hint at the possibility for uncovering new highly ordered polar liquid‐crystalline phases and delineate distinct transition mechanisms in orientational and polar ordering.

In recent years, thermosensitive polysaccharide-based injectable hydrogels have gained increasing attention in biomedical applications, including wound healing, drug delivery, and cartilage repair. These hydrogels have favorable biocompatibility, biodegradability, and tunable physical and chemical properties. Thermosensitive polysaccharide-based injectable hydrogels are a class of intelligent soft matter material. They can undergo a reversible liquid-solid transition when exposed to temperature stimuli. Therefore, their precursor solutions can be accurately inserted into target sites with irregular geometries in a minimally invasive way and then transformed into gels in situ by the organism's temperature stimulation to deliver biologically active molecules. This review summarizes the recent developments of thermosensitive injectable polysaccharide-based hydrogels. The focus is on the mechanism of sol-gel phase transition, as well as the design and preparation of thermosensitive polysaccharides and their applications in biomedical fields. In addition, the outlook of the challenges in biomedical applications is provided at the end of the paper.

ABSTRACTHydrogels are flexible materials that typically accommodate elongation with positive Poisson’s ratios. Auxetic property, i.e., the negative Poisson’s ratio, of elastic materials can be macroscopically implemented by the structural design of the continuum. We realize it without mold for hydrogel made of cellulose nanofibers (CNFs). The complex structural design of auxetic Kirigami is first implemented on the dry CNF film, i.e., so-called nanopaper, by laser processing, and the CNF hydrogel is formed by dipping the film in liquid water. The CNF films show anisotropic swelling where drastic volumetric change mainly originates from increase in the thickness. This anisotropy makes the design and fabrication of the emergent Kirigami hydrogel straightforward. We characterize the flexibility of this mechanical metamaterial made of hydrogel by cyclic tensile loading starting from the initial end-to-end distance of dry sample. The tensile load at the maximum strain decreases with the increasing number of cycles. Furthermore, the necessary work up to the maximum strain even decreases to the negative value, while the work of restoration to the original end-to-end distance increases from the negative value to the positive. The equilibrium strain where the force changes the sign increases to reach a plateau. This plastic deformation due to the cyclic loading can be regarded as the adaptive response without fracture to the applied dynamic loading input.

Polymer gels, consisting of cross‐linked polymer network systems swollen by a solvent, show great potential in biomedicine, flexible electronics, and artificial muscles, due to their tissue‐like mechanical properties. Due to the presence of a large amount of solvent, the improvement of the mechanical properties of the polymer gel is a challenge. Moreover, combining high toughness with useful properties, such as 3D printability or shape‐memory, in one polymer gel system is even more challenging. In this study, a simple and efficient method is developed for the fabrication of tough polymer gels by polymerizing 2‐hydroxyethyl methacrylate (HEMA) in a mixture of poly(ethylene glycol) (PEG) and poly(propylene glycol) (PPG). The polymerized elastic networkpresents distinct compatibility with PEG (compatible) and PPG (poorly compatible), resulting in in‐situ phase separation at the microscale. The resulting phase‐separated gel demonstrates high strength (8.0 MPa), favorable fracture strain (430%), and large toughness (17.0 MJ m−3). The separated hard phasewith a high glass transition temperature (75 °C) endows the whole soft polymer gel with the property of shape memory at room temperature. Finally, the fabrication of tunable tough PEGgels is combined with 3D printing as well as with shape memory properties, demonstrating the use of PEGgels for 4D printing. [ABSTRACT FROM AUTHOR]

Seeing the atomic configuration of single organic nanoparticles at a sub-Å spatial resolution by transmission electron microscopy has been so far prevented by the high sensitivity of soft matter to radiation damage. This difficulty is related to the need to irradiate the particle with a total dose of a few electrons/Å2, not compatible with the electron beam density necessary to search the low-contrast nanoparticle, to control its drift, finely adjust the electron-optical conditions and particle orientation, and finally acquire an effective atomic-resolution image. On the other hand, the capability to study individual pristine nanoparticles, such as proteins, active pharmaceutical ingredients, and polymers, with peculiar sensitivity to the variation in the local structure, defects, and strain, would provide advancements in many fields, including materials science, medicine, biology, and pharmacology. Here, we report the direct sub-ångström-resolution imaging at room temperature of pristine unstained crystalline polymer-based nanoparticles. This result is obtained by combining low-dose in-line electron holography and phase-contrast imaging on state-of-the-art equipment, providing an effective tool for the quantitative sub-ångström imaging of soft matter. [ABSTRACT FROM AUTHOR]

Additive manufacturing technology has fostered its significant application in soft robotics fabrication due to the design freedom and ease of realizing complex geometries. The selection of an appropriate additive manufacturing process (out-of-material extrusion, vat photopolymerization, and powder bed fusion) is vital for the fabrication of soft robotics as the process greatly influences the quality of the part further affecting the functionality and service life. These pneumatically actuated robots in their service life are subjected to fatigue loading and handling of very delicate tasks; thus, the porosity (including pores characterization) and surface roughness are two critical quality parameters which should be considered while choosing the fabrication process. In this study, a three-way decision-making (a multi-criteria decision-making tool) approach is implemented for selecting an appropriate additive manufacturing process for the fabrication of high-quality parts for soft robotics applications. The results (ranking of AM processes) obtained using the proposed approach are compared with the conventional decision-making techniques, namely TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), MOORA (Multi-Objective Optimization by Ratio Analysis), and VIKOR (VIseKriterijumska Optimizacija). The sensitivity analysis carried out in this work also suggests that three-way decision-making is as effective as other MCDM tools and the vat photopolymerization process is the most suitable out of all for fabricating TPU actuators. [ABSTRACT FROM AUTHOR]

The transmission of chiral information between the molecular, meso and microscopic scales is a facet of biology that remains challenging to understand mechanistically and to mimic with artificial systems. Here we demonstrate that the dynamic change in the expression of the chirality of a rotaxane can be transduced into a change in pitch of a soft matter system. Shuttling the position of the macrocycle from far‐away‐from to close‐to a point‐chiral center on the rotaxane axle changes the expression of the chiral information that is transmitted across length scales; from nanometer scale constitutional chirality that affects the conformation of the macrocycle, to the centimeter scale chirality of the liquid crystal phase, significantly changing the pitch length of the chiral nematic structure. [ABSTRACT FROM AUTHOR]

Smart polymer materials that are nonliving yet exhibit complex "life-like" or biomimetic behaviors have been the focus of intensive research over the past decades, in the quest to broaden our understanding of how living systems function under nonequilibrium conditions. Identification of how chemical and mechanical coupling can generate resonance and entrainment with other cells or external environment is an important research question. We prepared Belousov-Zhabotinsky (BZ) selfoscillating hydrogels which convert chemical energy to mechanical oscillation. By cyclically applying external mechanical stimulation to the BZ hydrogels, we found that when the oscillation of a gel sample entered into harmonic resonance with the applied oscillation during stimulation, the system kept a "memory" of the resonant oscillation period and maintained it post stimulation, demonstrating an entrainment effect. More surprisingly, by systematically varying the cycle length of the external stimulation, we revealed the discrete nature of the stimulation-induced resonance and entrainment behaviors in chemical oscillations of BZ hydrogels, i.e., the hydrogels slow down their oscillation periods to the harmonics of the cycle length of the external mechanical stimulation. Our theoretical model calculations suggest the important roles of the delayed mechanical response caused by reactant diffusion and solvent migration in affecting the chemomechanical coupling in active hydrogels and consequently synchronizing their chemical oscillations with external mechanical oscillations. [ABSTRACT FROM AUTHOR]

Granular materials are ubiquitous in nature and industry; their mechanical behavior has been a subject of academic and engineering interest for centuries. One of the reasons for their rather complex mechanical behavior is that stresses exerted on a granular material propagate only through contacts between the grains. These contacts can change as the packing evolves. This makes any deformation and mechanical response from a granular packing a function of the nature of contacts between the grains and the material response of the material the grains are made of. We present a study in which we isolate the role of the grain material in the contact forces acting between two particles sliding past each other. By using hydrogel particles, we find that a viscoelastic material model, in which the shear modulus decays with time, coupled with a simple Coulomb friction model, captures the experimental results. The results suggest that particle material evolution itself may play a role in the collective behavior of granular materials. [ABSTRACT FROM AUTHOR]

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X‐ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network. In this manner, the neural network can be trained simultaneously on all well‐posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics‐inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five‐layer multilayer model and a periodic multilayer model with up to 17 open parameters. [ABSTRACT FROM AUTHOR]

The maximum range of perpendicular momentum transfer (qz) has been tripled for X‐ray scattering from liquid surfaces when using a double‐crystal deflector setup to tilt the incident X‐ray beam. This is achieved by employing a higher‐energy X‐ray beam to access Miller indices of reflecting crystal atomic planes that are three times higher than usual. The deviation from the exact Bragg angle condition induced by misalignment between the X‐ray beam axis and the main rotation axis of the double‐crystal deflector is calculated, and a fast and straightforward procedure to align them is deduced. An experimental method of measuring scattering intensity along the qz direction on liquid surfaces up to qz = 7 Å−1 is presented, with liquid copper serving as a reference system for benchmarking purposes. [ABSTRACT FROM AUTHOR]

[Display omitted] Chirality dynamic tuning plays fundamental roles in chemistry, material science and biological system. Herein, a pair of azobenzene-bridged bis-tryptophan enantiomers (Azo-di- d / l -Trp) were designed and synthesized via simple reactions. With the fuel of glucono-δ-lactone (GdL), releasing protons during its hydrolysis, the alkaline solution of Azo-di- d / l -Trp gradually self-assembled into contrast chiral helical structures and displayed magnitude and mirror image of circular dichroism (CD) signals. While the chiral helices converted to CD silent nanoparticles when the azobenzene moiety isomerized from trans - to cis -form under UV irradiation. More importantly, this chiroptical switch, displaying reversible interconversion between chiral amplification and silent, can be smartly controlled via photoirradiation at various wavelengths. [ABSTRACT FROM AUTHOR]

The development of optical and photonic applications using soft-matter droplets holds great scientific and application importance. The machining of droplet structures is expected to drive breakthroughs in advancing frontier applications. This review highlights recent advancements in micro–nanofabrication techniques for soft-matter droplets, encompassing microfluidics, laser injection, and microfluidic 3D printing. The principles, advantages, and weaknesses of these technologies are thoroughly discussed. The review introduces the utilization of a phase separation strategy in microfluidics to assemble complex emulsion droplets and control droplet geometries by adjusting interfacial tension. Additionally, laser injection can take full advantage of the self-assembly properties of soft matter to control the spontaneous organization of internal substructures within droplets, thus providing the possibility of high-precision customized assembly of droplets. Microfluidic 3D printing demonstrates a 3D printing-based method for machining droplet structures. Its programmable nature holds promise for developing device-level applications utilizing droplet arrays. Finally, the review presents novel applications of soft-matter droplets in optics and photonics. The integration of processing concepts from microfluidics, laser micro–nano-machining, and 3D printing into droplet processing, combined with the self-assembly properties of soft materials, may offer novel opportunities for processing and application development. [ABSTRACT FROM AUTHOR]

Adhesives can be made by patterning surfaces with discrete adhesive elements. Nature uses this approach to provide animals with highly adaptive and robust approaches towards gaining an effective grip on surfaces. The mechanism of patterned surface adhesion involve many different attachment principles, adhesive site interactions, and probabilistic effects, the interplay of which is not understood. This limits our ability to design patterned surface adhesives for engineering applications. In this work, we quantify how a mechanically patterned adhesive based on passive mushroom-shaped elements performs. We explore a range of surface design features and model the mechanical adhesion dynamics with an approach based on the fiber bundle model (FBM). We find that the fiber bundle model can be used to rationalize the observations after modifying it to capture the initial non-linear force response of the adhesives. Additionally, we investigate the behavior of the system’s elastic energy and damage energy, as it is stretched under strain-controlled conditions. Our experimental data indicates that the elastic energy has a maximum that appears after the macroscopic strength (σc), corresponding to strains where a full rupture of the system can no longer be prevented. Moreover, we observed that below the maximum of the constitutive curve σc, the elastic energy consistently exceeds the damage energy. Finally, we found that the derivative of the elastic energy has a maximum, which always appears before σc. Therefore, the derivative of the elastic energy would serve as a reliable signal of upcoming catastrophic failure in experiments under stress-controlled conditions.

Debris flows are dense and fast-moving complex suspensions of soil and water that threaten lives and infrastructure. Assessing the hazard potential of debris flows requires predicting yield and flow behavior. Reported measurements of rheology for debris flow slurries are highly variable and sometimes contradictory due to heterogeneity in particle composition and volume fraction ([Formula: see text]) and also inconsistent measurement methods. Here we examine the composition and flow behavior of source materials that formed the postwildfire debris flows in Montecito, CA, in 2018, for a wide range of [Formula: see text] that encapsulates debris flow formation by overland flow. We find that shear viscosity and yield stress are controlled by the distance from jamming, [Formula: see text], where the jamming fraction [Formula: see text] is a material parameter that depends on grain size polydispersity and friction. By rescaling shear and viscous stresses to account for these effects, the data collapse onto a simple nondimensional flow curve indicative of a Bingham plastic (viscoplastic) fluid. Given the highly nonlinear dependence of rheology on [Formula: see text], our findings suggest that determining the jamming fraction for natural materials will significantly improve flow models for geophysical suspensions such as hyperconcentrated flows and debris flows.

The analysis of the impact of the star polymer topology on depletion interaction potentials, depletion forces, and monomer density profiles is carried out analytically using field theory methods and techniques as well as molecular dynamic simulations. The dimensionless depletion interaction potentials and the dimensionless depletion forces for a dilute solution of ideal star polymers with three and five legs (arms) in a Θ-solvent confined in a slit between two parallel walls with repulsive surfaces and for the case where one of the surfaces is repulsive and the other inert are obtained. Furthermore, the dimensionless layer monomer density profiles for ideal star polymers with an odd number (f˜ = 3, 5) of arms immersed in a dilute solution of big colloidal particles with different adsorbing or repelling properties in respect of polymers are calculated, bearing in mind the Derjaguin approximation. Molecular dynamic simulations of a dilute solution of star-shaped polymers in a good solvent with N = 901 (3 × 300 + 1 -star polymer with three arms) and 1501 (5 × 300 + 1 -star polymer with five arms) beads accordingly confined in a slit with different boundary conditions are performed, and the results of the monomer density profiles for the above-mentioned cases are obtained. The numerical calculation of the radius of gyration for star polymers with f˜ = 3, 5 arms and the ratio of the perpendicular to parallel components of the radius of gyration with respect to the wall orientation for the above-mentioned cases is performed. The obtained analytical and numerical results for star polymers with an odd number (f˜ = 3, 5) of arms are compared with our previous results for linear polymers in confined geometries. The acquired results show that a dilute solution of star polymer chains can be applied in the production of new functional materials, because the behavior of these solutions is strictly correlated with the topology of polymers and also with the nature and geometry of confined surfaces. The above-mentioned properties can find extensive practical application in materials engineering, as well as in biotechnology and medicine for drug and gene transmission.

[Display omitted] Understanding protein behaviour is crucial for developing functional solvent systems. Ionic liquids (ILs) are designer salts with versatile ion combinations, where some suppress unfavourable protein behaviour. This work utilizes small angle X-ray scattering (SAXS) to investigate the size and shape changes of model protein hen egg white lysozyme (HEWL) in 137 IL and salt solutions. Guinier, Kratky, and pair distance distribution analysis were used to evaluate the protein size, shape, and aggregation changes in these solvents. At low IL and salt concentration (1 mol%), HEWL remained monodispersed and globular. Most ILs increased HEWL size compared to buffer, while the nitrate and mesylate anions induced the most significant size increases. IL cation branching, hydroxyl groups, and longer alkyl chains counteracted this size increase. Common salts exhibited specific ion effects, while the IL effect varied with concentration due to complex ion-pairing. Protein aggregation and unfolding occurred at 10 mol% IL, altering the protein shape, especially for ILs with multiple alkyl chains on the cation, or with a mesylate/nitrate anion. This study highlights the usefulness of adopting a high-throughput SAXS strategy for understanding IL effects on protein behaviour and provides insights on controlling protein aggregation and unfolding with ILs. [ABSTRACT FROM AUTHOR]

Optical manipulation has emerged as a pivotal tool in soft matter research, offering superior applicability, spatiotemporal precision, and manipulation capabilities compared to conventional methods. Here, an overview of the optical mechanisms governing the interaction between light and soft matter materials during manipulation is provided. The distinct characteristics exhibited by various soft matter materials, including liquid crystals, polymers, colloids, amphiphiles, thin liquid films, and biological soft materials are highlighted, and elucidate their fundamental response characteristics to optical manipulation techniques. This knowledge serves as a foundation for designing effective strategies for soft matter manipulation. Moreover, the diverse range of applications and future prospects that arise from the synergistic collaboration between optical manipulation and soft matter materials in emerging fields are explored. [ABSTRACT FROM AUTHOR]

Self-assembly of isotropically interacting particles into desired crystal structures could allow for creating designed functional materials via simple synthetic means. However, the ability to use isotropic particles to assemble different crystal types remains challenging, especially for generating low-coordinated crystal structures. Here, we demonstrate that isotropic pairwise interparticle interactions can be rationally tuned through the design of DNA shells in a range that allows transition from common, high-coordinated FCC-CuAu and BCC-CsCl lattices, to more exotic symmetries for spherical particles such as the SC-NaCl lattice and to low-coordinated crystal structures (i.e., cubic diamond, open honeycomb). The combination of computational and experimental approaches reveals such a design strategy using DNA-functionalized nanoparticles and successfully demonstrates the realization of BCC-CsCl, SC-NaCl, and a weakly ordered cubic diamond phase. The study reveals the phase behavior of isotropic nanoparticles for DNA-shell tunable interaction, which, due to the ease of synthesis is promising for the practical realization of non-close-packed lattices. [ABSTRACT FROM AUTHOR]

We present a hybrid scheme based on classical density functional theory and machine learning for determining the equilibrium structure and thermodynamics of inhomogeneous fluids. The exact functional map from the density profile to the onebody direct correlation function is represented locally by a deep neural network. We substantiate the general framework for the hard sphere fluid and use grand canonical Monte Carlo simulation data of systems in randomized external environments during training and as reference. Functional calculus is implemented on the basis of the neural network to access higher-order correlation functions via automatic differentiation and the free energy via functional line integration. Thermal Noether sum rules are validated explicitly. We demonstrate the use of the neural functional in the selfconsistent calculation of density profiles. The results outperform those from state-of-the-art fundamental measure density functional theory. The low cost of solving an associated Euler-Lagrange equation allows to bridge the gap from the system size of the original training data to macroscopic predictions upon maintaining near-simulation microscopic precision. These results establish the machine learning of functionals as an effective tool in the multiscale description of soft matter. [ABSTRACT FROM AUTHOR]

In an in‐depth study of the mechanism of cation release from carboxymethyl cellulose hydrogels synthesized through Schiff base reaction, we analyze the differences in the release kinetics of potassium, calcium, and iron cations with Peleg model at pH values of pH 3.5 and pH 8.5 using ICP‐OES (inductively coupled plasma optical emission spectroscopy) technique. [ABSTRACT FROM AUTHOR]

The electrosteric interaction energy for a charged hydrogel and hard plane, and between two charged hydrogels is derived in the Debye-Hückel approximation. This is combined with a van der Waals potential that explicitly addresses the Hamaker constant for the solvent-mediated hydrogel interactions. Then, in the Derjaguin approximation, DLVO-type interaction potentials are provided for hydrogel and hard/rigid spheres, accounting for elastic deformation that accompanies adhesion. As examples, this furnishes the energy for cohesion of soft polyelectrolyte microspheres, and provides a quantitative interpretation for the adhesion of rigid latex spheres to a soft deformable hydrogel, as reported by Sato et al. (Sato et al. 2017 Sci. Rep. 7, 1-10 (doi:10.1038/s41598-017-06257-1)). The theory demonstrates that weak van der Waals attraction of hydrogels is readily balanced by electrosteric interactions, e.g. making colloidal hydrogel dispersions less stable than their rigid-particulate counterparts. [ABSTRACT FROM AUTHOR]

Nanopapers fabricated from cellulose nanofibers (CNFs) drastically swell to form hydrogels when they are in contact with water. This gelation makes contrast with conventional papers that simply deform without drastic volume increase. While the volume increase is qualitatively obvious from the macroscopic visual inspection, its quantitative understanding is nontrivial because of the difficulty in the detection of the boundary between the nanopaper hydrogel and the residual or extra water. In this study, we use single particle tracking (SPT) to reveal the swelling-based gelation phenomenon of cellulose nanopapers. The diffusive dynamics of probe particles uncovers the transient process of swelling, and equilibrium analysis reveals the dependence of volume increase fundamentally dependent on the amount of water to be in contact with the nanopapers. Comparison with the aqueous CNF dispersion without drying reveals the difference in the texture of the nanopaper hydrogels from them. [ABSTRACT FROM AUTHOR]