Soft Memristor at a Microbubble Interface.

Memristors show promising features for neuromorphic computing. Here we report a soft memristor based on the liquid-vapor surface of a microbubble. The thickness of the liquid film was modulated by electrostatic and interfacial forces, enabling resistance switches. We found a pinched current hysteresis at scanning periods between 1.6 and 51.2 s, while representing a resistor below 1.6 s and a diode-like behavior above 51.2 s. We approximate the thickening/thinning dynamics of liquid film by pressure-driven flow at the interface and derived the impacts of salt concentration and voltage amplitude on the memory effects. Our work opens a new approach to building nanofluidic memristors by a soft interface, which may be useful for new types of neuromorphic computing in the future.

Intrinsic dynamics of emulsions: Experiments in microgravity on the International Space Station.

HYPOTHESIS: In order to understand the basic mechanisms affecting emulsion stability, the intrinsic dynamics of the drop population must be investigated. We hypothesize that transient ballistic motion can serve as a marker of interactions between drops. In 1G conditions, buoyancy-induced drop motion obscures these interactions. The microgravity condition onboard the International Space Station enable this investigation. EXPERIMENTS: We performed Diffusing Wave Spectroscopy (DWS) experiments in the ESA Soft Matter Dynamics (SMD) facility. We used Monte Carlo simulations of photon trajectory to support data analysis. The analysis framework was validated by ground-based characterizations of the initial drop size distribution (DSD) and the properties of the oil/water interface in the presence of surfactant. FINDINGS: We characterized the drop size distribution and found to be bi-disperse. Drop dynamics shows transient ballistic features at early times, reaching a stationary regime of primarily diffusion-dominated motion. This suggests different ageing mechanisms: immediately after emulsification, the main mechanism is coalescence or aggregation between small drops. However at later times, ageing proceeds via coalescence or aggregation of small with large drops in some emulsions. Our results elucidate new processes relevant to emulsion stability with potential impact on industrial processes on Earth, as well as enabling technologies for space exploration.

Transparency-changing elastomers by controlling of the refractive index of liquid inclusions.

Complex materials that change their optical properties in response to changes in environmental conditions can find applications in displays, smart windows, and optical sensors. Here a class of biphasic composites with stimuli-adaptive optical transmittance is introduced. The biphasic composites comprise aqueous droplets (a mixture of water, glycerol, and surfactant) embedded in an elastomeric matrix. The biphasic composites are tuned to be optically transparent through a careful match of the refractive indices between the aqueous droplets and the elastomeric matrix. We demonstrate that stimuli (e.g., salinity and temperature change) can trigger variations in the optical transmittance of the biphasic composite. The introduction of such transparency-changing soft matter with liquid inclusions offers a novel approach to designing advanced optical devices, optical sensors, and metamaterials.

Bio-soft matter derived from traditional Chinese medicine: Characterizations of hierarchical structure, assembly mechanism, and beyond.

Structural and functional explorations on bio-soft matter such as micelles, vesicles, nanoparticles, aggregates or polymers derived from traditional Chinese medicine (TCM) has emerged as a new topic in the field of TCM. The discovery of such cross-scaled bio-soft matter may provide a unique perspective for unraveling the new effective material basis of TCM as well as developing innovative medicine and biomaterials. Despite the rapid rise of TCM-derived bio-soft matter, their hierarchical structure and assembly mechanism must be unambiguously probed for a further in-depth understanding of their pharmacological activity. In this review, the current emerged TCM-derived bio-soft matter assembled from either small molecules or macromolecules is introduced, and particularly the unambiguous elucidation of their hierarchical structure and assembly mechanism with combined electron microscopic and spectroscopic techniques is depicted. The pros and cons of each technique are also discussed. The future challenges and perspective of TCM-derived bio-soft matter are outlined, particularly the requirement for their precise in situ structural determination is highlighted.

Machine learning without a processor: Emergent learning in a nonlinear analog network.

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 self-adjusting 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.

Discontinuous Shear Thickening in Biological Tissue Rheology.

During embryonic morphogenesis, tissues undergo dramatic deformations in order to form functional organs. Similarly, in adult animals, living cells and tissues are continually subjected to forces and deformations. Therefore, the success of embryonic development and the proper maintenance of physiological functions rely on the ability of cells to withstand mechanical stresses as well as their ability to flow in a collective manner. During these events, mechanical perturbations can originate from active processes at the single-cell level, competing with external stresses exerted by surrounding tissues and organs. However, the study of tissue mechanics has been somewhat limited to either the response to external forces or to intrinsic ones. In this work, we use an active vertex model of a 2D confluent tissue to study the interplay of external deformations that are applied globally to a tissue with internal active stresses that arise locally at the cellular level due to cell motility. We elucidate, in particular, the way in which this interplay between globally external and locally internal active driving determines the emergent mechanical properties of the tissue as a whole. For a tissue in the vicinity of a solid-fluid jamming or unjamming transition, we uncover a host of fascinating rheological phenomena, including yielding, shear thinning, continuous shear thickening, and discontinuous shear thickening. These model predictions provide a framework for understanding the recently observed nonlinear rheological behaviors in vivo.

Unravelling soft interfaces: Visualization of gel ridges.

HYPOTHESIS: 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. EXPERIMENTS: Gel-on-gel contact systems were fabricated using immiscible organogels and hydrogels. Titanium dioxide (TiO2) 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. FINDINGS: Our investigation demonstrated that a minimal amount of TiO2 NPs effectively delineates the direct contact radius between organogel polymeric networks and hydrogel surfaces. Comparative experiments showed that TiO2 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.

Magnetically Responsive Gallium-Based Liquid Metal: Preparation, Property and Application.

Magnetically responsive soft smart materials have garnered significant academic attention due to their flexibility, remote controllability, and reconfigurability. However, traditional soft materials used in the construction of these magnetically responsive systems typically exhibit low density and poor thermal and electrical conductivities. These limitations result in suboptimal performance in applications such as medical radiography, high-performance electronic devices, and thermal management. To address these challenges, magnetically responsive gallium-based liquid metals have emerged as promising alternatives. In this review, we summarize the methodologies for achieving magnetically responsive liquid metals, including the integration of magnetic agents into the liquid metal matrix and the utilization of induced Lorentz forces. We then provide a comprehensive discussion of the key physicochemical properties of these materials and the factors influencing them. Additionally, we explore the advanced and potential applications of magnetically responsive liquid metals. Finally, we discuss the current challenges in this field and present an outlook on future developments and research directions.

A simple active fluid model unites cytokinesis, cell crawling, and axonal outgrowth.

Axonal outgrowth, cell crawling, and cytokinesis utilize actomyosin, microtubule-based motors, cytoskeletal dynamics, and substrate adhesions to produce traction forces and bulk cellular motion. While it has long been appreciated that growth cones resemble crawling cells and that the mechanisms that drive cytokinesis help power cell crawling, they are typically viewed as unique processes. To better understand the relationship between these modes of motility, here, we developed a unified active fluid model of cytokinesis, amoeboid migration, mesenchymal migration, neuronal migration, and axonal outgrowth in terms of cytoskeletal flow, adhesions, viscosity, and force generation. Using numerical modeling, we fit subcellular velocity profiles of the motions of cytoskeletal structures and docked organelles from previously published studies to infer underlying patterns of force generation and adhesion. Our results indicate that, during cytokinesis, there is a primary converge zone at the cleavage furrow that drives flow towards it; adhesions are symmetric across the cell, and as a result, cells are stationary. In mesenchymal, amoeboid, and neuronal migration, the site of the converge zone shifts, and differences in adhesion between the front and back of the cell drive crawling. During neuronal migration and axonal outgrowth, the primary convergence zone lies within the growth cone, which drives actin retrograde flow in the P-domain and bulk anterograde flow of the axonal shaft. They differ in that during neuronal migration, the cell body is weakly attached to the substrate and thus moves forward at the same velocity as the axon. In contrast, during axonal outgrowth, the cell body strongly adheres to the substrate and remains stationary, resulting in a decrease in flow velocity away from the growth cone. The simplicity with which cytokinesis, cell crawling, and axonal outgrowth can be modeled by varying coefficients in a simple model suggests a deep connection between them.

A Versatile Photocrosslinkable Silicone Composite for 3D Printing Applications.

Embedded printing has emerged as a valuable tool for fabricating complex structures and microfluidic devices. Currently, an ample of amount of research is going on to develop new materials to advance its capabilities and increase its potential applications. Here, we demonstrate a novel, transparent, printable, photocrosslinkable, and tuneable silicone composite that can be utilized as a support bath or an extrudable ink for embedded printing. Its properties can be tuned to achieve ideal rheological properties, such as optimal self-recovery and yield stress, for use in 3D printing. When used as a support bath, it facilitated the generation microfluidic devices with circular channels of diameter up to 30 µm. To demonstrate its utility, flow focusing microfluidic devices were fabricated for generation of Janus microrods, which can be easily modified for multitude of applications. When used as an extrudable ink, 3D printing of complex-shaped constructs were achieved with integrated electronics, which greatly extends its potential applications towards soft robotics. Further, its biocompatibility was tested with multiple cell types to validate its applicability for tissue engineering. Altogether, this material offers a myriad of potential applications (i.e., soft robotics, microfluidics, bioprinting) by providing a facile approach to develop complicated 3D structures and interconnected channels.

Interfacial Engineering of Soft Matter Substrates by Solid-State Polymer Adsorption.

Polymer coating to substrates alters surface chemistry and imparts bulk material functionalities with a minute thickness, even in nanoscale. Specific surface modification of a substate usually requires an active substrate that, e.g., undergoes a chemical reaction with the modifying species. Here, we present a generic method for surface modification, namely, solid-state adsorption, occurring purely by entropic strive. Formed by heating above the melting point or glass transition and subsequent rinsing of the excess polymer, the emerging ultrathin (<10 nm) layers are known in fundamental polymer physics but have never been utilized as building blocks for materials and they have never been explored on soft matter substrates. We show with model surfaces as well as bulk substrates, how solid-state adsorption of common polymers, such as polystyrene and poly(lactic acid), can be applied on soft, cellulose-based substrates. Our study showcases the versatility of solid-state adsorption across various polymer/substrate systems. Specifically, we achieve proof-of-concept hydrophobization on flexible cellulosic substrates, maintaining irreversible and miniscule adsorption yet with nearly 100% coverage without compromising the bulk material properties. The method can be considered generic for all polymers whose Tg and Tm are below those of the to-be-coated adsorbed layer, and whose integrity can withstand the solvent leaching conditions. Its full potential has broad implications for diverse materials systems where surface coatings play an important role, such as packaging, foldable electronics, or membrane technology.

Development of a Self-Healing Gel with Self-Healing Kinetics That Can Be Controlled by Heat.

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.

Changes in the material properties of spider glue droplet proteins accompanied shifts in prey capture biomechanics as cobweb spiders diverged from their orb weaving ancestors.

Although descended from orb weavers, spiders in the family Theridiidae spin cobwebs whose sticky prey capture gumfoot lines extend from a silk tangle to a surface below. When a crawling insect contacts glue droplets at the bottom of a gumfoot line, the line's weak pyriform anchor releases, causing the taut line to contract, pulling the insect from the surface and making its struggles to escape ineffective. To determine if this change in prey capture biomechanics was accompanied by a change in the material properties of theridiid glue, we characterized the elastic modulus and toughness of the glue droplet proteins of four theridiid species at 20-90 % relative humidity and compared their properties with those of 13 orb weaving species in the families Tetragnathidae and Araneidae. Compared to orb weavers, theridiid glue proteins had low extensions per protein volume and low elastic modulus and toughness values. These differences are likely explained by the loss of tension on a gumfoot line when its anchor fails, which may prioritize glue droplet adhesion rather than extension. Similarities in theridiid glue droplet properties did not reflect these species' evolutionary relationships. Instead, they appear associated with differences in web architecture. Two species that had stiffer gumfoot support lines and longer and more closely spaced gumfoot lines also had stiffer glue proteins. These lines may store more energy, and, when their anchors release, require stiffer glue to resist the more forceful upward thrust of a prey. STATEMENT OF SIGNIFICANCE: When a crawling insect contacts glue droplets on a theridiid cobweb's gumfoot line, this taut line's anchor fails and the insect is hoisted upward, rendering its struggles to escape ineffective. This strategy contrasts with that of orb weaving ancestors, which rely on more closely spaced prey capture threads to intercept and retain flying insects. A comparison of the elastic modulus and toughness of gumfoot and orb web glue proteins shows that this change in prey capture biomechanics is associated with reductions in the stiffness and toughness of cobweb glue. Unlike orb web capture threads, whose droplets extend in a coordinated fashion to sum adhesive forces, gumfoot lines become untethered, which prioritizes glue droplet adhesive contact over glue droplet extension.

Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques.

Diffuse soft matter interfaces take many forms, from end-tethered polymer brushes or adsorbed surfactants to self-assembled layers of lipids. These interfaces play crucial roles across a multitude of fields, including materials science, biophysics, and nanotechnology. Understanding the nanostructure and properties of these interfaces is fundamental for optimising their performance and designing novel functional materials. In recent years, reflectometry techniques, in particular neutron reflectometry, have emerged as powerful tools for elucidating the intricate nanostructure of soft matter interfaces with remarkable precision and depth. This review provides an overview of selected recent developments in reflectometry and their applications for illuminating the nanostructure of diffuse interfaces. We explore various principles and methods of neutron and X-ray reflectometry, as well as ellipsometry, and discuss advances in their experimental setups and data analysis approaches. Improvements to experimental neutron reflectometry methods have enabled greater time resolution in kinetic measurements and elucidation of diffuse structure under shear or confinement, while innovation in analysis protocols has significantly reduced data processing times, facilitated co-refinement of reflectometry data from multiple instruments and provided greater-than-ever confidence in proposed structural models. Furthermore, we highlight some significant research findings enabled by these techniques, revealing the organisation, dynamics, and interfacial phenomena at the nanoscale. We also discuss future directions and potential advancements in reflectometry techniques. By shedding light on the nanostructure of diffuse interfaces, reflectometry techniques enable the rational design and tailoring of interfaces with enhanced properties and functionalities.

3D-Printing Multi-Component Multi-Domain Supramolecular Gels with Differential Conductivity.

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.

Direct Imaging of Radiation-Sensitive Organic Polymer-Based Nanocrystals at Sub-Ångström Resolution.

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.

Short-range correlation of stress chains near solid-to-liquid transition in active monolayers.

Using a three-dimensional model of cell monolayers, we study the spatial organization of active stress chains as the monolayer transitions from a solid to a liquid state. The critical exponents that characterize this transition map the isotropic stress percolation onto the two-dimensional random percolation universality class, suggesting short-range stress correlations near this transition. This mapping is achieved via two distinct, independent pathways: (i) cell-cell adhesion and (ii) active traction forces. We unify our findings by linking the nature of this transition to high-stress fluctuations, distinctly linked to each pathway. The results elevate the importance of the transmission of mechanical information in dense active matter and provide a new context for understanding the non-equilibrium statistical physics of phase transition in active systems.

Lipid Membrane Topographies Are Regulators for the Spatial Distribution of Liquid Protein Condensates.

Liquid protein condensates play important roles in orchestrating subcellular organization and as biochemical reaction hubs. Recent studies have linked lipid membranes to proteins capable of forming liquid condensates, and shown that biophysical parameters, like protein enrichment and restricted diffusion at membranes, regulate condensate formation and size. However, the impact of membrane topography on liquid condensates remains poorly understood. Here, we devised a cell-free system to reconstitute liquid condensates on lipid membranes with microstructured topographies and demonstrated that lipid membrane topography is a significant biophysical regulator. Using membrane surfaces designed with microwells, we observed ordered condensate patterns. Furthermore, we demonstrate that membrane topographies influence the shape of liquid condensates. Finally, we show that capillary forces, mediated by membrane topographies, lead to the directed fusion of liquid condensates. Our results demonstrate that membrane topography is a potent biophysical regulator for the localization and shape of mesoscale liquid protein condensates.

Tripling of the scattering vector range of X-ray reflectivity on liquid surfaces using a double-crystal deflector.

The maximum range of perpendicular momentum transfer (q z) 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 q z direction on liquid surfaces up to q z = 7 Å-1 is presented, with liquid copper serving as a reference system for benchmarking purposes.

Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge.

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.