Programmable responsive hydrogels inspired by classical conditioning algorithm

Hydrogels with Differentiated Hydrogen-Bonding Networks for Bioinspired Stress Response

Stress response, an intricate and autonomously coordinated reaction in living organisms, holds a reversible, multi-path, and multi-state nature. However, existing stimuli-responsive materials often exhibit single-step and monotonous reactions due to the limited integration of structural components. Inspired by the cooperative interplay of extensor and flexor cells within Mimosa's pulvini, we present a hydrogel with differentiated hydrogen-bonding (H-bonding) networks designed to enable the biological stress response. Weak H-bonding domains resemble flexor cells, confined within a hydrophobic network stabilized by strong H-bonding clusters (acting like extensor cells). Under external force, strong H-bonding clusters are disrupted, facilitating water diffusion from the bottom layer and enabling transient expansion pressure gradient along the thickness direction. Subsequently, water diffuses upward, gradually equalizing the pressure, while weak H-bonding domains undergo cooperative elastic deformation. Consequently, the hydrogel autonomously undergoes a sequence of reversible and pluralistic motion responses, similar to Mimosa's touch-triggered stress response. Intriguingly, it exhibits stress-dependent color shifts under polarized light, highlighting its potential for applications in time-sensitive "double-lock" information encryption systems. This work achieves the coordinated stress response inspired by natural tissues using a simple hydrogel, paving the way for substantial advancements in the development of intelligent soft robots.

Piezoionic Elastomers by Phase and Interface Engineering for High-Performance Energy-Harvesting Ionotronics

Piezoionic materials play a pivotal role in energy-harvesting ionotronics. However, a persistent challenge lies in balancing the structural requirements for voltage generation, current conduction, and mechanical adaptability. The conventional approach of employing crystalline heterostructures for stress concentration and localized charge separation, while effective for voltage generation, often compromises the stretchability and long-range charge transport found in homogeneous quasisolid states. Herein, phase and interface engineering strategy is introduced to address this dilemma and a piezoionic elastomer is presented that seamlessly integrates ionic liquids and ionic plastic crystals, forming a finely tuned microphase-separated structure with an intermediate phase. This approach promotes charge separation via stress concentration among hard phases while leveraging the high ionic charge mobility in soft and intermediate phases. Impressively, the elastomer achieves an extraordinary piezoionic coefficient of about 6.0 mV kPa-1, a more than threefold improvement over current hydrogels and ionogels. The resulting power density of 1.3 µW cm-3 sets a new benchmark, exceeding that of state-of-the-art piezoionic gels. Notably, this elastomer combines outstanding stretchability, remarkable toughness, and rapid self-healing capability, underscoring its potential for real-world applications. This work may represent a stride toward mechanically robust energy harvesting systems and provide insights into ionotronic systems for human-machine interaction.

Trainable bioinspired magnetic sensitivity adaptation using ferromagnetic colloidal assemblies

Nature has already suggested bioinspired functions. Beyond them, adaptive and trainable functions could be the inspiration for novel responsive soft matter beyond the state-of-the-art classic static bioinspired, stimulus-responsive, and shape-memory materials. Here, we describe magnetic assembly/disassembly of electrically conducting soft ferromagnetic nickel colloidal particles into surface topographical pillars for bistable electrical trainable memories. They allow magnetic sensing with adaptable and rescalable sensitivity ranges, enabled by bistable memories and kinetic concepts inspired by biological sensory adaptations. Based on the soft ferromagnetism of the nanogranular composition and the resulting rough particle surfaces prepared via a solvothermal synthesis, triggerable structural memory is achieved by the magnetic field-driven particle assembly and disassembly, promoted by interparticle jamming. Electrical conversion from current to frequency for electrical spikes facilitates rescalable and trainable frequency-based sensitivity on magnetic fields. This work suggests an avenue for designing trainable and adaptable life-inspired materials, for example, for soft robotics and interactive autonomous devices.

Embedded Physical Intelligence in Liquid Crystalline Polymer Actuators and Robots

Responsive materials possess the inherent capacity to autonomously sense and respond to various external stimuli, demonstrating physical intelligence. Among the diverse array of responsive materials, liquid crystalline polymers (LCPs) stand out for their remarkable reversible stimuli-responsive shape-morphing properties and their potential for creating soft robots. While numerous reviews have extensively detailed the progress in developing LCP-based actuators and robots, there exists a need for comprehensive summaries that elucidate the underlying principles governing actuation and how physical intelligence is embedded within these systems. This review provides a comprehensive overview of recent advancements in developing actuators and robots endowed with physical intelligence using LCPs. This review is structured around the stimulus conditions and categorizes the studies involving responsive LCPs based on the fundamental control and stimulation logic and approach. Specifically, three main categories are examined: systems that respond to changing stimuli, those operating under constant stimuli, and those equip with learning and logic control capabilities. Furthermore, the persisting challenges that need to be addressed are outlined and discuss the future avenues of research in this dynamic field.

Engineered Dynamic Hydrogel Niches for the Regulation of Redox Homeostasis in Osteoporosis and Degenerative Endocrine Diseases

Osteoporosis and degenerative endocrine diseases are some of the major causes of disability in the elderly. The feedback loop in the endocrine system works to control the release of hormones and maintain the homeostasis of metabolism, thereby regulating the function of target organs. The breakdown of this feedback loop results in various endocrine and metabolic disorders, such as osteoporosis, type II diabetes, hyperlipidemia, etc. The direct regulation of redox homeostasis is one of the most attractive strategies to redress the imbalance of the feedback loop. The biophysical regulation of redox homeostasis can be achieved through engineered dynamic hydrogel niches, with which cellular mechanics and redox homeostasis are intrinsically connected. Mechanotransduction-dependent redox signaling is initiated by cell surface protein assemblies, cadherins for cell-cell junctions, and integrins for cell-ECM interactions. In this review, we focused on the biophysical regulation of redox homeostasis via the tunable cell-ECM interactions in the engineered dynamic hydrogel niches. We elucidate processes from the rational design of the hydrogel matrix to the mechano-signaling initiation and then to the redox response of the encapsulated cells. We also gave a comprehensive summary of the current biomedical applications of this strategy in several degenerative endocrine disease models.

Mean-field models for the chemical fueling of transient soft matter states

The chemical fueling of transient states (CFTS) is a powerful process to control the nonequilibrium structuring and the homeostatic function of adaptive soft matter systems. Here, we introduce a simple mean-field model of CFTS based on the activation of metastable equilibrium states in a tilted 'Landau' bistable energy landscape along a coarse-grained reaction coordinate (or 'order parameter') triggered by a nonmonotonic two-step chemical fueling reaction. Evaluation of the model in the quasi-static (QS) limit-valid for fast system relaxation-allows us to extract useful analytical laws for the critical activation concentration and duration of the transient states in dependence of physical parameters, such as rate constants, fuel concentrations, and the system's distance to its equilibrium transition point. We apply our model in the QS limit explicitly to recent experiments of CFTS of collapsing responsive microgels and find a very good performance with only a few global and physically interpretable fitting parameters, which can be employed for programmable material design. Moreover, our model framework also allows a thermodynamic analysis of the energy and performed work in the system. Finally, we go beyond the QS limit, where the system's response is slow and retarded versus the chemical reaction, using an overdamped Smoluchowski approach. The latter demonstrates how internal system time scales can be used to tune the time-dependent behavior and programmed delay of the transient states in full nonequilibrium.

Thermally trainable dual network hydrogels

Inspired by biological systems, trainable responsive materials have received burgeoning research interests for future adaptive and intelligent material systems. However, the trainable materials to date typically cannot perform active work, and the training allows only one direction of functionality change. Here, we demonstrate thermally trainable hydrogel systems consisting of two thermoresponsive polymers, where the volumetric response of the system upon phase transitions enhances or decreases through a training process above certain threshold temperature. Positive or negative training of the thermally induced deformations can be achieved, depending on the network design. Importantly, softening, stiffening, or toughening of the hydrogel can be achieved by the training process. We demonstrate trainable hydrogel actuators capable of performing increased active work or implementing an initially impossible task. The reported dual network hydrogels provide a new training strategy that can be leveraged for bio-inspired soft systems such as adaptive artificial muscles or soft robotics.

Non-Specific Responsive Nanogels and Plasmonics to Design MathMaterial Sensing Interfaces: The Case of a Solvent Sensor

The combination of non-specific deformable nanogels and plasmonic optical probes provides an innovative solution for specific sensing using a generalistic recognition layer. Soft polyacrylamide nanogels that lack specific selectivity but are characterized by responsive behavior, i.e., shrinking and swelling dependent on the surrounding environment, were grafted to a gold plasmonic D-shaped plastic optical fiber (POF) probe. The nanogel-POF cyclically challenged with water or alcoholic solutions optically reported the reversible solvent-to-phase transitions of the nanomaterial, embodying a primary optical switch. Additionally, the non-specific nanogel-POF interface exhibited more degrees of freedom through which specific sensing was enabled. The real-time monitoring of the refractive index variations due to the time-related volume-to-phase transition effects of the nanogels enabled us to determine the environment's characteristics and broadly classify solvents. Hence the nanogel-POF interface was a descriptor of mathematical functions for substance identification and classification processes. These results epitomize the concept of responsive non-specific nanomaterials to perform a multiparametric description of the environment, offering a specific set of features for the processing stage and particularly suitable for machine and deep learning. Thus, soft MathMaterial interfaces provide the ground to devise devices suitable for the next generation of smart intelligent sensing processes.

Self-assembled liquid crystal architectures for soft matter photonics

Self-assembled architectures of soft matter have fascinated scientists for centuries due to their unique physical properties originated from controllable orientational and/or positional orders, and diverse optic and photonic applications. If one could know how to design, fabricate, and manipulate these optical microstructures in soft matter systems, such as liquid crystals (LCs), that would open new opportunities in both scientific research and practical applications, such as the interaction between light and soft matter, the intrinsic assembly of the topological patterns, and the multidimensional control of the light (polarization, phase, spatial distribution, propagation direction). Here, we summarize recent progresses in self-assembled optical architectures in typical thermotropic LCs and bio-based lyotropic LCs. After briefly introducing the basic definitions and properties of the materials, we present the manipulation schemes of various LC microstructures, especially the topological and topographic configurations. This work further illustrates external-stimuli-enabled dynamic controllability of self-assembled optical structures of these soft materials, and demonstrates several emerging applications. Lastly, we discuss the challenges and opportunities of these materials towards soft matter photonics, and envision future perspectives in this field.

From Precision Colloidal Hybrid Materials to Advanced Functional Assemblies

ConspectusThe concept of colloids encompasses a wide range of isotropic and anisotropic particles with diverse sizes, shapes, and functions from synthetic nanoparticles, nanorods, and nanosheets to functional biological units. They are addressed in materials science for various functions, while they are ubiquitous in the biological world for multiple functions. A large variety of synthetic colloids have been researched due to their scientific and technological importance; still they characteristically suffer from finite size distributions, imperfect shapes and interactions, and not fully engineered functions. This contrasts with biological colloids that offer precision in their size, shape, and functionality. Materials science has searched for inspiration from the biological world to allow structural control by self-assembly and hierarchy and to identify novel routes for combinations of functions in bio-inspiration.Herein, we first discuss different approaches for highly defined structural control of technically relevant synthetic colloids based on guided assemblies of biological motifs. First, we describe how polydisperse nanoparticles can be assembled within hollow protein cages to allow well-defined assemblies and hierarchical packings. Another approach relies on DNA nanotechnology-based assemblies, where engineered DNA structures allow programmed assembly. Then we will discuss synthetic colloids that have either particularly narrow size dispersity or even atomically precise structures for new assemblies and potential functions. Such colloids can have well-defined packings for membranes allowing high modulus. They can be switchable using light-responsive moieties, and they can initiate packing of larger assemblies of different geometrical shapes. The emphasis is on atomically defined nanoclusters that allow well-defined assemblies by supramolecular interactions, such as directional hydrogen bonding. Finally, we will discuss stimulus-responsive colloids for new functions, even toward complex responsive functions inspired by life. Therein, stimulus-responsive materials inspired by biological learning could allow the next generation of such materials. Classical conditioning is among the simplest biological learning concepts, requiring two stimuli and triggerable memory. Therein we use thermoresponsive hydrogels with plasmonic gold nanoparticles and a spiropyran photoacid as a model. Heating is the unconditioned stimulus leading to melting of the thermoresponsive gel, whereas light (at a specified wavelength) originally leads to reduced pH without plasmonic or structural changes because of steric gel stabilization. Under heat-induced gel melting, light results in pH-decrease and chain-like aggregation of the gold nanoparticles, allowing a new plasmonic response. Thus, simultaneous heating and light irradiation allow conditioning for a newly derived stimulus, where the logic diagram is analogous to Pavlovian conditioning. The shown assemblies demonstrate the different functionalities achievable using colloids when the sizes and the dispersity are controlled.

Near-Infrared Light-Driven Shape-Programmable Hydrogel Actuators Loaded with Metal-Organic Frameworks

Shape-programmable hydrogel-based soft actuators that can adaptively respond to external stimuli are of paramount significance for the development of bioinspired aquatic smart soft robots. Herein, we report the design and synthesis of near-infrared (NIR) light-driven hydrogel actuators through in situ photopolymerization of poly(N-isopropylacrylamide) (PNIPAM) hydrogels loaded with metal-organic frameworks (MOFs) onto the surface of the poly(dimethylsiloxane) (PDMS) thin film. The MOFs can not only function as an excellent photothermal nanotransducer but also accelerate the adsorption/desorption of water due to their porous nanostructure, which speeds up the response rate of the actuators. Shape-programmable hydrogel actuators are fabricated by tailoring the patterning of PDMS thin film, and thus different shape-morphing modes such as directional bending and chiral twisting are observed under the NIR light irradiations. As the proof-of-concept demonstrations, an artificial hand, biomimetic mimosa, and flower are conceptualized with light-driven MOF-containing hydrogel actuators. Interestingly, we are able to achieve an octopus-inspired light-driven soft swimmer upon cyclic NIR illumination due to the fast photoresponsiveness of as-prepared hydrogel actuators. This work can offer insights for fabricating programmable and reconfigurable smart aquatic soft actuators, thus shining a light into their potential applications in emerging fields including soft robots, biomedical devices, and beyond.

Photoacid-Enabled Synthesis of Indanes via Formal [3 + 2] Cycloaddition of Benzyl Alcohols with Olefins

An environmentally friendly and highly diastereoselective method for synthesizing indanes has been developed via a metastable-state photoacid system containing catalytic protonated merocyanine (MEH). Under visible-light irradiation, MEH yields a metastable spiro structure and liberated protons, which facilitates the formation of carbocations from benzyl alcohols, thus delivering diverse molecules in the presence of various nucleophiles. Mainly, a variety of indanes could be easily obtained from benzyl alcohols and olefins, and water is the only byproduct.

Specific recognition and photothermal release of circulating tumor cells using near-infrared light-responsive 2D MXene nanosheets@hydrogel membranes

2D materials with attractive optical properties are promising for individualized cancer immunotherapy. Isolation, capture, and release of circulating tumor cells (CTCs) are of great significance for promoting the process of early diagnosis of cancers. MXene nanosheets incorporated gelatin hydrogel offers the possibility of achieving near-infrared (NIR) light response to initiate the photothermal effect. Herein, the design and preparation of Ti₃C₂T_x MXene nanosheets-embedded thermoresponsive gelatin hydrogel membrane with NIR light-responsive for the specific capture and release of CTCs were reported. The membrane was fabricated by casting Ti₃C₂T_x-embedded gelatin onto a substrate and then modified with epithelial-cell adhesion-molecule antibody (anti-EpCAM) for the specific recognition and separation of CTCs from whole blood. The captured cells can be released without damage with dual-mode containing temperature-responsive release (gelatin deconstructed at 37 °C) and photothermal site-release (Ti₃C₂T_x induced by NIR light). Furthermore, we were able to achieve an average efficient release rate of 89 % of captured cells with stable cell viability of 87 % via the NIR light irradiation. This work may provide the promising potential for retrieval of single cells in clinical diagnosis.

Deconstruction and Reassembly of Renewable Polymers and Biocolloids into Next Generation Structured Materials

This review considers the most recent developments in supramolecular and supraparticle structures obtained from natural, renewable biopolymers as well as their disassembly and reassembly into engineered materials. We introduce the main interactions that control bottom-up synthesis and top-down design at different length scales, highlighting the promise of natural biopolymers and associated building blocks. The latter have become main actors in the recent surge of the scientific and patent literature related to the subject. Such developments make prominent use of multicomponent and hierarchical polymeric assemblies and structures that contain polysaccharides (cellulose, chitin, and others), polyphenols (lignins, tannins), and proteins (soy, whey, silk, and other proteins). We offer a comprehensive discussion about the interactions that exist in their native architectures (including multicomponent and composite forms), the chemical modification of polysaccharides and their deconstruction into high axial aspect nanofibers and nanorods. We reflect on the availability and suitability of the latter types of building blocks to enable superstructures and colloidal associations. As far as processing, we describe the most relevant transitions, from the solution to the gel state and the routes that can be used to arrive to consolidated materials with prescribed properties. We highlight the implementation of supramolecular and superstructures in different technological fields that exploit the synergies exhibited by renewable polymers and biocolloids integrated in structured materials.

A nanoimprinted artificial engram device

At present, mainstream neuromorphic hardware is based on artificial synapses; however, an engram, instead of a synapse, has recently been confirmed as the basic unit of memory, which verifies the engram theory proposed by Richard Semon in 1904. Here, we demonstrate an artificial engram device based on a nanoimprinted curable resin. The variation in the relative diffraction efficiency based on the asymmetric reversible topological change of the nanoimprinted resin enables the device to meet all the requirements for artificial engrams, including synaptic plasticity, long memory storage time, asymmetric memorizing-forgetting behaviour and measurable changes and responses. On this basis, we demonstrate the concept of realizing memory formation, memory manipulation and implantation, and memory consolidation using our artificial engram device in comparison with its biological counterpart.

Light-fueled transient supramolecular assemblies in water as fluorescence modulators

Dissipative self-assembly, which requires a continuous supply of fuel to maintain the assembled states far from equilibrium, is the foundation of biological systems. Among a variety of fuels, light, the original fuel of natural dissipative self-assembly, is fundamentally important but remains a challenge to introduce into artificial dissipative self-assemblies. Here, we report an artificial dissipative self-assembly system that is constructed from light-induced amphiphiles. Such dissipative supramolecular assembly is easily performed using protonated sulfonato-merocyanine and chitosan based molecular and macromolecular components in water. Light irradiation induces the assembly of supramolecular nanoparticles, which spontaneously disassemble in the dark due to thermal back relaxation of the molecular switch. Owing to the presence of light-induced amphiphiles and the thermal dissociation mechanism, the lifetimes of these transient supramolecular nanoparticles are highly sensitive to temperature and light power and range from several minutes to hours. By incorporating various fluorophores into transient supramolecular nanoparticles, the processes of aggregation-induced emission and aggregation-caused quenching, along with periodic variations in fluorescent color over time, have been demonstrated. Transient supramolecular assemblies, which act as fluorescence modulators, can also function in human hepatocellular cancer cells.

Dissipative self-assembly, which requires a continuous supply of fuel to maintain the assembled states far from equilibrium, is the foundation of biological systems but it remains a challenge to introduce light as fuel into artificial dissipative self-assemblies. Here, the authors report an artificial dissipative self-assembly system that is constructed from light-induced amphiphiles.

Recent Progress of Layer-by-layer Assembly, Free-Standing Film and Hydrogel Based on Polyelectrolytes

Nowadays, polyelectrolytes play an essential role in the development of new materials. Their use allows creating new properties of materials and surfaces and vary them in a wide range. Basically, modern methods are divided into three areas-the process of layer-by-layer deposition, free-standing films, and hydrogels based on polyelectrolytes. Layer-by-layer assembly of polyelectrolytes on various surfaces is a powerful technique. It allows giving surfaces new properties, for example, protect them from corrosion. Free-standing films are essential tools for the design of membranes and sensors. Hydrogels based on polyelectrolytes have recently shown their applicability in electrical and materials science. The creation of new materials and components with controlled properties can be achieved using polyelectrolytes. This review focuses on new technologies that have been developed with polyelectrolytes over the last five years.

The rise of intelligent matter

Artificial intelligence (AI) is accelerating the development of unconventional computing paradigms inspired by the abilities and energy efficiency of the brain. The human brain excels especially in computationally intensive cognitive tasks, such as pattern recognition and classification. A long-term goal is de-centralized neuromorphic computing, relying on a network of distributed cores to mimic the massive parallelism of the brain, thus rigorously following a nature-inspired approach for information processing. Through the gradual transformation of interconnected computing blocks into continuous computing tissue, the development of advanced forms of matter exhibiting basic features of intelligence can be envisioned, able to learn and process information in a delocalized manner. Such intelligent matter would interact with the environment by receiving and responding to external stimuli, while internally adapting its structure to enable the distribution and storage (as memory) of information. We review progress towards implementations of intelligent matter using molecular systems, soft materials or solid-state materials, with respect to applications in soft robotics, the development of adaptive artificial skins and distributed neuromorphic computing.

Continuous learning of emergent behavior in robotic matter

In the last century, robots have been revolutionizing our lives, augmenting human actions with greater precision and repeatability. Unfortunately, most robotic systems can only operate in controlled environments. While increasing the complexity of the centralized controller is an instinctive direction to enable robots that are capable of autonomously adapting to their environment, there are ample examples in nature where adaptivity emerges from simpler decentralized processes. Here we perform experiments and simulations on a modular and scalable robotic platform in which each unit is stochastically updating its own behavior to explore requirements needed for a decentralized learning strategy capable of achieving locomotion in a continuously changing environment or when undergoing damage.

One of the main challenges in robotics is the development of systems that can adapt to their environment and achieve autonomous behavior. Current approaches typically aim to achieve this by increasing the complexity of the centralized controller by, e.g., direct modeling of their behavior, or implementing machine learning. In contrast, we simplify the controller using a decentralized and modular approach, with the aim of finding specific requirements needed for a robust and scalable learning strategy in robots. To achieve this, we conducted experiments and simulations on a specific robotic platform assembled from identical autonomous units that continuously sense their environment and react to it. By letting each unit adapt its behavior independently using a basic Monte Carlo scheme, the assembled system is able to learn and maintain optimal behavior in a dynamic environment as long as its memory is representative of the current environment, even when incurring damage. We show that the physical connection between the units is enough to achieve learning, and no additional communication or centralized information is required. As a result, such a distributed learning approach can be easily scaled to larger assemblies, blurring the boundaries between materials and robots, paving the way for a new class of modular “robotic matter” that can autonomously learn to thrive in dynamic or unfamiliar situations, for example, encountered by soft robots or self-assembled (micro)robots in various environments spanning from the medical realm to space explorations.

Unveiling the urease like intrinsic catalytic activities of two dinuclear nickel complexes towards the in situ syntheses of aminocyanopyridines

Designing metal complexes as functional models for metalloenzymes remains one of the main targets in synthetic bioinorganic chemistry. Furthermore, the utilization of the product(s) derived from the catalytic reaction for subsequent organic transformation that occurs in biological systems is an even more difficult challenge for biochemists. Urease, the most efficient enzyme known, catalyzes the hydrolysis of urea and it contains an essential dinuclear Ni^II cluster in the active site. Inspired by the catalytic properties of urease, two dinickel(ii) complexes viz. Ni₂L¹₂(OAc)₂(H₂O) (1) and Ni₂L²₂(OAc)₂(H₂O) (2) [HL1 = 2,4-dimethyl-6-{[(2'-dimethyl aminoethyl)methylamino]methyl}-phenol and HL2 = 2,4-dichloro-6-{[(2'-dimethyl aminoethyl)methylamino]methyl}-phenol] have been synthesized and characterized in this report. Both the complexes have shown the urease kind of activity with the liberation of ammonia from urea in aqueous solution. The plausible mechanistic pathway and kinetics of the reactions have been studied. Besides, the liberated ammonia has been utilized in the one-pot synthesis of biologically active products like 2-amino-3-cyanopyridines and their derivatives in aqueous medium with excellent yields.

Light-induced switching of polymer-surfactant interactions enables controlled polymer thermoresponsive behaviour

Hydroxypropyl cellulose (HPC) and arylazopyrazole (AAP) mixtures can be remotely controlled by light and temperature. We show that the hydrophobic interactions between HPC polymers with AAP surfactants can be drastically changed by changing the surfactants configuration through E/Z photo-isomerization. E-AAP interacts strongly with HPC which causes a dramatic increase of the critical temperature Tc of the polymers' phase transition and a loss of the coil-to-globule transition, while the hydrophobic interactions of HPC with Z-AAP are drastically reduced. As a result, E/Z photo-isomerization of AAP in mixtures with HPC offers remote control of the polymers phase transition, size and solution viscosity in an unprecedented way, and allows for new directions in colloid science.

Thermodynamics and kinetics of protonated merocyanine photoacids in water

Metastable-state photoacids (mPAHs) are chemical species whose photo-activated state is long-lived enough to allow for proton diffusion. Liao's photoacid (1) represents the archetype of mPAHs, and is being widely used on account of its unique capability to change the acidity of aqueous solutions reversibly. The behavior of 1 in water, however, still remains poorly understood. Herein, we provide in-depth insights on the thermodynamics and kinetics of 1 in water through a series of comparative 1H NMR and UV-Vis studies and relative modelling. Under dark conditions, we quantified a three-component equilibrium system where the dissociation (K a) of the open protonated form (MCH) is followed by isomerization (K c) of the open deprotonated form (MC) to the closed spiropyran form (SP) - i.e., in the absence of light, the ground state acidity can be expressed as K GS a = K a(1 + K c). On the other hand, under powerful and continuous light irradiation we were able to assess, for the first time experimentally, the dissociation constant (K MS a) of the protonated metastable state (cis-MCH). In addition, we found that thermal ring-opening of SP is always rate-determining regardless of pH, whereas hydrolysis is reminiscent of what is found for Schiff bases. The proposed methodology is general, and it was applied to two other compounds bearing a shorter (ethyl, 2) and a longer (butyl, 3) alkyl-1-sulfonate bridge. We found that the pK a remains constant, whereas both pK c and pK MS a linearly increase with the length of the alkyl bridge. Importantly, all results are consistent with a four-component model cycle, which describes perfectly the full dynamics of proton release/uptake of 1-3 in water. The superior hydrolytic stability and water solubility of compound 3, together with its relatively high pK GS a (low K c), allowed us to achieve fully reversible jumps of 2.5 pH units over 18 consecutive cycles (6 hours).

Hydrogels as dynamic memory with forgetting ability

The memory of our brain, stored in soft matter, is dynamic, and it forgets spontaneously to filter unimportant information. By contrast, the existing manmade memory, made from hard materials, is static, and it does not forget without external stimuli. Here we propose a principle for developing dynamic memory from soft hydrogels with temperature-sensitive dynamic bonds. The memorizing-forgetting behavior is achieved based on fast water uptake and slow water release upon thermal stimulus, as well as thermal-history-dependent transparency change of these gels. The forgetting time is proportional to the thermal learning time, in analogy to the behavior of brain. The memory is stable against temperature fluctuation and large stretching; moreover, the forgetting process is programmable. This principle may inspire future research on dynamic memory based on the nonequilibrium process of soft matter.

Fast Switching of Bright Whiteness in Channeled Hydrogel Networks

Beside pigment absorption and reflection by periodic photonic structures, natural species often use light scattering to achieve whiteness. Synthetic hydrogels offer opportunities in stimuli-responsive materials and devices; however, they are not conventionally considered as ideal materials to achieve high whiteness by scattering due to the ill-defined porosities and the low refractive index contrast between the polymer and water. Herein, a poly(N-isopropylacrylamide) hydrogel network with percolated empty channels (ch-PNIPAm) is demonstrated to possess switchable bright whiteness upon temperature changes, obtained by removing the physical agarose gel in a semi-interpenetrating network of agarose and PNIPAm. The hydrogel is highly transparent at room temperature and becomes brightly white above 35 °C. Compared to conventional PNIPAm, the ch-PNIPAm hydrogel exhibits 80% higher reflectance at 800 nm and 18 times faster phase transition kinetics. The nanoscopic channels in the ch-PNIPAm facilitate water diffusion upon phase transition, thus enabling the formation of smaller pores and enhanced whiteness in the gel. Furthermore, fast photothermally triggered response down to tens of milliseconds can be achieved. This unique property of the ch-PNIPAm hydrogel to efficiently scatter visible light can be potentially used for, e.g., smart windows, optical switches, and, as demonstrated in this report, thermoresponsive color displays.

Viewpoint: Pavlovian Materials-Functional Biomimetics Inspired by Classical Conditioning

Herein, it is discussed whether the complex biological concepts of (associative) learning can inspire responsive artificial materials. It is argued that classical conditioning, being one of the most elementary forms of learning, inspires algorithmic realizations in synthetic materials, to allow stimuli-responsive materials that learn to respond to a new stimulus, to which they are originally insensitive. Two synthetic model systems coined as "Pavlovian materials" are described, whose stimuli-responsiveness algorithmically mimics programmable associative learning, inspired by classical conditioning. The concepts minimally need a stimulus-triggerable memory, in addition to two stimuli, i.e., the unconditioned and the originally neutral stimuli. Importantly, the concept differs conceptually from the classic stimuli-responsive and shape-memory materials, as, upon association, Pavlovian materials obtain a given response using a new stimulus (the originally neutral one); i.e., the system evolves to a new state. This also enables the functionality to be described by a logic diagram. Ample room for generalization to different stimuli and memory combinations is foreseen, and opportunities to develop future adaptive materials with ever-more intelligent functions are expected.

Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap

Soft matter systems and materials are moving toward adaptive and interactive behavior, which holds outstanding promise to make the next generation of intelligent soft materials systems inspired from the dynamics and behavior of living systems. But what is an adaptive material? What is an interactive material? How should classical responsiveness or smart materials be delineated? At present, the literature lacks a comprehensive discussion on these topics, which is however of profound importance in order to identify landmark advances, keep a correct and noninflating terminology, and most importantly educate young scientists going into this direction. By comparing different levels of complex behavior in biological systems, this Viewpoint strives to give some definition of the various different materials systems characteristics. In particular, the importance of thinking in the direction of training and learning materials, and metabolic or behavioral materials is highlighted, as well as communication and information-processing systems. This Viewpoint aims to also serve as a switchboard to further connect the important fields of systems chemistry, synthetic biology, supramolecular chemistry and nano- and microfabrication/3D printing with advanced soft materials research. A convergence of these disciplines will be at the heart of empowering future adaptive and interactive materials systems with increasingly complex and emergent life-like behavior.

The Many Ways to Assemble Nanoparticles Using Light

The ability to reversibly assemble nanoparticles using light is both fundamentally interesting and important for applications ranging from reversible data storage to controlled drug delivery. Here, the diverse approaches that have so far been developed to control the self-assembly of nanoparticles using light are reviewed and compared. These approaches include functionalizing nanoparticles with monolayers of photoresponsive molecules, placing them in photoresponsive media capable of reversibly protonating the particles under light, and decorating plasmonic nanoparticles with thermoresponsive polymers, to name just a few. The applicability of these methods to larger, micrometer-sized particles is also discussed. Finally, several perspectives on further developments in the field are offered.

Transient Supramolecular Hydrogels Formed by Aging-Induced Seeded Self-Assembly of Molecular Hydrogelators

Here, transient supramolecular hydrogels that are formed through simple aging-induced seeded self-assembly of molecular gelators are reported. In the involved molecular self-assembly system, multicomponent gelators are formed from a mixture of precursor molecules and, typically, can spontaneously self-assemble into thermodynamically more stable hydrogels through a multilevel self-sorting process. In the present work, it is surprisingly found that one of the precursor molecules is capable of self-assembling into nano-sized aggregates upon a gentle aging treatment. Importantly, these tiny aggregates can serve as seeds to force the self-assembly of gelators along a kinetically controlled pathway, leading to transient hydrogels that eventually spontaneously convert into thermodynamically more stable hydrogels over time. Such an aging-induced seeded self-assembly process is not only a new route toward synthetic out-of-equilibrium supramolecular systems, but also suggests the necessity of reporting the age of self-assembling building block solutions in other self-assembly systems.

Associative Learning by Classical Conditioning in Liquid Crystal Network Actuators

Responsive and shape-memory materials allow stimuli-driven switching between fixed states. However, their behavior remains unchanged under repeated stimuli exposure, i.e., their properties do not evolve. By contrast, biological materials allow learning in response to past experiences. Classical conditioning is an elementary form of associative learning, which inspires us to explore simplified routes even for inanimate materials to respond to new, initially neutral stimuli. Here, we demonstrate that soft actuators composed of thermoresponsive liquid crystal networks "learn" to respond to light upon a conditioning process where light is associated with heating. We apply the concept to soft microrobotics, demonstrating a locomotive system that "learns to walk" under periodic light stimulus, and gripping devices able to "recognize" irradiation colors. We anticipate that actuators that algorithmically emulate elementary aspects of associative learning and whose sensitivity to new stimuli can be conditioned depending on past experiences may provide new routes toward adaptive, autonomous soft microrobotics.

A Novel Nanofiber Hydrogel Loaded with Platelet-Rich Plasma Promotes Wound Healing Through Enhancing the Survival of Fibroblasts

Background

Hydrogels are ideal biological carriers in vivo and have been widely used in the treatment of wound healing through loading with or without bioactive substances. Platelet-rich plasma (PRP) is purified from autologous plasma and has known curative efficacy for wound healing. The combined efficacy of shorten poly-N-acetyl glucosamine (sNAG) hydrogels and PRP in the treatment of wound healing has not been previously assessed.

Material/Methods

The cytotoxic and proliferative effects of PRP on fibroblasts were detected using Cell Counting Kit-8 assays and flow cytometry. The levels of cyclin D1 and cyclin D3 were assessed to evaluate cell proliferation. Protein expression was assessed by western blot analysis. Adenosine levels were assessed by enzyme-linked immunosorbent assay. Cell apoptosis was assessed by flow cytometry and western blot analysis. Rat wound models were performed, and the effects of PRP, single hydrogels, and sNAG hydrogels loaded with PRP were respectively detected through the assessment of wound closure. Hematoxylin eosin staining was used to measure the depth and width of regenerative scars.

Results

Our results demonstrated that PRP promotes fibroblast proliferation and inhibits apoptosis. PRP contains abundant levels of adenosine, which has a positive role on fibroblast function, whilst the inhibition of adenosine A2A receptors impairs the efficacy of PRP. sNAG hydrogels loaded with PRP showed curative efficacy during wound healing in mice. Mice treated with hydrogels loaded with PRP showed high levels of regeneration with scarless healing.

Conclusions

Our results indicate that sNAG hydrogels loaded with PRP promote wound healing. The pro-proliferative, and anti-apoptotic effects of the fibroblasts are mediated by the activating A2A receptor in response to elevated adenosine levels.