Associative Learning by Classical Conditioning in Liquid Crystal Network Actuators

Bioinspired learning and memory in ionogels through fast response and slow relaxation dynamics of ions

Mimicking biological systems' sensing, learning, and memory capabilities in synthetic soft materials remains challenging. While significant progress has been made in sensory functions in ionogels, their learning and memory capabilities still lag behind biological systems. Here, we introduce cation-π interactions and a self-adaptable ionic-double-layer interface in bilayer ionogels to control ion transport. Fast ion response enables sensing and learning, while slow ion relaxation supports long-term memory. The ionogels achieve bioinspired functions, including sensitization, habituation, classical conditioning, and multimodal memory, with low energy consumption (0.06 pJ per spike). Additionally, the ionogels exhibit mechanical adaptability, such as stretchability, self-healing, and reconfigurability, making them ideal for soft robotics. Notably, the ionogels enable a robotic arm to mimic the selective capture behavior of a Venus flytrap. This work bridges the gap between biological intelligence and artificial systems, offering promising applications in bioinspired, energy-efficient sensing, learning, and memory.

Force-Trainable Liquid Crystal Elastomer Enabled by Mechanophore-Induced Radical Polymerization

In nature, organisms adapt to environmental changes through training to learn new abilities, offering valuable insights for developing intelligent materials. However, replicating this "adaptive learning" in synthetic materials presents a significant challenge. This study introduces a feasible approach to train liquid crystal elastomers (LCEs) by integrating a mechanophore tetraarylsuccinonitrile into their main chain, addressing the challenge of enabling synthetic materials to exchange substances with their environment. Inspired by biological training, the LCEs can self-strengthen and acquire new functionalities through mechanical stress-induced radical polymerization. The research not only enhances the mechanical performance of LCEs, but also endows them with the ability to learn properties such as flexibility, light responsiveness, and fluorescence. These advancements are crucial for overcoming the limitations of current materials, paving the way for the creation of advanced intelligent soft materials with autonomous self-improvement, akin to the adaptive skills of living organisms.

Hydrogen-bonded multi-mode liquid crystal elastomer actuators

As biomimicry advances, liquid crystal elastomers (LCEs) are gaining attention for their (multi-)stimuli-responsiveness and reversible shape morphing. Introduction of dynamic bonds into the LCEs provides versatile means towards programmable shape morphing and adaptation to environmental cues, and new designs for dynamic LCEs are actively sought for. Here, we present a supramolecular LCE that integrates shape memory programming, humidity sensitivity, and photochemical actuation. By utilizing hydrogen bonding crosslinks, the LCE gains shape memory functionality, enabling arbitrary shape programming and photochemical actuation. By breaking the supramolecular crosslinks via base treatment, the LCE becomes hygroscopic and humidity sensitive, yet maintains photochemical deformability. These two states enable different types of soft actuator demonstrations both in air and under water, adding to the versatility and programmability of light-driven shape-changing LCEs.

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.

Reconfigurable Visible Light-Driven Liquid Crystalline Network Showing Off-Equilibrium Motions Enabled by Mesogen-Grafted Donor-Acceptor Stenhouse Adducts

Liquid crystalline network (LCN)-based soft actuators have opened up great opportunities to fabricate emerging and intriguing smart materials, serving as potential building blocks for intelligent soft robotics. Endowing LCN actuators with complex responsive behaviors to enhance their intelligence is both challenging and highly demanded. Herein, Donor-Acceptor Stenhouse Adducts (DASAs) molecules with rod-like mesogen and the polymerizable group are judiciously designed and synthesized, which is strong-colored at linear form and de-coloration at cyclic form after visible light. In the colored state, the DASA presents a striking photothermal effect that is capable of driving the motions of LCN film. Upon visible light irradiation, the DASA becomes colorless, making the diminishing photothermal effect. The light-gated switching of the photothermal effect renders the LCN films to be reconfigurable and perform off-equilibrium motions. The varying glass transition temperature of LCN matrix endowing tunable isomerization rates of DASAs and the equilibrium balance of photo- and thermal-isomerization at different temperatures in LCN-P-DASA film mainly guiding the off-equilibrium or stable motions, providing high adjustability of the novel visible light-driven LCN actuators. The multiply modulated LCN-P-DASA film holds great potential in constructing complex visible light-driven soft actuators based on the synergetic effect and interactions of photochemical and photothermal effects.

Emerging paradigms in Alzheimer's therapy

Alzheimer's disease is a neurodegenerative disorder that affects elderly, and its incidence is continuously increasing across the globe. Unfortunately, despite decades of research, a complete cure for Alzheimer's disease continues to elude us. The current medications are mainly symptomatic and slow the disease progression but do not result in reversal of all disease pathologies. The growing body of knowledge on the factors responsible for the onset and progression of the disease has resulted in the identification of new targets that could be targeted for treatment of Alzheimer's disease. This has opened new vistas for treatment of Alzheimer's disease that have moved away from chemotherapeutic agents modulating a single target to biologics and combinations that acted on multiple targets thereby offering better therapeutic outcomes. This review discusses the emerging directions in therapeutic interventions against Alzheimer's disease highlighting their merits that promise to change the treatment paradigm and challenges that limit their clinical translation.

Photoactivation of Millimeters Thick Liquid Crystal Elastomers with Broadband Visible Light Using Donor-Acceptor Stenhouse Adducts

Light-responsive liquid crystal elastomers (LCEs) are stimuli-responsive materials that facilitate the conversion of light energy into a mechanical response. In this work, a novel polysiloxane-based LCE with donor-acceptor Stenhouse adduct (DASA) side-chains is synthesized using a late-stage functionalization strategy. It is demonstrated that this approach does not compromise the molecular alignment observed in the traditional Finkelmann method. This easy, single-batch process provides a robust platform to access well-aligned, light-responsive LCE films with thickness ranging from 400 µm to a 14-layer stack that is 5 mm thick. Upon irradiation with low-intensity broadband visible light (100-200 mW cm-2), these systems undergo 2D planar actuation and complete bleaching. Conversely, exposure to higher-intensity visible light induces bending followed by contraction (300 mW cm-2). These processes are repeatable over several cycles. Finally, it is demonstrated how light intensity and the resulting heat generation influences the photothermal stationary state equilibrium of DASA, thereby controlling its photoresponsive properties. This work establishes the groundwork for advancement of LCE-based actuators beyond thin film and UV-light reliant systems.

Artificial Multimodal Neuron with Associative Learning Capabilities: Acquisition, Extinction, and Spontaneous Recovery

Associative multimodal artificial intelligence (AMAI) has gained significant attention across various fields, yet its implementation poses challenges due to the burden on computing and memory resources. To address these challenges, researchers have paid increasing attention to neuromorphic devices based on novel materials and structures, which can implement classical conditioning behaviors with simplified circuitry. Herein, we introduce an artificial multimodal neuron device that shows not only the acquisition behavior but also the extinction and the spontaneous recovery behaviors for the first time. Being composed of an ovonic threshold switch (OTS)-based neuron device, a conductive bridge memristor (CBM)-based synapse device, and a few passive electrical elements, such observed behaviors of this neuron device are explained in terms of the electroforming and the diffusion of metallic ions in the CBM. We believe that the proposed associative learning neuron device will shed light on the way of developing large-scale AMAI systems by providing inspiration to devise an associative learning network with improved energy efficiency.

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.

Intelligent electroactive material systems with self-adaptive mechanical memory and sequential logic

By synthesizing the requisite functionalities of intelligence in an integrated material system, it may become possible to animate otherwise inanimate matter. A significant challenge in this vision is to continually sense, process, and memorize information in a decentralized way. Here, we introduce an approach that enables all such functionalities in a soft mechanical material system. By integrating nonvolatile memory with continuous processing, we develop a sequential logic-based material design framework. Soft, conductive networks interconnect with embedded electroactive actuators to enable self-adaptive behavior that facilitates autonomous toggling and counting. The design principles are scaled in processing complexity and memory capacity to develop a model 8-bit mechanical material that can solve linear algebraic equations based on analog mechanical inputs. The resulting material system operates continually to monitor the current mechanical configuration and to autonomously search for solutions within a desired error. The methods created in this work are a foundation for future synthetic general intelligence that can empower materials to autonomously react to diverse stimuli in their environment.

Dynamic Shape Change of Liquid Crystal Polymer Based on An Order-Order Phase Transition

Liquid crystal actuators conventionally undergo shape changes across an order-disorder phase transition between liquid crystal (LC) and isotropic phases. In this study, we introduce an innovative Liquid Crystal Polymer (LCP) actuator harnessing an order-order LC phase transition mechanism. The LCP film is easily stretchable within the LC phase, facilitated by the π-π stacking of phenyl groups serving as robust physical crosslinking points, and thereby transforms to a stable monodomain structure. The resultant monodomain LCP actuator shows a distinctive reversible dynamic shape change, exhibiting extension followed by contraction along the LC director on cooling. The extension is propelled by the reversible smectic C to smectic A phase transition, and the contraction is attributed to the re-entry to the smectic C phase from smectic A phase. Thermal annealing temperature determines this peculiar dynamic shape change, which occurs during both heating and cooling processes. This pivotal attribute finds manifestation in gripper and flower-shaped actuators, adeptly executing grabbing and releasing as well as blooming and closure motions within a single thermal stimulation. In essence, our study introduces an innovative approach to the realm of LCP actuators, ushering in a new avenue for the design and fabrication of versatile and dynamically responsive LCP actuators.

Autonomous hydrogel locomotion regulated by light and electric fields

Autonomous robotic functions in materials beyond simple stimulus-response actuation require the development of functional soft matter that can complete well-organized tasks without step-by-step control. We report the design of photo- and electroactivated hydrogels that can capture and deliver cargo, avoid obstacles, and return without external, stepwise control. By incorporating two spiropyran monomers with different chemical substituents in the hydrogel, we created chemically random networks that enabled photoregulated charge reversal and autonomous behaviors under a constant electric field. In addition, using perturbations in the electric field induced by a dielectric inhomogeneity, the hydrogel could be attracted to high dielectric constant materials and autonomously bypasses the low dielectric constant materials under the guidance of the electric field vector. The photo- and electroactive hydrogels investigated here can autonomously perform tasks using constant external stimuli, an encouraging observation for the potential development of molecularly designed intelligent robotic materials.

Perspiring Soft Robotics Skin Constituted by Dynamic Polarity-Switching Porous Liquid Crystal Membrane

Secretion of functional fluids is essential for affecting surface properties in ecosystems. The existing polymer membranes that mimic human skin functions are limited to secreting, either apolar or polar, liquid. However, the development of membranes that grant exchange liquid with different polarities remains a grand challenge. This process is prohibited by the mismatch of the polarity between the carrier polymer and the loaded liquid. To conquer this limitation, an innovative strategy is reported to dynamically switch the polarity of the porous membrane, thereby empowering the exchange of apolar liquid with polar liquid and vice versa. This approach incorporates a benzoic acid derivative into the original apolar polymer network. The benzoic acid dimerizes and forms hydrogen bonds, which supports the molecular alignment, but can be broken into the ionic state when subjected to alkaline treatment, changing the polarity of themembrane. Consequently, the apolar liquid can be replaced with a more polar one. This polar liquid is ejected upon safe-dose UV illumination from the membrane. Reabsorption occurs on demand by illumination of visible light or when left in contact with the membrane, spontaneously in the dark. Based on this, the consumed membrane is replenished with the same or different exchanging liquid.

Polymer-dispersed liquid crystal elastomers as moldable shape-programmable material

The current development of soft shape-memory materials often results in materials that are typically limited to the synthesis of thin-walled specimens and usually rely on complex, low-yield manufacturing techniques to fabricate macro-sized, solid three-dimensional objects. However, such geometrical limitations and slow production rates can significantly hinder their practical implementation. In this work, we demonstrate a shape-memory composite material that can be effortlessly molded into arbitrary shapes or sizes. The composite material is made from main-chain liquid crystal elastomer (MC-LCE) microparticles dispersed in a silicone polymer matrix. Shape-programmability is achieved via low-temperature induced glassiness and hardening of MC-LCE inclusions, which effectively freezes-in any mechanically instilled deformations. Once thermally reset, the composite returns to its initial shape and can be shape-programmed again. Magnetically aligning MC-LCE microparticles prior to curing allows the shape-programmed artefacts to be additionally thermomechanically functionalized. Therefore, our material enables efficient morphing among the virgin, thermally-programmed, and thermomechanically-controlled shapes.

Shape Morphing by Topological Patterns and Profiles in Laser-Cut Liquid Crystal Elastomer Kirigami

Programming shape changes in soft materials requires precise control of the directionality and magnitude of their mechanical response. Among ordered soft materials, liquid crystal elastomers (LCEs) exhibit remarkable and programmable shape shifting when their molecular order changes. In this work, we synthesized, remotely programmed, and modeled reversible and complex morphing in monolithic LCE kirigami encoded with predesigned topological patterns in its microstructure. We obtained a rich variety of out-of-plane shape transformations, including auxetic structures and undulating morphologies, by combining different topological microstructures and kirigami geometries. The spatiotemporal shape-shifting behaviors are well recapitulated by elastodynamics simulations, revealing that the complex shape changes arise from integrating the custom-cut geometry with local director profiles defined by topological defects inscribed in the material. Different functionalities, such as a bioinspired fluttering butterfly, a flower bud, dual-rotation light mills, and dual-mode locomotion, are further realized. Our proposed LCE kirigami with topological patterns opens opportunities for the future development of multifunctional devices for soft robotics, flexible electronics, and biomedicine.

Neuromorphic Liquids, Colloids, and Gels: A Review

Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses would make an ideal core component for flexible liquid circuits. This is due to their unbeatable features such as flexibility, reconfiguration, fault tolerance. To mimic synaptic functions in fluids we need to imitate dynamics and complexity similar to those that occurring in living systems. Mimicking ionic movements are considered as the simplest platform for implementation of neuromorphic in material computing systems. We overview a series of experimental laboratory prototypes where neuromorphic systems are implemented in liquids, colloids and gels.

Stiff Shape Memory Polymers for High-Resolution Reconfigurable Nanophotonics

Reconfigurable metamaterials require constituent nanostructures to demonstrate switching of shapes with external stimuli. Yet, a longstanding challenge is in overcoming stiction caused by van der Waals forces in the deformed configuration, which impedes shape recovery. Here, we introduce stiff shape memory polymers. This designer material has a storage modulus of ∼5.2 GPa at room temperature and ∼90 MPa in the rubbery state at 150 °C, 1 order of magnitude higher than those in previous reports. Nanopillars with diameters of ∼400 nm and an aspect ratio as high as ∼10 were printed by two-photon lithography. Experimentally, we observe shape recovery as collapsed and touching structures overcome stiction to stand back up. We develop a theoretical model to explain the recoverability of these sub-micrometer structures. Reconfigurable structural color prints with a resolution of 21150 dots per inch and holograms are demonstrated, indicating potential applications of the stiff shape memory polymers in high-resolution reconfigurable nanophotonics.

Multicomponent and multifunctional integrated miniature soft robots

Miniature soft robots with elaborate structures and programmable physical properties could conduct micromanipulation with high precision as well as access confined and tortuous spaces, which promise benefits in medical tasks and environmental monitoring. To improve the functionalities and adaptability of miniature soft robots, a variety of integrated design and fabrication strategies have been proposed for the development of miniaturized soft robotic systems integrated with multicomponents and multifunctionalities. Combining the latest advancement in fabrication technologies, intelligent materials and active control methods enable these integrated robotic systems to adapt to increasingly complex application scenarios including precision medicine, intelligent electronics, and environmental and proprioceptive sensing. Herein, this review delivers an overview of various integration strategies applicable for miniature soft robotic systems, including semiconductor and microelectronic techniques, modular assembly based on self-healing and welding, modular assembly based on bonding agents, laser machining techniques, template assisted methods with modular material design, and 3D printing techniques. Emerging applications of the integrated miniature soft robots and perspectives for the future design of small-scale intelligent robots are discussed.

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.

Electrically driven liquid crystal network actuators

Soft actuators based on liquid crystal networks (LCNs) have aroused great scientific interest for use as stimuli-controlled shape-changing and moving components for robotic devices due to their fast, large, programmable and solvent-free actuation responses. Recently, various LCN actuators have been implemented in soft robotics using stimulus sources such as heat, light, humidity and chemical reactions. Among them, electrically driven LCN actuators allow easy modulation and programming of the input electrical signals (amplitude, phase, and frequency) as well as stimulation throughout the volume, rendering them promising actuators for practical applications. Herein, the progress of electrically driven LCN actuators regarding their construction, actuation mechanisms, actuation performance, actuation programmability and the design strategies for intelligent systems is elucidated. We also discuss new robotic functions and advanced actuation control. Finally, an outlook is provided, highlighting the research challenges faced with this type of actuator.

Bio-Inspired 4D Printing of Dynamic Spider Silks

Spider silks exhibit excellent mechanical properties and have promising application prospects in engineering fields. Because natural spider silk fibers cannot be manufactured on a large scale, researchers have attempted to fabricate bio-inspired spider silks. However, the fabrication of bio-inspired spider silks with dynamically tunable mechanical properties and stimulation–response characteristics remains a challenge. Herein, the 4D printing of shape memory polyurethane is employed to produce dynamic bio-inspired spider silks. The bio-inspired spider silks have two types of energy-absorbing units that can be adjusted, one by means of 4D printing with predefined nodes, and the other through different stimulation methods to make the bio-inspired spider silks contract and undergo spiral deformation. The shape morphing behaviors of bio-inspired spider silks are programmed via pre-stress assemblies enabled by 4D printing. The energy-absorbing units of bio-inspired spider silks can be dynamically adjusted owing to stress release generated with the stimuli of temperature or humidity. Therefore, the mechanical properties of bio-inspired spider silks can be controlled to change dynamically. This can further help in developing applications of bio-inspired spider silks in engineering fields with dynamic changes of environment.

Design, Regulation, and Applications of Soft Actuators Based on Liquid-Crystalline Polymers and Their Composites

Soft actuators designed from stimuli-responsive polymers often possess a certain amount of bionic functionality because of their versatile deformation. Liquid-crystalline polymers (LCPs) and their composites are among the most fascinating materials for soft actuators due to their great advantages of flexible structure design and easy regulation. In this Spotlight on Applications, we mainly focus on our group's latest research progress in soft actuators based on LCPs and their composites. Some representative research findings from other groups are also included for a better understanding of this research field. Above all, the essential principles for the responsive behavior and reconfigurable performance of the soft actuators are discussed, from the perspective of material morphology and structure design. Further on, we analyze recent work on how to precisely regulate the responsive modes and quantify the operating parameters of soft actuators. Finally, some application examples are given to demonstrate well-designed soft actuators with different functions under varied working environments, which is expected to provide inspiration for future research in developing more intelligent and multifunctional integrated soft actuators.

Patterned crystal growth and heat wave generation in hydrogels

The crystallization of metastable liquid phase change materials releases stored energy as latent heat upon nucleation and may therefore provide a triggerable means of activating downstream processes that respond to changes in temperature. In this work, we describe a strategy for controlling the fast, exothermic crystallization of sodium acetate from a metastable aqueous solution into trihydrate crystals within a polyacrylamide hydrogel whose polymerization state has been patterned using photomasks. A comprehensive experimental study of crystal shapes, crystal growth front velocities and evolving thermal profiles showed that rapid growth of long needle-like crystals through unpolymerized solutions produced peak temperatures of up to 45˚C, while slower-crystallizing polymerized solutions produced polycrystalline composites and peaked at 30˚C due to lower rates of heat release relative to dissipation in these regions. This temperature difference in the propagating heat waves, which we describe using a proposed analytical model, enables the use of this strategy to selectively activate thermoresponsive processes in predefined areas.

The crystallization of metastable liquid phase change materials releases stored energy upon nucleation. Here, the authors demonstrate area-selective activation of thermoresponsive processes by exothermic crystallization of sodium acetate into trihydrate crystals within a patterned polyacrylamide hydrogel.

4D Printing of Liquid Crystals: What's Right for Me?

Recent years have seen major advances in the developments of both additive manufacturing concepts and responsive materials. When combined as 4D printing, the process can lead to functional materials and devices for use in health, energy generation, sensing, and soft robots. Among responsive materials, liquid crystals, which can deliver programmed, reversible, rapid responses in both air and underwater, are a prime contender for additive manufacturing, given their ease of use and adaptability to many different applications. In this paper, selected works are compared and analyzed to come to a didactical overview of the liquid crystal-additive manufacturing junction. Reading from front to back gives the reader a comprehensive understanding of the options and challenges in the field, while researchers already experienced in either liquid crystals or additive manufacturing are encouraged to scan through the text to see how they can incorporate additive manufacturing or liquid crystals into their own work. The educational text is closed with proposals for future research in this crossover field.

Liquid Crystals: Versatile Self-Organized Smart Soft Materials

Smart soft materials are envisioned to be the building blocks of the next generation of advanced devices and digitally augmented technologies. In this context, liquid crystals (LCs) owing to their responsive and adaptive attributes could serve as promising smart soft materials. LCs played a critical role in revolutionizing the information display industry in the 20th century. However, in the turn of the 21st century, numerous beyond-display applications of LCs have been demonstrated, which elegantly exploit their controllable stimuli-responsive and adaptive characteristics. For these applications, new LC materials have been rationally designed and developed. In this Review, we present the recent developments in light driven chiral LCs, i.e., cholesteric and blue phases, LC based smart windows that control the entrance of heat and light from outdoor to the interior of buildings and built environments depending on the weather conditions, LC elastomers for bioinspired, biological, and actuator applications, LC based biosensors for detection of proteins, nucleic acids, and viruses, LC based porous membranes for the separation of ions, molecules, and microbes, living LCs, and LCs under macro- and nanoscopic confinement. The Review concludes with a summary and perspectives on the challenges and opportunities for LCs as smart soft materials. This Review is anticipated to stimulate eclectic ideas toward the implementation of the nature's delicate phase of matter in future generations of smart and augmented devices and beyond.

Stimulus-driven liquid metal and liquid crystal network actuators for programmable soft robotics

Sophisticated soft matter engineering has been endorsed as an emerging paradigm for developing untethered soft robots with built-in electronic functions and biomimetic adaptation capacities. However, the integration of flexible electronic components into soft robotic actuators is challenging due to strain mismatch and material incompatibilities. Herein, we report a general strategy to integrate electrically conductive liquid metals (LMs) and shape-morphing liquid crystal networks (LCNs) towards multifunctional and programmable soft robotics. A unique colloidal LM ink with superior adhesion and photothermal conversion efficiency was judiciously designed and fabricated by ultrasonicating LMs and miniature carboxylated gold nanorods (MiniGNR-COOH) in an aqueous suspension of biological bacterial cellulose. The designed nanocellulose-based colloidal LM ink is used for shape-deformable and electrically conductive LM-LCN soft robots that can be electro- and photo-thermally actuated. As proof-of-concept demonstrations, we present a light-fueled soft oscillator, an inchworm-inspired soft crawler and programmable robotic Shadow Play exhibiting multifunctional controllability. The strategy disclosed here could open up a new technological arena for advanced multifunctional soft materials with potential utility in bioinspired soft machines, integrated soft electronics, human-computer interaction and beyond.

Reversible Underwater Adhesion for Soft Robotic Feet by Leveraging Electrochemically Tunable Liquid Metal Interfaces

Soft crawling robots have potential applications for surveillance, rescue, and detection in complex environments. Despite this, most existing soft crawling robots either use nonadjustable feet to passively induce asymmetry in friction to actuate or are only capable of moving on surfaces with specific designs. Thus, robots often lack the ability to move along arbitrary directions in a two-dimensional (2D) plane or in unpredictable environments such as wet surfaces. Here, leveraging the electrochemically tunable interfaces of liquid metal, we report the development of liquid metal smart feet (LMSF) that enable electrical control of friction for achieving versatile actuation of prismatic crawling robots on wet slippery surfaces. The functionality of the LMSF is examined on crawling robots with soft or rigid actuators. Parameters that affect the performance of the LMSF are investigated. The robots with the LMSF prove capable of actuating across different surfaces in various solutions. Demonstration of 2D locomotion of crawling robots along arbitrary directions validates the versatility and reliability of the LMSF, suggesting broad utility in the development of advanced soft robotic systems.

Smart Actuators Based on External Stimulus Response

Smart actuators refer to integrated devices that are composed of smart and artificial materials, and can provide actuation and dampening capabilities in response to single/multi external stimuli (such as light, heat, magnetism, electricity, humidity, and chemical reactions). Due to their capability of dynamically sensing and interaction with complex surroundings, smart actuators have attracted increasing attention in different application fields, such as artificial muscles, smart textiles, smart sensors, and soft robots. Among these intelligent material, functional hydrogels with fiber structure are of great value in the manufacture of smart actuators. In this review, we summarized the recent advances in stimuli-responsive actuators based on functional materials. We emphasized the important role of functional nano-material-based additives in the preparation of the stimulus response materials, then analyzed the driving response medium, the preparation method, and the performance of different stimuli responses in detail. In addition, some challenges and future prospects of smart actuators are reported.

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.

Triple-Shape-Memory Soft Actuators from an Interpenetrating Network of Hybrid Liquid Crystals

In this work, the formation of triple-shape-memory liquid crystalline-interpenetrating polymer network (LC-IPN) actuators based on a hybrid acrylate-oxetane LC mixture is reported. Orthogonal polymerization of the oxetane and acrylate liquid crystals creates polymer films with two distinct glass-transition temperatures. The use of these two transitions for one-way triple-shape-memory actuation and two-way bending actuation with a broad temperature window for actuation is demonstrated. Our results combine shape memory polymers with liquid crystal-based soft actuators having advanced stimuli-responsive properties.

Translating 2D Director Profile to 3D Topography in a Liquid Crystal Polymer

Morphological properties of surfaces play a key role in natural and man-made objects. The development of robust methods to fabricate micro/nano surface structures has been a long pursuit. Herein, an approach based on molecular self-assembling of liquid crystal polymers (LCPs) is presented to directly translate 2D molecular director profiles obtained by a photoalignment procedure into 3D topographies, without involving further multi-step lithographic processes. The principle of surface deformation from a flat morphology into complex topographies is based on the coupling between electrostatic interactions and the anisotropic flow in LCPs. When activated by an electric field, the LCP melts and is driven by electrohydrodynamic instabilities to connect the electrode plates of a capacitor, inducing topographies governed by the director profile of the LCP. Upon switching off the electric field, the formed structures vitrify as the temperature decreases below the glass transition. When heated, the process is reversible as the formed topographies disappear. By pre-programming the molecular director a variety of structures could be made with increasing complexity. The height, pitch, and the aspect ratio of the textures are further regulated by the conditions of the applied electric field. The proposed approach will open new opportunities for optical and electrical applications.

4D-Printable Liquid Metal-Liquid Crystal Elastomer Composites

Soft actuators that undergo programmable shape change in response to a stimulus are enabling components of future soft robots and other soft machines. Strategies to power these actuators often require the incorporation of rigid, electrically conductive materials into the soft actuator, thus limiting the compliance and shape change of the material. In this study, we develop a 4D-printable composite composed of liquid crystal elastomer (LCE) matrix with dispersed droplets of eutectic gallium indium alloy (EGaIn). Using deformable EGaIn droplets in place of rigid conductive fillers preserves the compliance and shape-morphing properties of the LCE. The process enables 4D-printed LCE actuators capable of photothermal and electrothermal actuation. At low liquid metal (LM) concentrations (71 wt %), the composite actuator exhibits a photothermal response upon irradiation of near-IR light. Printed actuators with a twisted nematic configuration are capable of bending angles of 150° at 800 mW cm^-2. At higher LM concentrations (88 wt %), the embedded LM droplets can form percolating networks that conduct electricity and enable electrical Joule heating of the LCE. Actuation strain ranging from 5 to 12% is controlled by the amount of electrical power that is delivered to the composite. We also introduce a method for multimaterial printing of monolithic structures where the LM filler loading is spatially varied. These multifunctional materials exhibit innate responsivity where the actuator behaves as an electrical switch and can report one of two states (on/off). These multiresponsive, 4D-printable composites enable multifunctional, mechanically active structures that can be powered with IR light or low DC voltages.

Desynchronized liquid crystalline network actuators with deformation reversal capability

Liquid crystalline network (LCN) actuator normally deforms upon thermally or optically induced order-disorder phase transition, switching once between two shapes (shape 1 in LC phase and shape 2 in isotropic state) for each stimulation on/off cycle. Herein, we report an LCN actuator that deforms from shape 1 to shape 2 and then reverses the deformation direction to form shape 3 on heating or under light only, thus completing the shape switch twice for one stimulation on/off cycle. The deformation reversal capability is obtained with a monolithic LCN actuator whose two sides are made to start deforming at different temperatures and exerting different reversible strains, by means of asymmetrical crosslinking and/or asymmetrical stretching. This desynchronized actuation strategy offers possibilities in developing light-fueled LCN soft robots. In particular, the multi-stage bidirectional shape change enables multimodal, light-driven locomotion from the same LCN actuator by simply varying the light on/off times.

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.