Non-equilibrium-Growing Aesthetic Ionic Skin for Fingertip-Like Strain-Undisturbed Tactile Sensation and Texture Recognition

Multifunctional Self-Powered Sensors Integrated on a Robot Hand for Detecting Temperature-Pressure Stimuli and Recognizing Objects

Tactile sensing, especially pressure and temperature recognition, is crucial for both humans and robots in identifying objects. The general solutions, which use piezoresistive, capacitive, and thermal resistance effects, are usually subject to single-mode sensing and an energy supply. Here, we propose a multimode self-powered sensor. The sensor can respond to pressure and temperature stimuli using triboelectric and thermoelectric effects. Furthermore, we developed a sensing system comprising sensors, a deep learning block, and a smart board. The deep learning model can fuse features of triboelectric and thermoelectric signals, enabling a high accuracy of 99.8% in recognizing ten objects. This method may provide the future design of self-powered sensors for object recognition in robotics.

Jellyfish-Inspired Polyurea Ionogel with Mechanical Robustness, Self-Healing, and Fluorescence Enabled by Hyperbranched Cluster Aggregates

Ionogels are promising for soft iontronics, with their network structure playing a pivotal role in determining their performance and potential applications. However, simultaneously achieving mechanical toughness, low hysteresis, self-healing, and fluorescence using existing network structures is challenging. Drawing inspiration from jellyfish, we propose a novel hierarchical crosslinking network structure design for in situ formation of hyperbranched cluster aggregates (HCA) to fabricate polyurea ionogels to overcome these challenges. Leveraging the disparate reactivity of isocyanate groups, we induce the in situ formation of HCA through competing reactions, enhancing toughness and imparting the clustering-triggered emission of ionogel. This synergy between supramolecular interactions in the network and plasticizing effect in ionic liquid leads to reduced hysteresis of the ionogel. Furthermore, the incorporation of NCO-terminated prepolymer with dynamic oxime-urethane bonds (NPU) enables self-healing and enhances stretchability. Our investigations highlight the significant influence of HCA on ionogel performance, showcasing mechanical robustness including high strength (3.5 MPa), exceptional toughness (5.5 MJ m-3), resistance to puncture, and low hysteresis, self-healing, as well as fluorescence, surpassing conventional dynamic crosslinking approaches. This network design strategy is versatile and can meet the various demands of flexible electronics applications.

Flexible and wearable electronic systems based on 2D hydrogel composites

Flexible electronics is a rapidly developing field of study, which integrates many other fields, including materials science, biology, chemistry, physics, and electrical engineering. Despite their vast potential, the widespread utilization of flexible electronics is hindered by several constraints, including elevated Young's modulus, inadequate biocompatibility, and diminished responsiveness. Therefore, it is necessary to develop innovative materials aimed at overcoming these hurdles and catalysing their practical implementation. In these materials, hydrogels are particularly promising owing to their three-dimensional crosslinked hydrated polymer networks and exceptional properties, positioning them as leading candidates for the development of future flexible electronics.

Pushing Pressure Detection Sensitivity to New Limits by Modulus-Tunable Mechanism

Only microstructures are used to improve the sensitivity of iontronic pressure sensors. By modulating the compressive modulus, a breakthrough in the sensitivity of the iontronic pressure sensor is achieved. Furthermore, it allows for programmatic tailoring of sensor performance according to the requirements of different applications. Such a new strategy pushes the sensitivity up to a record-high of 25 548.24 kPa-1 and expands the linear pressure range from 15 to 127 kPa. Additionally, the sensor demonstrates excellent mechanical stability over 10 000 compression-release cycles. Based on this, a well-controlled robotic hand that precisely tracks the pressure behavior inside a balloon to autonomously regulate the gripping angle is developed. This paves the way for the application of iontronic pressure sensors in precise sensing scenarios.

Zero-Biased Bionic Fingertip E-Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness

Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping system simplicity for lack of multimodal sensing capability in a single sensor. Two kinds of tactile sensors, transient voltage artificial neuron (TVAN) and sustained potential artificial neuron (SPAN), featuring self-generated zero-biased signals are developed to realize synergistic sensing of multimodal information (vibration, material, texture, pressure, and temperature) in a single device instead of complex sensor arrays. Simultaneously, machine learning with feature fusion is applied to fully decode their output information and compensate for the inevitable instability of applied force, speed, etc, in real applications. Integrating TVAN and SPAN, the formed E-Skin achieves holistic touch awareness in only a single unit. It can thoroughly perceive an object through a simple touch without strictly controlled testing conditions, realize the capability to discern surface roughness from 0.8 to 1600 µm, hardness from 6HA to 85HD, and correctly distinguish 16 objects with temperature variance from 0 to 80 °C. The E-skin also features a simple and scalable fabrication process, which can be integrated into various devices for broad applications.

Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm

Post-earthquake rescue missions are full of challenges due to the unstable structure of ruins and successive aftershocks. Most of the current rescue robots lack the ability to interact with environments, leading to low rescue efficiency. The multimodal electronic skin (e-skin) proposed not only reproduces the pressure, temperature, and humidity sensing capabilities of natural skin but also develops sensing functions beyond it-perceiving object proximity and NO2 gas. Its multilayer stacked structure based on Ecoflex and organohydrogel endows the e-skin with mechanical properties similar to natural skin. Rescue robots integrated with multimodal e-skin and artificial intelligence (AI) algorithms show strong environmental perception capabilities and can accurately distinguish objects and identify human limbs through grasping, laying the foundation for automated post-earthquake rescue. Besides, the combination of e-skin and NO2 wireless alarm circuits allows robots to sense toxic gases in the environment in real time, thereby adopting appropriate measures to protect trapped people from the toxic environment. Multimodal e-skin powered by AI algorithms and hardware circuits exhibits powerful environmental perception and information processing capabilities, which, as an interface for interaction with the physical world, dramatically expands intelligent robots' application scenarios.

Quantitative softness and texture bimodal haptic sensors for robotic clinical feature identification and intelligent picking

Replicating human somatosensory networks in robots is crucial for dexterous manipulation, ensuring the appropriate grasping force for objects of varying softness and textures. Despite advances in artificial haptic sensing for object recognition, accurately quantifying haptic perceptions to discern softness and texture remains challenging. Here, we report a methodology that uses a bimodal haptic sensor to capture multidimensional static and dynamic stimuli, allowing for the simultaneous quantification of softness and texture features. This method demonstrates synergistic measurements of elastic and frictional coefficients, thereby providing a universal strategy for acquiring the adaptive gripping force necessary for scarless, antislippage interaction with delicate objects. Equipped with this sensor, a robotic manipulator identifies porcine mucosal features with 98.44% accuracy and stably grasps visually indistinguishable mature white strawberries, enabling reliable tissue palpation and intelligent picking. The design concept and comprehensive guidelines presented would provide insights into haptic sensor development, promising benefits for robotics.

Robust Gradient Hydrogel-Loaded Nanofiber Fleshy Artificial Skin Via A Coupled Microfluidic Electrospinning-Reactive Coating Strategy

Skin regeneration attracts tremendous interest due to the important role of skin for human protection and beauty. Thus, methods allowing artificial skin to be carried out in a controllable fashion are potentially important for wound healing, which involves an intersection of materials, medicine, biology, and other disciplines. Herein, aiming at a new general methodology for fleshy materials, a new hydrogel-loaded hydrophobic-hydrophilic nanofiber fleshy artificial skin is designed and fabricated. The gradient hydrogel-loaded nanofiber artificial skin integrates both advantages of nanofiber and hydrogel, exhibiting fleshy feature (comparability to real skin in terms of appearance, texture, and function), excellent air permeability, compatibility, and good mechanical and antibacterial property. Interestingly, the efficient transport channels are formed throughout the hydrogel-loaded nanofiber structure, which is beneficial for water absorption and transfer. These advantages enable the establishment of a moist and favorable microenvironment; thus, greatly accelerating wound healing process. This work couples microfluidic electrospinning with reactive coating technique, which is in favor of material design and fabrication with controllable and uniform structures. The hydrogel-loaded nanofiber fleshy artificial skin shows comparability to real skin in terms of beauty, texture, and function, which would definitely provide new opportunities for the further optimization and upgrading of artificial skin.

Wearable and Recyclable Water-Toleration Sensor Derived from Lipoic Acid

Flexible wearable sensors recently have made significant progress in human motion detection and health monitoring. However, most sensors still face challenges in terms of single detection targets, single application environments, and non-recyclability. Lipoic acid (LA) shows a great application prospect in soft materials due to its unique properties. Herein, ionic conducting elastomers (ICEs) based on polymerizable deep eutectic solvents consisting of LA and choline chloride are prepared. In addition to the good mechanical strength, high transparency, ionic conductivity, and self-healing efficiency, the ICEs exhibit swelling-strengthening behavior and enhanced adhesion strength in underwater environments due to the moisture-induced association of poly(LA) hydrophobic chains, thus making it possible for underwater sensing applications, such as underwater communication. As a strain sensor, it exhibits highly sensitive strain response with repeatability and durability, enabling the monitoring of both large and fine human motions, including joint movements, facial expressions, and pulse waves. Furthermore, due to the enhancement of ion mobility at higher temperatures, it also possesses excellent temperature-sensing performance. Notably, the ICEs can be fully recycled and reused as a new strain/temperature sensor through heating. This study provides a novel strategy for enhancing the mechanical strength of poly(LA) and the fabrication of multifunctional sensors.

3D Printing of Thermo-Mechano-Responsive Photoluminescent Noncovalent Cross-Linked Ionogels with High-Stretchability and Ultralow-Hysteresis for Wearable Ionotronics and Anti-Counterfeiting

Ionogel has recently emerged as a promising ionotronic material due to its good ionic conductivity and flexibility. However, low stretchability and significant hysteresis under long-term loading limit their mechanical stability and repeatability. Developing ultralow hysteresis ionogels with high stretchability is of great significance. Here, a simple and effective strategy is developed to fabricate highly stretchable and ultralow-hysteresis noncovalent cross-linked ionogels based on phase separation by 3D printing of 2-hydroxypropyl acrylate (HPA) in 1-butyl-3-methylimidazolium tetrafluoroborate (BMIMBF4). Ingeniously, the sea-island structure of the physically cross-linked network constructed by the smaller nanodomains and larger nanodomain clusters significantly minimizes the energy dissipation, endowing these ionogels with remarkable stretchability (>1000%), ultra-low hysteresis (as low as 0.2%), excellent temperature tolerance (-33-317 °C), extraordinary ionic conductivity (up to 1.7 mS cm-1), and outstanding durability (5000 cycles). Moreover, due to the formation of nanophase separation and cross-linking structure, the as-prepared ionogels exhibit unique thermochromic and multiple photoluminescent properties, which can synergistically be applied for anti-counterfeiting and encrypting. Importantly, flexible thermo-mechano-multimodal visual ionotronic sensors for strain and temperature sensing with highly stable and reproducible electrical response over 20 000 cycles are fabricated, showing synergistically optical and electrical output performances.

High-Sensitive Spatiotemporal Distribution Imaging of Compression Stresses Based on Time-Evolutional Responsiveness

Mechanoresponsive materials have been studied to visualize and measure stresses in various fields. However, the high-sensitive and spatiotemporal imaging remain a challenging issue. In particular, the time evolutional responsiveness is not easily integrated in mechanoresponsive materials. In the present study, high-sensitive spatiotemporal imaging of weak compression stresses is achieved by time-evolutional controlled diffusion processes using conjugated polymer, capsule, and sponge. Stimuli-responsive polydiacetylene (PDA) is coated inside a sponge. A mechanoresponsive capsule is set on the top face of the sponge. When compression stresses in the range of 6.67-533 kPa are applied to the device, the blue color of PDA is changed to red by the diffusion of the interior liquid containing a guest polymer flowed out of the disrupted capsule. The applied strength (F/N), time (t/s), and impulse (F·t/N s) are visualized and quantified by the red-color intensity. When a guest metal ion is intercalated in the layered structure of PDA to tune the responsivity, the device visualizes the elapsed time (τ/min) after unloading the stresses. PDA, capsule, and sponge play the important roles to achieve the time evolutional responsiveness for the high-sensitive spatiotemporal distribution imaging through the controlled diffusion processes.

A Solid-Liquid Bicontinuous Fiber with Strain-Insensitive Ionic Conduction

Stretchable ionic conductors are crucial for enabling advanced iontronic devices to operate under diverse deformation conditions. However, when employed as interconnects, existing ionic conductors struggle to maintain stable ionic conduction under strain, hindering high-fidelity signal transmission. Here, it is shown that strain-insensitive ionic conduction can be achieved by creating a solid-liquid bicontinuous microstructure. A bicontinuous fiber from polymerization-induced phase separation, which contains a solid elastomer phase interpenetrated by a liquid ion-conducting phase, is fabricated. The spontaneous partitioning of dissolved salts leads to the formation of a robust self-wrinkled interface, fostering the development of highly tortuous ionic channels. Upon stretch, these meandering ionic channels are straightened, effectively enhancing ionic conductivity to counteract the strain effect. Remarkably, the fiber retains highly stable ionic conduction till fracture, with only 7% resistance increase at 200% strain. This approach presents a promising avenue for designing durable ionic cables capable of signal transmission with minimal strain-induced distortion.

Facile Multiple Graded Wrinkle Construction Strategy for Vastly Boosting the Sensing Performance of Ionic Skins

The construction of surface microstructures (e.g., micropyramids and wrinkles) has been proven as the most effective means to boost the sensitivity of ionic skins (I-skins). However, the single-scale micronano patterns constructed by the common fabrication strategy generally lead to a limited pressure-response range. Here, a convenient repeated stretching/coordinating/releasing strategy is developed to controllably construct multiple graded wrinkles on the polyelectrolyte hydrogel-based I-skins for increasing their sensitivity over a broad pressure range. We find that the small wrinkles allow for high sensitivity yet small pressure detection range, while the large wrinkles can reduce structural stiffening to generate large pressure-response range but incur limited sensitivity. The multiple graded wrinkles can combine the merits of both the small and large wrinkles to simultaneously improve the sensitivity and broaden the pressure-response range. In particular, the sensing performance of multiple-wrinkle-based I-skins substantially outperforms the superposition of the sensing performance of different single-wrinkle-based I-skins. As a proof of concept, the triple-wrinkle-based I-skins can provide an extremely high sensitivity of 17,309 kPa-1 and an ultrawide pressure detection range of 0.38 Pa to 372 kPa. The approach and insight contribute to the future development of I-skins with a broader pressure-response range and higher sensitivity.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

Skin-Inspired, Highly Sensitive, Broad-Range-Response and Ultra-Strong Gradient Ionogels Prepared by Electron Beam Irradiation

Skin, characterized by its distinctive gradient structure and interwoven fibers, possesses remarkable mechanical properties and highly sensitive attributes, enabling it to detect an extensive range of stimuli. Inspired by these inherent qualities, a pioneering approach involving the crosslinking of macromolecules through in situ electron beam irradiation (EBI) is proposed to fabricate gradient ionogels. Such a design offers remarkable mechanical properties, including excellent tensile properties (>1000%), exceptional toughness (100 MJ m-3), fatigue resistance, a broad temperature range (-65-200°C), and a distinctive gradient modulus change. Moreover, the ionogel sensor exhibits an ultra-fast response time (60 ms) comparable to skin, an incredibly low detection limit (1 kPa), and an exceptionally wide detection range (1 kPa-1 MPa). The exceptional gradient ionogel material holds tremendous promise for applications in the field of smart sensors, presenting a distinct strategy for fabricating flexible gradient materials.

Anisotropic Liesegang pattern for the nonlinear elastic biomineral-hydrogel complex

The Liesegang pattern is a beautiful natural anisotropic patterning phenomenon observed in rocks and sandstones. This study reveals that the Liesegang pattern can induce nonlinear elasticity. Here, a Liesegang-patterned complex with biomineral-hydrogel repetitive layers is prepared. This Liesegang-patterned complex is obtained only when the biomineralization is performed under the supersaturated conditions. The Liesegang-patterned complex features a nonlinear elastic response, whereas a complex with a single biomineral shell shows a linear behavior, thus demonstrating that the Liesegang pattern is essential in achieving nonlinear elasticity. The stiff biomineral layers have buffered the concentrated energy on behalf of soft hydrogels, thereby exposing the hydrogel components to reduced stress and, in turn, enabling them to perform the elasticity continuously. Moreover, the nonlinear elastic Liesegang-patterned complex exhibits excellent stress relaxation to the external loading, which is the biomechanical characteristic of cartilage. This stress relaxation allows the bundle of fiber-type Liesegang-patterned complex to endure greater deformation.

Bimodal Intelligent Electronic Skin Based on Proximity and Tactile Interaction for Pressure and Configuration Perception

The flexible bimodal e-skin exhibits significant promise for integration into the next iteration of human-computer interactions, owing to the integration of tactile and proximity perception. However, those challenges, such as low tactile sensitivity, complex fabrication processes, and incompatibility with bimodal interactions, have restricted the widespread adoption of bimodal e-skin. Herein, a bimodal capacitive e-skin capable of simultaneous tactile and proximity sensing has been developed. The entire process eliminates intricate fabrication techniques, employing DLP-3D printing for the electrode layers and sacrificial templating for the dielectric layers, conferring high tactile sensitivity (1.672 kPa-1) and rapid response capability (∼30 ms) to the bimodal e-skin. Moreover, exploiting the "fringing electric field" effect inherent in parallel-plate capacitors has facilitated touchless sensing, thereby enabling static distance recognition and dynamic gesture recognition of varying materials. Interestingly, an e-skin sensing array was created to identify the positions and pressure levels of various objects of different masses. Furthermore, with the aid of machine learning techniques, an artificial neural network has been established to possess intelligent object recognition capabilities, facilitating the identification, classification, and training of various object configurations. The advantages of the bimodal e-skin render it highly promising for extensive applications in the field of next-generation human-machine interaction.

Multimodal Sensors Enabled Autonomous Soft Robotic System with Self-Adaptive Manipulation

Human hands are amazingly skilled at recognizing and handling objects of different sizes and shapes. To date, soft robots rarely demonstrate autonomy equivalent to that of humans for fine perception and dexterous operation. Here, an intelligent soft robotic system with autonomous operation and multimodal perception ability is developed by integrating capacitive sensors with triboelectric sensor. With distributed multiple sensors, our robot system can not only sense and memorize multimodal information but also enable an adaptive grasping method for robotic positioning and grasp control, during which the multimodal sensory information can be captured sensitively and fused at feature level for crossmodally recognizing objects, leading to a highly enhanced recognition capability. The proposed system, combining the performance and physical intelligence of biological systems (i.e., self-adaptive behavior and multimodal perception), will greatly advance the integration of soft actuators and robotics in many fields.

Fluorine-Containing Ionogels with Stretchable, Solvent-Resistant, Wide Temperature Tolerance, and Transparent Properties for Ionic Conductors

Stretchable ionogels, as soft ion-conducting materials, have generated significant interest. However, the integration of multiple functions into a single ionogel, including temperature tolerance, self-adhesiveness, and stability in diverse environments, remains a challenge. In this study, a new class of fluorine-containing ionogels was synthesized through photo-initiated copolymerization of fluorinated hexafluorobutyl methacrylate and butyl acrylate in a fluorinated ionic liquid 1-butyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide. The resulting ionogels demonstrate good stretchability with a fracture strain of ~1300%. Owing to the advantages of the fluorinated network and the ionic liquid, the ionogels show excellent stability in air and vacuum, as well as in various solvent media such as water, sodium chloride solution, and hexane. Additionally, the ionogels display impressive wide temperature tolerance, functioning effectively within a wide temperature range from -60 to 350 °C. Moreover, due to their adhesive properties, the ionogels can be easily attached to various substrates, including plastic, rubber, steel, and glass. Sensors made of these ionogels reliably respond to repetitive tensile-release motion and finger bending in both air and underwater. These findings suggest that the developed ionogels hold great promise for application in wearable devices.

Microphase-Separated Elastic and Ultrastretchable Ionogel for Reliable Ionic Skin with Multimodal Sensation

Bioinspired artificial skins integrated with reliable human-machine interfaces and stretchable electronic systems have attracted considerable attention. However, the current design faces difficulties in simultaneously achieving satisfactory skin-like mechanical compliance and self-powered multimodal sensing. Here, this work reports a microphase-separated bicontinuous ionogel which possesses skin-like mechanical properties and mimics the multimodal sensing ability of biological skin by ion-driven stimuli-electricity conversion. The ionogel exhibits excellent elasticity and ionic conductivity, high toughness, and ultrastretchability, as well as a Young's modulus similar to that of human skin. Leveraging the ion-polymer interactions enabled selective ion transport, the ionogel can output pulsing or continuous electrical signals in response to diverse stimuli such as strain, touch pressure, and temperature sensitively, demonstrating a unique self-powered multimodal sensing. Furthermore, the ionogel-based I-skin can concurrently sense different stimuli and decouple the variations of the stimuli from the voltage signals with the assistance of a machine-learning model. The ease of fabrication, wide tunability, self-powered multimodal sensing, and the excellent environmental tolerance of the ionogels demonstrate a new strategy in the development of next-generation soft smart mechano-transduction devices.

High Strength and Toughness Polymeric Triboelectric Materials Enabled by Dense Crystal-Domain Cross-Linking

Lightweight, easily processed, and durable polymeric materials play a crucial role in wearable sensor devices. However, achieving simultaneously high strength and toughness remains a challenge. This study addresses this by utilizing an ion-specific effect to control crystalline domains, enabling the fabrication of a polymeric triboelectric material with tunable mechanical properties. The dense crystal-domain cross-linking enhances energy dissipation, resulting in a material boasting both high tensile strength (58.0 MPa) and toughness (198.8 MJ m-3), alongside a remarkable 416.7% fracture elongation and 545.0 MPa modulus. Leveraging these properties, the material is successfully integrated into wearable self-powered devices, enabling real-time feedback on human joint movement. This work presents a valuable strategy for overcoming the strength-toughness trade-off in polymeric materials, paving the way for their enhanced applicability and broader use in diverse sensing applications.

Triboelectric micro-flexure-sensitive fiber electronics

Developing fiber electronics presents a practical approach for establishing multi-node distributed networks within the human body, particularly concerning triboelectric fibers. However, realizing fiber electronics for monitoring micro-physiological activities remains challenging due to the intrinsic variability and subtle amplitude of physiological signals, which differ among individuals and scenarios. Here, we propose a technical approach based on a dynamic stability model of sheath-core fibers, integrating a micro-flexure-sensitive fiber enabled by nanofiber buckling and an ion conduction mechanism. This scheme enhances the accuracy of the signal transmission process, resulting in improved sensitivity (detectable signal at ultra-low curvature of 0.1 mm-1; flexure factor >21.8% within a bending range of 10°.) and robustness of fiber under micro flexure. In addition, we also developed a scalable manufacturing process and ensured compatibility with modern weaving techniques. By combining precise micro-curvature detection, micro-flexure-sensitive fibers unlock their full potential for various subtle physiological diagnoses, particularly in monitoring fiber upper limb muscle strength for rehabilitation and training.

Dielectric-Enhanced, High-Sensitivity, Wide-Bandwidth, and Moisture-Resistant Noncontact Triboelectric Sensor for Vibration Signal Acquisition

Noncontact triboelectric sensors (TESs) have the potential to enhance self-powered sensing performance by eliminating the need for physical contact. This study demonstrates a strategy to construct noncontact TES that enables self-powered sensing and vibration signal acquisition with high sensitivity and wide bandwidth. The incorporation of carbon nanotubes into nitrocellulose (CNTs/NC) endows the tribopositive layer with larger inner micro/nanocapacitances, consequently augmenting the charge storage capacity. As a result, the contactless sensing performance of CNTs/NC-based TES (CNTs/NC-TES) was enhanced by 146%. Correspondingly, the related theory and working mechanism of noncontact sensing were demonstrated. Furthermore, the CNTs/NC-TES exhibits optimal distance response sensitivity of 57.10 V mm-1, a wide-bandwidth response from 0.1 to 4000 Hz, and relative humidity (RH) stability. This contactless CNTs/NC-TES has the potential for high sensitivity and wide frequency vibration monitoring in a high-RH environment.

An All-Protein Multisensory Highly Bionic Skin

To achieve a highly realistic robot, closely mimicking human skin in terms of materials and functionality is essential. This paper presents an all-protein silk fibroin bionic skin (SFBS) that emulates both fast-adapting (FA) and slow-adapting (SA) receptors. The mechanically different silk film and hydrogel, which exhibited skin-like properties, such as stretchability (>140%), elasticity, low modulus (<10 kPa), biocompatibility, and degradability, were prepared through mesoscopic reconstruction engineering to mimic the epidermis and dermis. Our SFBS, incorporating SA and FA sensors, demonstrated a highly sensitive (1.083 kPa-1) static pressure sensing performance (in vitro and in vivo), showed the ability to sense high-frequency vibrations (50-400 Hz), could discriminate materials and sliding, and could even identify the fine morphological differences between objects. As proof of concept, an SFBS-integrated rehabilitation glove was synthesized, which could help stroke patients regain sensory feedback. In conclusion, this work provides a practical approach for developing skin equivalents, prostheses, and smart robots.

Peeling-Stiffening Self-Adhesive Ionogel with Superhigh Interfacial Toughness

Self-adhesive materials that can directly adhere to diverse solid surfaces are indispensable in modern life and technologies. However, it remains a challenge to develop self-adhesive materials with strong adhesion while maintaining its intrinsic softness for efficient tackiness. Here, a peeling-stiffening self-adhesive ionogel that reconciles the seemingly contradictory properties of softness and strong adhesion is reported. The ionogel contains two ionophilic repeating units with distinct associating affinities, which allows to adaptively wet rough surface in the soft dissipating state for adhering, and to dramatically stiffen to the glassy state upon peeling. The corresponding modulus increases by 117 times driven by strain-rate-induced phase separation, which greatly suppresses crack propagation and results in a super high interfacial toughness of 8046 J m-2 . The self-adhesive ionogel is also transparent, self-healable, recyclable, and can be easily removed by simple moisture treatment. This strategy provides a new way to design high-performance self-adhesive materials for intelligent soft devices.

Skin-Inspired Patterned Hydrogel with Strain-Stiffening Capability for Strain Sensors

Flexible materials with ionic conductivity and stretchability are indispensable in emerging fields of flexible electronic devices as sensing and protecting layers. However, designing robust sensing materials with skin-like compliance remains challenging because of the contradiction between softness and strength. Herein, inspired by the modulus-contrast hierarchical structure of biological skin, we fabricated a biomimetic hydrogel with strain-stiffening capability by embedding the stiff array of poly(acrylic acid) (PAAc) in the soft polyacrylamide (PAAm) hydrogel. The stress distribution in both stiff and soft domains can be regulated by changing the arrangement of patterns, thus improving the mechanical properties of the patterned hydrogel. As expected, the resulting patterned hydrogel showed its nonlinear mechanical properties, which afforded a high strength of 1.20 MPa while maintaining a low initial Young's modulus of 31.0 kPa. Moreover, the array of PAAc enables the patterned hydrogel to possess protonic conductivity in the absence of additional ionic salts, thus endowing the patterned hydrogel with the ability to serve as a strain sensor for monitoring human motion.

Imaging of Accumulated Mechanical Stresses Using Self-Assembled Layered Conjugated Polymer

When mechanical stresses, such as tensile, compressive, and frictional stresses, are applied to objects by various motions, they are accumulated in materials. Conventional mechanoresponsive materials and sensors detect one-time applied stress. However, the accumulated stresses are not visualized or measured in previous works. The present study demonstrated imaging and sensing of not only one-time but also accumulated tensile, compressive, and frictional stresses. Polyurethane (PU) film was combined with 2D layered polydiacetylene (PDA), a stimuli-responsive color-changing polymer. PDA generally exhibits no color changes with the application of tensile and compression stresses because the molecular motion leading to the color change is not induced by such mechanical stresses. Here the versatile mechanoresponsiveness was achieved using a block copolymer guest partially intercalated in the layered PDA. As the interlayer and outerlayer segments interact with PDA and PU, respectively, the applied stresses to the film are transferred from PU to PDA via the block copolymer guest. The color changes of the film imaged and quantified the accumulated work depending on the number and strength of the applied multiple stresses such as tensile, compressive, and frictional stresses. The design strategy of materials and methodology of sensing can be applied to the development of new sensors for accumulated mechanical stresses in a wide range of length and strength scales.

Knitting from Nature: Self-Sensing Soft Robotics Enabled by All-in-One Knit Architectures

Self-sensing soft robotics that mimic the proprioception and exteroception abilities of natural biological systems have shown great potential in challenging applications. However, current add-on strategies that simply combine sensors with actuators by post processing generally suffer from poor compatibility in mechanical properties, interfacing problems, complex manufacturing, and high cost. Herein, we present knitted soft robotics with build-in textile-integrated multimodal sensors, where the knit structure is used not only as a physical actuating layer but also as a sensing functional component. Based on different knit-stitch arrangements, an all-in-one knitted electronic skin with functions of neurons, sensing, and actuation in a single knit-structured fabric layer is constructed. The knitted electronic skin is then integrated into knitted soft robotics, enabling a proprioceptive sense of actuation deformation and an exteroceptive perception of ambient stimuli with minimized interferences for actuation. In addition, the tuck stitches serve as an anisotropic strain-limiting layer to increase the actuating energy efficiency, which resolves the key conflict of softness and volumetric power density in soft actuators. This design strategy provides a convenient, low-cost, and customized method to bring about structural and functional integrability into soft actuators, greatly extending the adaptability of current soft robotics for real-world applications.

Patterning Complex Line Motifs in Thin Films Using Immersion-Controlled Reaction-Diffusion

The discovery of self-organization principles that enable scalable routes toward complex functional materials has proven to be a persistent challenge. Here, reaction-diffusion driven, immersion-controlled patterning (R-DIP) is introduced, a self-organization strategy using immersion-controlled reaction-diffusion for targeted line patterning in thin films. By modulating immersion speeds, the movement of a reaction-diffusion front over gel films is controlled, which induces precipitation of highly uniform lines at the reaction front. A balance between the immersion speed and diffusion provides both hands-on tunability of the line spacing (d = 10 - 300 μ m $d = 10-300 \; \umu \text{m}$ ) as well as error-correction against defects. This immersion-driven patterning strategy is widely applicable, which is demonstrated by producing line patterns of silver/silver oxide nanoparticles, silver chromate, silver dichromate, and lead carbonate. Through combinatorial stacking of different line patterns, hybrid materials with multi-dimensional patterns such as square-, diamond-, rectangle-, and triangle-shaped motifs are fabricated. The functionality potential and scalability is demonstrated by producing both wafer-scale diffraction gratings with user-defined features as well as an opto-mechanical sensor based on Moiré patterning.

A liquid-free conducting ionoelastomer for 3D printable multifunctional self-healing electronic skin with tactile sensing capabilities

Conductive elastomers with both softness and conductivity are widely used in the field of flexible electronics. Nonetheless, conductive elastomers typically exhibit prominent problems such as solvent volatilization and leakage, and poor mechanical and conductive properties, which limit their applications in electronic skin (e-skin). In this work, a liquid-free conductive ionogel (LFCIg) with excellent performance was fabricated by utilizing the innovative double network design approach based on a deep eutectic solvent (DES). The double-network LFCIg is cross-linked by dynamic non-covalent bonds, which exhibit excellent mechanical properties (2100% strain while sustaining a fracture strength of 1.23 MPa) and >90% self-healing efficiency, and a superb electrical conductivity of 23.3 mS m-1 and 3D printability. Moreover, the conductive elastomer based on LFCIg has been developed into a stretchable strain sensor that achieves accurate response recognition, classification, and identification of different robot gestures. More impressively, an e-skin with tactile sensing functions is produced by in situ 3D printing of sensor arrays on flexible electrodes to detect light weight objects and recognize the resulting spatial pressure variations. Collectively, the results demonstrate that the designed LFCIg has unparalleled advantages and presents wide application potential in flexible robotics, e-skin and physiological signal monitoring.