Peeling–Stiffening Self‐Adhesive Ionogel with Superhigh Interfacial Toughness

Advanced Materials, Год журнала: 2023, Номер 36(11)

Опубликована: Дек. 14, 2023

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

Язык: Английский

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An Intelligent Robotic System Capable of Sensing and Describing Objects Based on Bimodal, Self‐Powered Flexible Sensors

Advanced Functional Materials, Год журнала: 2023, Номер 33(41)

Опубликована: Авг. 24, 2023

Abstract This study presents an intelligent soft robotic system capable of perceiving, describing, and sorting objects based on their physical properties. work introduces a bimodal self‐powered flexible sensor (BSFS) the triboelectric nanogenerator giant magnetoelastic effect. The BSFS features simplified structure comprising conductive film packaged liquid metal coil. can precisely detect distinguish touchless tactile models, with response time 10 ms. By seamlessly integrating BSFSs into fingers, this realizes anthropomorphic hand remarkable multimodal perception capabilities. signals provide valuable insights object shape material composition, while offer precise information regarding surface roughness. Utilizing convolutional neural network (CNN), integrates all sensing information, resulting in that accurately describes properties, including materials, roughness, shapes, accuracy rate up to 97%. may lay foundation for hardware general artificial intelligence capacities interpret interact world, which also serves as interface between robots.

Язык: Английский

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

Nano Letters, Год журнала: 2024, Номер 24(12), С. 3826 - 3834

Опубликована: Март 18, 2024

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

Язык: Английский

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

ACS Nano, Год журнала: 2024, Номер 18(14), С. 9980 - 9996

Опубликована: Фев. 22, 2024

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

Язык: Английский

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Neural Network‐Inspired Polyurea Ionogel with Mechanical Robustness, Low Hysteresis, and High Transparency for Soft Iontronics

Advanced Functional Materials, Год журнала: 2024, Номер 34(37)

Опубликована: Март 7, 2024

Abstract Concurrently achieving mechanical robustness, low hysteresis, and high transparency are essential for ionogels to enhance their reliability satisfy the requirements in soft electronics. Fabricating comprising these characteristics presents a considerable challenge. Herein, inspired by structure of neural networks, new strategy situ formation dense urea moieties aggregated domains is proposed achieve topology‐tailoring polyurea ionogels. Initially, leveraging pronounced disparity reactivity isocyanate (─NCO) groups between isophorone diisocyanate (IPDI) NCO‐terminated prepolymer (PPGTD), IPDI preferentially reacts with deblocked trifunctional latent curing agents, resulting domains. Thereafter, interconnected via PPGTD establish polymer networks which ionic liquid uniformly dispersed, forming like Attributed this unique design strategy, ionogel demonstrates remarkable properties, including strength (0.6–2.4 MPa), excellent toughness (0.9–4.3 MJ m −3 ), hysteresis (6.6–11.6%), (>92%), along enhanced fatigue puncture resistance. Furthermore, exhibit outstanding versatility, enabling strain sensors, flexible electroluminescence devices, nanogenerators. This contributes unparalleled combinatory catering diverse demands iontronics.

Язык: Английский

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

Nano-Micro Letters, Год журнала: 2024, Номер 16(1)

Опубликована: Июль 29, 2024

Abstract Post-earthquake rescue missions are full of challenges due to the unstable structure ruins and successive aftershocks. Most current robots lack ability interact with environments, leading low efficiency. The multimodal electronic skin (e-skin) proposed not only reproduces pressure, temperature, humidity sensing capabilities natural but also develops functions beyond it—perceiving object proximity NO 2 gas. Its multilayer stacked based on Ecoflex organohydrogel endows e-skin mechanical properties similar skin. Rescue integrated artificial intelligence (AI) algorithms show strong environmental perception can accurately distinguish objects identify human limbs through grasping, laying foundation for automated post-earthquake rescue. Besides, combination wireless alarm circuits allows sense toxic gases in environment real time, thereby adopting appropriate measures protect trapped people from environment. Multimodal powered by AI hardware exhibits powerful information processing capabilities, which, as an interface interaction physical world, dramatically expands intelligent robots’ application scenarios.

Язык: Английский

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

Science Advances, Год журнала: 2024, Номер 10(30)

Опубликована: Июль 24, 2024

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

Язык: Английский

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Wearable and Recyclable Water‐Toleration Sensor Derived from Lipoic Acid

Small, Год журнала: 2024, Номер 20(30)

Опубликована: Март 12, 2024

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

Язык: Английский

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

Advanced Materials, Год журнала: 2024, Номер unknown

Опубликована: Авг. 11, 2024

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

Язык: Английский

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An All-Protein Multisensory Highly Bionic Skin

ACS Nano, Год журнала: 2024, Номер 18(5), С. 4579 - 4589

Опубликована: Янв. 23, 2024

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

Язык: Английский

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