High-Performance Strain Sensors Based on Organohydrogel Microsphere Film for Wearable Human-Computer Interfacing

Recent advances in flexible hydrogel sensors: Enhancing data processing and machine learning for intelligent perception

With the advent of flexible electronics and sensing technology, hydrogel-based flexible sensors have exhibited considerable potential across a diverse range of applications, including wearable electronics and soft robotics. Recently, advanced machine learning (ML) algorithms have been integrated into flexible hydrogel sensing technology to enhance their data processing capabilities and to achieve intelligent perception. However, there are no reviews specifically focusing on the data processing steps and analysis based on the raw sensing data obtained by flexible hydrogel sensors. Here we provide a comprehensive review of the latest advancements and breakthroughs in intelligent perception achieved through the fusion of ML algorithms with flexible hydrogel sensors, across various applications. Moreover, this review thoroughly examines the data processing techniques employed in flexible hydrogel sensors, offering valuable perspectives expected to drive future data-driven applications in this field.

Nature-inspired adhesive systems

Many organisms in nature thrive in intricate habitats through their unique bio-adhesive surfaces, facilitating tasks such as capturing prey and reproduction. It's important to note that the remarkable adhesion properties found in these natural biological surfaces primarily arise from their distinct micro- and nanostructures and/or chemical compositions. To create artificial surfaces with superior adhesion capabilities, researchers delve deeper into the underlying mechanisms of these captivating adhesion phenomena to draw inspiration. This article provides a systematic overview of various biological surfaces with different adhesion mechanisms, focusing on surface micro- and nanostructures and/or chemistry, offering design principles for their artificial counterparts. Here, the basic interactions and adhesion models of natural biological surfaces are introduced first. This will be followed by an exploration of research advancements in natural and artificial adhesive surfaces including both dry adhesive surfaces and wet/underwater adhesive surfaces, along with relevant adhesion characterization techniques. Special attention is paid to stimulus-responsive smart artificial adhesive surfaces with tunable adhesive properties. The goal is to spotlight recent advancements, identify common themes, and explore fundamental distinctions to pinpoint the present challenges and prospects in this field.

Design of Cellulose Nanocrystal-Based Self-Healing Nanocomposite Hydrogels and Application in Motion Sensing and Sweat Detection

Hydrogels, as flexible materials, have been widely used in the field of flexible sensors. Human sweat contains a variety of biomarkers that can reflect the physiological state of the human body. Therefore, it is of great practical significance and application value to realize the detection of sweat composition and combine it with human motion sensing through a hydrogel. Based on mussel-inspired chemistry, polydopamine (PDA) and gold nanoparticles (AuNPs) were coated on the surface of cellulose nanocrystals (CNCs) to obtain CNC-based nanocomposites (CNCs@PDA-Au), which could simultaneously enhance the mechanical, electrochemical, and self-healing properties of hydrogels. The CNCs@PDA-Au was composited with poly(vinyl alcohol) (PVA) hydrogel to obtain the nanocomposite hydrogel (PVA/CNCs@PDA-Au) by freeze-thaw cycles. The PVA/CNCs@PDA-Au has excellent mechanical strength (7.2 MPa) and self-healing properties (88.3%). The motion sensors designed with PVA/CNCs@PDA-Au exhibited a fast response time (122.9 ms), wide strain sensing range (0-600.0%), excellent stability, and fatigue resistance. With the unique electrochemical redox properties of uric acid, the designed hydrogel sensor successfully realized the detection of uric acid in sweat with a wide detection range (1.0-100.0 μmol/L) and low detection limit (0.42 μmol/L). In this study, the dual detection of human motion and uric acid in sweat was successfully realized by the designed PVA/CNCs@PDA-Au nanocomposite hydrogel.

Mechanically Excellent, Notch-Insensitive, and Highly Conductive Double-Network Hydrogel for Flexible Strain Sensor

A novel double-network conductive hydrogel based on lithium acetate/gelatin/polyacrylamide (PAAM) was synthesized by heating-cooling and subsequent γ-ray radiation-induced polymerization and cross-linking. Owing to the hydrogen bonding interaction between lithium acetate, physical cross-linked gelatin, and chemical cross-linked PAAM, the resultant hydrogel exhibited high tensile strength (1260 kPa), high ionic conductivity (35.2 mS cm-1), notch-insensitivity (tensile strength 415 kPa, elongation at break 872% with transverse notch), and extensive strain monitoring range (0.15-800%) under optimum conditions. The lithium acetate/gelatin/polyacrylamide hydrogel strain sensor attached to the skin can sensitively monitor the subtle movements of the human body. The strain sensor based on the resultant hydrogel with transverse notch can still work for 1200 cycles, due to that the covalent-cross-linked PAAm chain bridges the cracks and stabilizes the deformation, while the physical-cross-linked gelatin was unzipped to make the blunting of notch. The conductive hydrogel with high-sensitivity and high stability is expected to be used as materials for the preparation of flexible strain sensors in the future.

Anti-Freezing and Ultrasensitive Zwitterionic Betaine Hydrogel-Based Strain Sensor for Motion Monitoring and Human-Machine Interaction

Ultrasensitive and reliable conductive hydrogels are significant in the construction of human-machine twinning systems. However, in extremely cold environments, freezing severely limits the application of hydrogel-based sensors. Herein, building on biomimetics, a zwitterionic hydrogel was elaborated for human-machine interaction employing multichemical bonding synergies and experimental signal analyses. The covalent bonds, hydrogen bonds, and electrostatic interactions construct a dense double network structure favorable for stress dispersion and hydrogen bond regeneration. In particular, zwitterions and ionic conductors maintained excellent strain response (99 ms) and electrical sensitivity (gauge factor = 14.52) in the dense hydrogel structure while immobilizing water molecules to enhance the weather resistance (-68 °C). Inspired by the high sensitivity, zwitterionic hydrogel-based strain sensors and remote-control gloves were designed by analyzing the experimental signals, demonstrating promising potential applications within specialized flexible materials and human-machine symbiotic systems.

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human-Machine Interaction System for Active Rehabilitation

Human-machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsatisfactory recognition accuracy and wearing comfort. Here, this work develops a fully flexible, conformable, and functionalized multimodal HMI interface consisting of hydrogel-based sensors and a self-designed flexible printed circuit board. Thanks to the component regulation and structural design of the hydrogel, both electromyogram (EMG) and forcemyography (FMG) signals can be collected accurately and stably, so that they are later decoded with the assistance of artificial intelligence (AI). Compared with traditional multichannel EMG signals, the multimodal human-machine interaction method based on the combination of EMG and FMG signals significantly improves the efficiency of human-machine interaction by increasing the information entropy of the interaction signals. The decoding accuracy of the interaction signals from only two channels for different gestures reaches 91.28%. The resulting AI-powered active rehabilitation system can control a pneumatic robotic glove to assist stroke patients in completing movements according to the recognized human motion intention. Moreover, this HMI interface is further generalized and applied to other remote sensing platforms, such as manipulators, intelligent cars, and drones, paving the way for the design of future intelligent robot systems.

A Soft, Adhesive Self-Healing Naked-Eye Strain/Stress Visualization Patch

Learning about the strain/stress distribution in a material is essential to achieve its mechanical stability and proper functionality. Conventional techniques such as universal testing machines only apply to static samples with standardized geometry in laboratory environment. Soft mechanical sensors based on stretchable conductors, carbon-filled composites, or conductive gels possess better adaptability, but still face challenges from complicated fabrication process, dependence on extra readout device, and limited strain/stress mapping ability. Inspired by the camouflage mechanism of cuttlefish and chameleons, here an innovative responsive hydrogel containing light-scattering "mechano-iridophores" is developed. Force induced reversible phase separation manipulates the dynamic generation of mechano-iridophores, serving as optical indicators of local deformation. Patch-shaped mechanical sensors made from the responsive hydrogel feature fast response time (<0.4 s), high spatial resolution (≈100 µm), and wide dynamic ranges (e.g., 10-150% strain). The intrinsic adhesiveness and self-healing material capability of sensing patches also ensure their excellent applicability and robustness. This combination of chemical and optical properties allows strain/stress distributions in target samples to be directly identified by naked eyes or smartphone apps, which is not yet achieved. The great advantages above are ideal for developing the next-generation mechanical sensors toward material studies, damage diagnosis, risk prediction, and smart devices.

Ultraflexible Temperature-Strain Dual-Sensor Based on Chalcogenide Glass-Polymer Film for Human-Machine Interaction

Skin-like thermoelectric (TE) films with temperature- and strain-sensing functions are highly desirable for human-machine interaction systems and wearable devices. However, current TE films still face challenges in achieving high flexibility and excellent sensing performance simultaneously. Herein, for the first time, a facile roll-to-roll strategy is proposed to fabricate an ultraflexible chalcogenide glass-polytetrafluoroethylene composite film with superior temperature- and strain-sensing performance. The unique reticular network of the composite film endows it with efficient Seebeck effect and flexibility, leading to a high Seebeck coefficient (731 µV/K), rapid temperature response (≈0.7 s), and excellent strain sensitivity (gauge factor = 836). Based on this high-performance composite film, an intelligent robotic hand for action feedback and temperature alarm is fabricated, demonstrating its great potential in human-machine interaction. Such TE film fabrication strategy not only brings new inspiration for wearable inorganic TE devices, but also sets the stage for a wide implementation of multifunctional human-machine interaction systems.

Strong and tough polysaccharide organohydrogels for strain, humidity and temperature sensors

To avoid the potential toxicity of monomer residues in synthetic polymer based organohydrogels, natural polysaccharide-based organohydrogels are expected to be used in multi-functional wearable sensory systems, but most of them have unsatisfactory stiffness, strength and fracture toughness. Herein, a cooking and soaking strategy is proposed to prepare novel natural polysaccharide-based organohydrogels possessing outstanding stiffness, strength, toughness, freezing resistance, heating resistance and long-term durability. The agar organohydrogel exhibits a fracture stress of 3.3 MPa, a Young's modulus of 2.26 MPa and a fracture toughness of 14.8 kJ m-2, the κ-carrageenan organohydrogel exhibits a fracture stress of 3.3 MPa, a Young's modulus of 4.34 MPa and a fracture toughness of 11.0 kJ m-2, and the gellan organohydrogel exhibits a fracture stress of 1.2 MPa, a Young's modulus of 2.81 MPa and a fracture toughness of 5.4 kJ m-2. Furthermore, the agar organohydrogels are assembled into multi-functional wearable sensors by introducing NaCl as a conducting agent exhibiting responses to strain (5-150%), temperature (-15 to 60 °C) and humidity (11-97%), and possessing exceptional multi-sensory capabilities. Therefore, the developed strategy has shown a new pathway towards strengthening polysaccharide-based organohydrogels with potential for application in wearable sensory systems.

Mechanically Durable Superhydrophobic Strain Sensors with High Biocompatibility and Sensing Performance for Underwater Motion Monitoring

Much progress has been made toward the development of wearable flexible strain sensors with high sensing performance to monitor human motion, but continuous function in harsh aqueous environments remains a significant challenge. A promising strategy has been the design of sensors with highly durable superhydrophobicity and maintenance of unique sensing properties. Herein, an extremely durable superhydrophobic strain sensor with an ultrawide sensing range was simply fabricated by directly brushing conductive carbon black nanoparticles (CBNPs) onto an elastic silicone rubber sheet (SS) with poly(dimethylsiloxane) (PDMS) coatings (i.e., SS/PDMS-CBNPs sensors). First, this method avoided the use of toxic solvents and a conventional prestretching treatment. Second, considering the easily destroyed rough structures and surface chemistry for conventional superhydrophobic sensors during practical applications, the prepared SS/PDMS-CBNP sensors showed excellent mechanical durability of both superhydrophobicity and sensing as examined by harsh abrasion (300 cycles), stretching (up to 200%), and ultrasonication (40 min) treatments. Third, the prepared superhydrophobic strain sensor exhibited high sensitivity (gauge factor of 101.75), high stretchability (0.015-460%), low hysteresis (83 ms), and long-term stability (10000 cycles). Fourth, the high biocompatibility of the SS/PDMS-CBNP sensor was demonstrated by rabbit skin irritation tests. Finally, the remarkable water-repellent and sensing properties of the SS/PDMS-CBNP sensor allowed its application to monitor a swimmer's real-time situation and send distress signals when needed.

High-Fidelity, Low-Hysteresis Bionic Flexible Strain Sensors for Soft Machines

Stretchable flexible strain sensors based on conductive elastomers are rapidly emerging as a highly promising candidate for popular wearable flexible electronic and soft-mechanical sensing devices. However, due to the intrinsic limitations of low fidelity and high hysteresis, existing flexible strain sensors are unable to exploit their full application potential. Herein, a design strategy for a successive three-dimensional crack conductive network is proposed to cope with the uncoordinated variation of the output resistance signal arising from the conductive elastomer. The electrical characteristics of the sensor are dominated by the successive crack conductive network through a greater resistance variation and a concise sensing mechanism. As a result, the developed elastomer bionic strain sensors exhibit excellent sensing performance in terms of a smaller overshoot response, a lower hysteresis (∼2.9%), and an ultralow detection limit (0.00179%). What's more, the proposed strategy is universal and applicable to many conductive elastomers with different conductive fillers (including 0-D, 1-D, and 2-D conductive fillers). This approach improves the sensing signal accuracy and reliability of conductive elastomer strain sensors and holds promising potential for various applications in the fields of e-skin and soft robotic systems.

Advancing high-performance tailored dual-crosslinking network organo-hydrogel flexible device for wireless wearable sensing

Conductive hydrogels are essential for enabling long-term and reliable signal sensing in wearable electronics due to their tunable flexibility, stimulus responsiveness, and multimodal sensing integration. However, developing durable and dependable integrated hydrogel-based flexible devices has been challenging due to mismatched mechanical properties, limited water retention capability, and reduced flexibility. This work addresses these challenges by employing a tailored physical-chemical dual-crosslinking strategy to fabricate dynamically reversible organo-hydrogels with high performance. The resultant organo-hydrogels exhibit exceptional characteristics, including high stretchability (up to ∼495% strain), remarkable toughness (with tensile and compressive strengths of ∼1350 kPa and ∼9370 kPa, respectively), and outstanding transparency (∼90.3%). Moreover, they demonstrate excellent long-term water retention ability (>2424 h, >97%). Notably, the organo-hydrogel based sensor exhibits heightened sensitivity for monitoring physiological signals and motions. Furthermore, our integrated wireless wearable sensing system efficiently captures and transmits various human physiological signals and motion information in real-time. This research advances the development of customized devices utilizing functional organo-hydrogel materials, making contributions to fulfilling the increasing demand for high-performance wireless wearable sensing.

Low-Power Consumption IGZO Memristor-Based Gas Sensor Embedded in an Internet of Things Monitoring System for Isopropanol Alcohol Gas

Low-power-consumption gas sensors are crucial for diverse applications, including environmental monitoring and portable Internet of Things (IoT) systems. However, the desorption and adsorption characteristics of conventional metal oxide-based gas sensors require supplementary equipment, such as heaters, which is not optimal for low-power IoT monitoring systems. Memristor-based sensors (gasistors) have been investigated as innovative gas sensors owing to their advantages, including high response, low power consumption, and room-temperature (RT) operation. Based on IGZO, the proposed isopropanol alcohol (IPA) gas sensor demonstrates a detection speed of 105 s and a high response of 55.15 for 50 ppm of IPA gas at RT. Moreover, rapid recovery to the initial state was achievable in 50 μs using pulsed voltage and without gas purging. Finally, a low-power circuit module was integrated for wireless signal transmission and processing to ensure IoT compatibility. The stability of sensing results from gasistors based on IGZO has been demonstrated, even when integrated into IoT systems. This enables energy-efficient gas analysis and real-time monitoring at ~0.34 mW, supporting recovery via pulse bias. This research offers practical insights into IoT gas detection, presenting a wireless sensing system for sensitive, low-powered sensors.

Developing Safe Organohydrogel Sunscreens Using Polyelectrolyte-Betaine Surfactant Complexes

Oil-in-water emulsions are extensively used in skincare products due to their improved texture, stability, and effectiveness. There is limited success in developing effective delivery systems that can selectively target the active sunscreen ingredients onto the skin surface. Herein, an organohydrogel was prepared by physical cross-linking of an oil-in-water nanoemulsion with chitosan under neutral pH conditions. In the presence of a small quantity of coconut oil, lauramidopropyl betaine and glycerol were able to emulsify the active sunscreen ingredients into nanoscale droplets with enhanced ultraviolet light absorption. A facile pH-triggered interfacial cross-linking approach was applied to transform the nanoemulsion into an organohydrogel sunscreen. Furthermore, the organohydrogel sunscreen displayed encouraging characteristics including efficient UV-blocking capacity, resistance to water, simple removal, and minimal skin penetration. This facile approach provides an effective pathway for scaling up the organohydrogels, which are highly suitable for the safe application of sunscreen.

Template-Free and Stretchable Conductive Fiber with a Built-In Helical Structure for Strain-Insensitive Signal Transmission

With the rapid development of intelligent electronic devices, conductive fibers have become very critical to signal transmission devices. However, metal-based rigid conductive wires, such as high-modulus copper and silver wires, are prone to signal failure owing to tensile breakage under large strain conditions. Therefore, strain-insensitive stretchable conductive fibers for signal transmission are critical for next-generation wearable devices. Herein, a stretchable conductive fiber with a built-in helical structure is constructed by a "speed discrepancy" fiber-coating strategy with mass scalable production (60 cm/min). Such a "speed discrepancy" strategy is the key mechanism to template-free fabricate a built-in helical structure of the stretchable conductive fiber. The resultant fiber exhibits high conductivity (873 S/cm), stable insensitive signal transmission with a high quality factor (47.4), and a low relative resistance change (∼6%) under large strain. The built-in helical structure inspired by loofah whiskers endows the fiber with excellent strain insensitivity, and it can withstand large strains. On the proof of concept, our fiber can be seamlessly knitted, woven, and braided into smart textiles as an ideal signal transmission device under large strains, which will undoubtedly promote the development of intelligent electronic textiles and next-generation wearable devices.

Gesture Recognition System Using Reduced Graphene Oxide-Enhanced Hydrogel Strain Sensors for Rehabilitation Training

Gesture recognition systems epitomize a modern and intelligent approach to rehabilitative training, finding utility in assisted driving, sign language comprehension, and machine control. However, wearable devices that can monitor and motivate physically rehabilitated people in real time remain little studied. Here, we present an innovative gesture recognition system that integrates hydrogel strain sensors with machine learning to facilitate finger rehabilitation training. PSTG (PAM/SA/TG) hydrogels are constructed by thermal polymerization of acrylamide (AM), sodium alginate (SA), and tannic acid-reduced graphene oxide (TA-rGO, TG), with AM polymerizing into polyacrylamide (PAM). The surface of TG has abundant functional groups that can establish multiple hydrogen bonds with PAM and SA chains to endow the hydrogel with high stretchability and mechanical stability. Our strain sensor boasts impressive sensitivity (Gauge factor = 6.13), a fast response time (40.5 ms), and high linearity (R2 = 0.999), making it an effective tool for monitoring human joint movements and pronunciation. Leveraging machine learning techniques, our gesture recognition system accurately discerns nine distinct types of gestures with a recognition accuracy of 100%. Our research drives wearable advancements, elevating the landscape of patient rehabilitation and augmenting gesture recognition systems' healthcare applications.

3D Printable Organohydrogel with Long-Lasting Moisture and Extreme-Temperature Tolerance for Flexible Electronics

Hydrogels with high electrical conductivity and mechanical stretchability are promising materials for flexible electronics. However, traditional hydrogels are applied in short-term usage at room temperature or low temperature due to their poor water-retention ability and freezing-tolerance property. Here, a dually cross-linked glycerol-organohydrogel (GL-organohydrogel) based on GL and acrylic acid was synthesized in a GL-water binary solvent. Fe3+ ions working as an electrolyte were added to improve the conductivity of the organohydrogel and form coordination interactions between Fe3+ ions and carboxyl groups of acrylic acid. The strong hydrogen bonding between GL and water molecules firmly lock water in the organohydrogel network, thereby endowing the GL-organohydrogel with the antifreezing property, long-term stability, and moisture lock-in capability. Our organohydrogel could endure extremely low temperature (-80 °C) over 30 days without freezing and retain its water content (almost 100% of its initial state) after being stored at room temperature (25 °C, 54% humidity) for 30 days. It also demonstrated desired stretchable properties, conductivity, three-dimensional (3D) printability, and self-healing ability. A wearable data glove was constructed by using the GL-organohydrogel and digital light processing technology. This work opens a new avenue for developing hydrogels with long-term stability, moisture lock-in capability, and extreme-temperature tolerance for stretchable electronics.

Ultrasensitive Flexible Thermal Sensor Arrays based on High-Thermopower Ionic Thermoelectric Hydrogel

Ionic circuits using ions as charge carriers have demonstrated great potential for flexible and bioinspired electronics. The emerging ionic thermoelectric (iTE) materials can generate a potential difference by virtue of selective thermal diffusion of ions, which provide a new route for thermal sensing with the merits of high flexibility, low cost, and high thermopower. Here, ultrasensitive flexible thermal sensor arrays based on an iTE hydrogel consisting of polyquaternium-10 (PQ-10), a cellulose derivative, as the polymer matrix and sodium hydroxide (NaOH) as the ion source are reported. The developed PQ-10/NaOH iTE hydrogel achieves a thermopower of 24.17 mV K-1 , which is among the highest values reported for biopolymer-based iTE materials. The high p-type thermopower can be attributed to thermodiffusion of Na+ ions under a temperature gradient, while the movement of OH- ions is impeded by the strong electrostatic interaction with the positively charged quaternary amine groups of PQ-10. Flexible thermal sensor arrays are developed through patterning the PQ-10/NaOH iTE hydrogel on flexible printed circuit boards, which can perceive spatial thermal signals with high sensitivity. A smart glove integrated with multiple thermal sensor arrays is further demonstrated, which endows a prosthetic hand with thermal sensation for human-machine interaction.

High Sensitivity, Wide Linear-Range Strain Sensor Based on MXene/AgNW Composite Film with Hierarchical Microcrack

Stretchable strain sensors suffer the trade-off between sensitivity and linear sensing range. Developing sensors with both high sensitivity and wide linear range remains a formidable challenge. Different from conventional methods that rely on the structure design of sensing nanomaterial or substrate, here a heterogeneous-surface strategy for silver nanowires (AgNWs) and MXene is proposed to construct a hierarchical microcrack (HMC) strain sensor. The heterogeneous surface with distinct differences in cracks and adhesion strengths divides the sensor into two regions. One region contributes to high sensitivity through penetrating microcracks of the AgNW/MXene composite film during stretching. The other region maintains conductive percolation pathways to provide a wide linear sensing range through network microcracks. As a result, the HMC sensor exhibits ultrahigh sensitivity (gauge factor ≈ 244), broad linear range (ɛ = 60%, R2 ≈ 99.25%), and fast response time (<30 ms). These merits are confirmed in the detection of large and subtle human motions and digital joint movement for Morse coding. The manipulation of cracks on the heterogeneous surface provides a new paradigm for designing high-performance stretchable strain sensors.

Deep-Learning Enabled Active Biomimetic Multifunctional Hydrogel Electronic Skin

There is huge demand for recreating human skin with the functions of epidermis and dermis for interactions with the physical world. Herein, a biomimetic, ultrasensitive, and multifunctional hydrogel-based electronic skin (BHES) was proposed. Its epidermis function was mimicked using poly(ethylene terephthalate) with nanoscale wrinkles, enabling accurate identification of materials through the capabilities to gain/lose electrons during contact electrification. Internal mechanoreceptor was mimicked by interdigital silver electrodes with stick-slip sensing capabilities to identify textures/roughness. The dermis function was mimicked by patterned microcone hydrogel, achieving pressure sensors with high sensitivity (17.32 mV/Pa), large pressure range (20-5000 Pa), low detection limit, and fast response (10 ms)/recovery time (17 ms). Assisted by deep learning, this BHES achieved high accuracy and minimized interference in identifying materials (95.00% for 10 materials) and textures (97.20% for four roughness cases). By integrating signal acquisition/processing circuits, a wearable drone control system was demonstrated with three-degree-of-freedom movement and enormous potentials for soft robots, self-powered human-machine interaction interfaces of digital twins.

Constructing origami power generator from one piece of electret thin film and application in AI-enabled transmission line vibration monitoring

One of the crucial issues for applying electret/triboelectric power generators in the Internet of Things (IoT) is to take full advantage of specific high voltage signals and enable self-powered sensing. Therefore, inspired by Miura-origami, we present an innovative origami power generator (OPG) constructed from only one piece of electret thin film. The Miura-origami architecture realizes a generator with excellent deformability and stretchability and makes it unnecessary for any auxiliary support structure during the compress-release cycle. Various parameters of the generator are intensively investigated, including the excitation accelerations, excitation displacements, numbers of power generation units and deformation degree of the device. When stimulated with 5.0 g acceleration at 15 Hz frequency, the generator with 8 generation units can obtain an instantaneous peak-to-peak voltage and a remarkable optimum peak power of 328 V and 2152 μW at 50 MΩ, respectively. In addition, the regulable shape and multiple generation modes of the device greatly improve its applicability in various vibration energy collection requirements. Based on the above results, a hexagonal electret generator integrated with six-phase OPGs is developed as a "Buoy on Sky," after which the signal waveforms generated from internal power generators are recognized with 92% accuracy through a neural network algorithm that identifies the vibration conditions of transmission lines. This work demonstrates that a fusion of origami art and energy conversion techniques can achieve a multifunctional generator design satisfying the requirements for IoT applications.

Adhesive Ion-Conducting Hydrogel Strain Sensor with High Sensitivity, Long-Term Stability, and Extreme Temperature Tolerance

Ion-conducting hydrogels with excellent flexibility and ductility have great potential in human movements monitoring. However, some obstacles, including a small detection range, low sensitivity, low electrical conductivity, and poor stability under extreme conditions, impede their use as sensors. Herein, an ion-conducting hydrogel comprising acrylamide (AM), lauryl methacrylate (LMA), 2-acrylamido-2-methylpropanesulfonic acid (AMPS), and a water/glycerol binary solvent (named the AM-LMA-AMPS-LiCl (water/glycerol) hydrogel) is designed, which exhibits an enlarged detection range of 0%-1823% and improved transparency. Notably, the ion channel constructed using AMPS and LiCl significantly improves the sensitivity (gauge factor = 22.15 ± 2.86) of the hydrogel. The water/glycerol binary solvent endows the hydrogel with electrical and mechanical stability under extreme conditions (70 and -80 °C). Furthermore, the AM-LMA-AMPS-LiCl (water/glycerol) hydrogel exhibits antifatigue properties for 10 cycles (0%-1000%) because of noncovalent interactions such as hydrophobic interactions and hydrogen bonding. The hydrogel can be used to monitor human movements such as joint bending and perceive subtle discrepancies such as different joint bending speeds and angles, showing its great potential application in human movement monitoring, electronic skin, and wearable devices.

Functionalized Hydrogel-Based Wearable Gas and Humidity Sensors

Breathing is an inherent human activity; however, the composition of the air we inhale and gas exhale remains unknown to us. To address this, wearable vapor sensors can help people monitor air composition in real time to avoid underlying risks, and for the early detection and treatment of diseases for home healthcare. Hydrogels with three-dimensional polymer networks and large amounts of water molecules are naturally flexible and stretchable. Functionalized hydrogels are intrinsically conductive, self-healing, self-adhesive, biocompatible, and room-temperature sensitive. Compared with traditional rigid vapor sensors, hydrogel-based gas and humidity sensors can directly fit human skin or clothing, and are more suitable for real-time monitoring of personal health and safety. In this review, current studies on hydrogel-based vapor sensors are investigated. The required properties and optimization methods of wearable hydrogel-based sensors are introduced. Subsequently, existing reports on the response mechanisms of hydrogel-based gas and humidity sensors are summarized. Related works on hydrogel-based vapor sensors for their application in personal health and safety monitoring are presented. Moreover, the potential of hydrogels in the field of vapor sensing is elucidated. Finally, the current research status, challenges, and future trends of hydrogel gas/humidity sensing are discussed.