A multimodal magnetoelastic artificial skin for underwater haptic sensing

3D Printing of Auxetic Self-powered Mechanoluminescent Photonic Skins for Underwater Communication and Safety Monitoring

Stretchable mechanoluminescent (ML) photonic skin with strong and stable brightness holds great promise for underwater communication and safety monitoring. However, traditional film-based ML devices often lack the compliance needed to accommodate curved surfaces and face a trade-off between extensibility and luminescent intensity. This study introduces a 3D-printed self-powered auxetic ML photonic skin. By utilizing auxetic materials with a negative Poisson's ratio, we created a stretchable ML device that conforms to complex, curved surfaces, enhancing its applicability in dynamic underwater settings. By encapsulating the auxetic ML structure in silicone, simultaneous improvements in brightness uniformity and stretchability are achieved. The device exhibits remarkable durability, maintaining consistent light emission and mechanical performance over 10 000 cycles, and demonstrates the potential for real-time underwater communication and safety monitoring. Integrated into a glove, a swimming toy, and a gas tank, the photonic skin successfully transmitted Morse code signals and detected gas leaks, showcasing its versatility and robustness in harsh underwater conditions. These findings underscore the potential of this technology to improve safety and efficiency in marine exploration, paving the way for further advancements in underwater robotics and communication.

Logarithmic Helical Design for Reversed Magnetic Field in Magnetoelastic Soft Matters with Giant Current Outputs

Magnetoelastic soft materials are widely used in soft bioelectronics. However, mechanical deformation usually induces minimal changes in magnetic flux, limiting electrical outputs. To overcome this limitation, a two-step process is employed to enhance the variation in magnetic flux density under mechanical force. On one hand, the helical structural design enables the magnetic membrane to flip completely, reversing the magnetic field. On the other hand, the applied mechanical force induces strain within the magnetoelastic membrane, leading to variations in magnetic flux density. A complete 180° reversal of the magnetic field is achieved using a logarithmic helical structure, resulting in a 200% increase in magnetic flux variation and a peak current of 6.34 mA. Following structural optimization, the current density reached an impressive 7.17 mA cm-2. Using this rationally designed logarithmic helix model, a knee pad is developed for wearable energy harvesting from human body movement. The device can generate a current of up to 2.83 mA, providing sufficient power for various small electronics, including smartphones, LED lights, headlamps, and rechargeable batteries. This achievement represents a significant milestone in advancing high-performance wearable biomechanical energy harvesting.

Optimized Magnetization Distribution in Body-Centered Cubic Lattice-Structured Magnetoelastomer for High-Performance 3D Force-Tactile Sensors

Flexible magnetic tactile sensors hold transformative potential in robotics and human-computer interactions by enabling precise force detection. However, existing sensors face challenges in balancing sensitivity, detection range, and structural adaptability for sensing force. This study proposed a pre-compressed magnetization method to address these limitations by amplifying the magnetoelastic effect through optimized magnetization direction distribution of the elastomer. A body-centered cubic lattice-structured magnetoelastomer featuring regular deformation under compression was fabricated via digital light processing (DLP) to validate this method. Finite element simulations and experimental analyses revealed that magnetizing the material under 60% compression strain optimized magnetization direction distribution, enhancing force-magnetic coupling. Integrating the magnetic elastomer with a hall sensor, the prepared tactile sensor demonstrated a low detection limit (1 mN), wide detection range (0.001-10 N), rapid response/recovery times (40 ms/50 ms), and durability (>1500 cycles). By using machine learning, the sensor enabled accurate 3D force prediction.

Soft Materials and Devices Enabling Sensorimotor Functions in Soft Robots

Sensorimotor functions, the seamless integration of sensing, decision-making, and actuation, are fundamental for robots to interact with their environments. Inspired by biological systems, the incorporation of soft materials and devices into robotics holds significant promise for enhancing these functions. However, current robotics systems often lack the autonomy and intelligence observed in nature due to limited sensorimotor integration, particularly in flexible sensing and actuation. As the field progresses toward soft, flexible, and stretchable materials, developing such materials and devices becomes increasingly critical for advanced robotics. Despite rapid advancements individually in soft materials and flexible devices, their combined applications to enable sensorimotor capabilities in robots are emerging. This review addresses this emerging field by providing a comprehensive overview of soft materials and devices that enable sensorimotor functions in robots. We delve into the latest development in soft sensing technologies, actuation mechanism, structural designs, and fabrication techniques. Additionally, we explore strategies for sensorimotor control, the integration of artificial intelligence (AI), and practical application across various domains such as healthcare, augmented and virtual reality, and exploration. By drawing parallels with biological systems, this review aims to guide future research and development in soft robots, ultimately enhancing the autonomy and adaptability of robots in unstructured environments.

Self-powered electrotactile textile haptic glove for enhanced human-machine interface

Human-machine interface (HMI) plays an important role in various fields, where haptic technologies provide crucial tactile feedback that greatly enhances user experience, especially in virtual reality/augmented reality, prosthetic control, and therapeutic applications. Through tactile feedback, users can interact with devices in a more realistic way, thereby improving the overall effectiveness of the experience. However, existing haptic devices are often bulky due to cumbersome instruments and power modules, limiting comfort and portability. Here, we introduce a concept of wearable haptic technology: a thin, soft, self-powered electrotactile textile haptic (SPETH) glove that uses the triboelectric effect and gas breakdown discharge for localized electrical stimulation. Daily hand movements generate sufficient mechanical energy to power the SPETH glove. Its features-softness, lightweight, self-sustainability, portability, and affordability-enable it to provide tactile feedback anytime and anywhere without external equipment. This makes the SPETH glove an enhanced, battery-free HMI suitable for a wide range of applications.

A flexible pressure sensor array for self-powered identity authentication during typing

The keyboard, a staple tool for information entry and human-machine interaction, faces demands for enhanced information security due to evolving internet technologies. This study introduces a self-powered flexible intelligent keyboard (SFIK) that harnesses the giant magnetoelastic effect to convert the mechanical pressure from key presses into electrical signals. The sensor boasts a wide sensing range (35 to 600 kPa) and a rapid response time (∼300 ms), allowing it to record and recognize individual keystroke dynamics. Integrated with machine learning, this keyboard enables identity authentication through both fixed- and dynamic-text inputs. It accurately authenticates fixed passwords of eight characters with a 95.3% success rate and dynamic text from 14 sets of double keys with 100% accuracy. Given its capabilities, the SFIK offers promising applications in artificial intelligence, network security, and access control for computers and networks.

Recent advancements in wearable sensors: integration with machine learning for human-machine interaction

Wearable sensors have emerged as a transformative technology, enabling real-time monitoring and advanced functionality in various fields, including healthcare, human-machine interaction, and environmental sensing. This review provides a comprehensive overview of the latest advancements in wearable sensor technologies, focusing on innovations in sensor design, material flexibility, and integration with machine learning. We explore the feasibility of wearable electronics in achieving high-performance, flexible devices and discuss their potential to enhance human-machine interactions through intelligent data processing and decision-making. The combination of wearable electronics and machine learning offers immense potential for applications requiring real-time responsiveness and advanced analytics. By analyzing recent developments of sensors, this review aims to inspire further innovations in this rapidly evolving field, paving the way for the next generation of wearable technologies.

Advances in conducting nanocomposite hydrogels for wearable biomonitoring

Recent advancements in wearable biosensors and bioelectronics have led to innovative designs for personalized health management devices, with biocompatible conducting nanocomposite hydrogels emerging as a promising building block for soft electronics engineering. In this review, we provide a comprehensive framework for advancing biosensors using these engineered nanocomposite hydrogels, highlighting their unique properties such as high electrical conductivity, flexibility, self-healing, biocompatibility, biodegradability, and tunable architecture, broadening their biomedical applications. We summarize key properties of nanocomposite hydrogels for thermal, biomechanical, electrophysiological, and biochemical sensing applications on the human body, recent progress in nanocomposite hydrogel design and synthesis, and the latest technologies in developing flexible and wearable devices. This review covers various sensor types, including strain, physiological, and electrochemical sensors, and explores their potential applications in personalized healthcare, from daily activity monitoring to versatile electronic skin applications. Furthermore, we highlight the blueprints of design, working procedures, performance, detection limits, and sensitivity of these soft devices. Finally, we address challenges, prospects, and future outlook for advanced nanocomposite hydrogels in wearable sensors, aiming to provide a comprehensive overview of their current state and future potential in healthcare applications.

Piezo-Capacitive Flexible Pressure Sensor with Magnetically Self-Assembled Microneedle Array

Flexible pressure sensors are pivotal in advancing artificial intelligence, the Internet of Things (IoT), and wearable technologies. While microstructuring the functional layer of these sensors effectively enhances their performance, current fabrication methods often require complex equipment and time-consuming processes. Herein, we present a novel magnetization-induced self-assembly method to develop a magnetically grown microneedle array as a dielectric layer for flexible capacitive pressure sensors. By precisely controlling the magnetic particle concentration and dynamic magnetic field strength, we achieve a tunable microneedle morphology. The resulting sensor exhibits high sensitivity (4.11 kPa-1), an ultrafast response time (20 ms), excellent cyclic stability (≈1700 cycles), and flexibility. We demonstrate real-time monitoring of various physiological signals including pulse, grip force, breathing rate, and head motion. This study introduces a promising approach for fabricating high-performance flexible sensors, potentially enabling more intuitive and effective human-machine interactions.

Advanced Dielectric Materials for Triboelectric Nanogenerators: Principles, Methods, and Applications

Triboelectric nanogenerator (TENG) manifests distinct advantages such as multiple structural selectivity, diverse selection of materials, environmental adaptability, low cost, and remarkable conversion efficiency, which becomes a promising technology for micro-nano energy harvesting and self-powered sensing. Tribo-dielectric materials are the fundamental and core components for high-performance TENGs. In particular, the charge generation, dissipation, storage, migration of the dielectrics, and dynamic equilibrium behaviors determine the overall performance. Herein, a comprehensive summary is presented to elucidate the dielectric charge transport mechanism and tribo-dielectric material modification principle toward high-performance TENGs. The contact electrification and charge transport mechanism of dielectric materials is started first, followed by introducing the basic principle and dielectric materials of TENGs. Subsequently, modification mechanisms and strategies for high-performance tribo-dielectric materials are highlighted regarding physical/chemical, surface/bulk, dielectric coupling, and structure optimization. Furthermore, representative applications of dielectric materials based TENGs as power sources, self-powered sensors are demonstrated. The existing challenges and promising potential opportunities for advanced tribo-dielectric materials are outlined, guiding the design, fabrication, and applications of tribo-dielectric materials.

Solvent-adaptive hydrogels with lamellar confinement cellular structure for programmable multimodal locomotion

Biological organisms can perform flexible and controllable multimodal motion under external stimuli owing to the hierarchical assembly of anisotropic structures across multiple length scales. However, artificial soft actuators exhibit the limited response speed, deformation programmability and movement capability especially in harsh environments because of insufficient anisotropic hierarchy and precision in structural design. Here, we report a programmed assembly directed confinement polymerization method for the fabrication of environmentally tolerant and fast responsive hydrogels with lamellar assembly-confined cellular structure interpenetrated with highly aligned nanopillars by the directional freezing-assisted polymerization in the predesigned anisotropic laminar scaffold. The obtained hydrogel exhibits ultrafast responsiveness and anisotropic deformation exposed to temperature/light/solvent stimulation, maintaining highly consistent responsive deformation capability in all-polarity solvents over 100 days of soaking. Moreover, the hydrogels implement photoactive programmable multi-gait locomotion whose amplitude and directionality are precisely regulated by the intrinsic structure, including controlled crawling and rotation in water and non-polar solvents, and 3D self-propulsion floating and swimming in polar solvents. Thus, this hydrogel with hierarchically ordered structure and dexterous locomotion may be suitable for flexible intelligent actuators serving in harsh solvent environments.

Biomimetic Hydrodynamic Sensor with Whisker Array Architecture and Multidirectional Perception Ability

The rapid development of ocean exploration and underwater robot technology has put forward new requirements for underwater sensing methods, which can be used for hydrodynamic characteristics perception, underwater target tracking, and even underwater cluster communication. Here, inspired by the specialized undulated surface structure of the seal whisker and its ability to suppress vortex-induced vibration, a multidirectional hydrodynamic sensor based on biomimetic whisker array structure and magnetic 3D self-decoupling theory is introduced. The magnetic-based sensing method enables wireless connectivity between the magnetic functional structures and electronics, simplifying device design and endowing complete watertightness. The 3D self-decoupling capability enables the sensor, like a seal or other organisms, to perceive arbitrary whisker motions caused by the action of water flow without complex calibration and additional sensing units. The whisker sensor is capable of detecting a variety of hydrodynamic information, including the velocity (RMSE < 0.061 m s-1) and direction of the steady flow field, the frequency (error < 0.05 Hz) of the dynamic vortex wake, and the orientation (error < 7°) of the vortex wake source, demonstrating its extensive potential for underwater environmental perception and communication, especially in deep sea conditions.

Magnetostrictive bi-perceptive flexible sensor for tracking bend and position of human and robot hand

The sensor that simultaneously perceives bending strain and magnetic field has the potential to detect the finger bending state and hand position of the human and robot. Based on unique magneto-mechanical coupling effect of magnetostrictive materials, the proposed a bi-perceptive flexible sensor, consisting of the Co-Fe film and magnetic sensing plane coils, can realize dual information perception of strain/magnetic field through the change of magnetization state. The sensor structure and interface circuit of the sensing system are designed to provide high sensitivity and fast response, based on the input-output characteristics of the simulation model. An asynchronous multi-task deep learning method is proposed, which takes the output of the position task as the partial input of the bending state task to analyze the output information of the sensor quickly and accurately. The sensing system, integrating with the proposed model, can better predict the bending state and approach distance of human or robot hand.

Advances in Machine Learning for Wearable Sensors

Recent years have witnessed tremendous advances in machine learning techniques for wearable sensors and bioelectronics, which play an essential role in real-time sensing data analysis to provide clinical-grade information for personalized healthcare. To this end, supervised learning and unsupervised learning algorithms have emerged as powerful tools, allowing for the detection of complex patterns and relationships in large, high-dimensional data sets. In this Review, we aim to delineate the latest advancements in machine learning for wearable sensors, focusing on key developments in algorithmic techniques, applications, and the challenges intrinsic to this evolving landscape. Additionally, we highlight the potential of machine-learning approaches to enhance the accuracy, reliability, and interpretability of wearable sensor data and discuss the opportunities and limitations of this emerging field. Ultimately, our work aims to provide a roadmap for future research endeavors in this exciting and rapidly evolving area.

A Novel Induction-Type Pressure Sensor based on Magneto-Stress Impedance and Magnetoelastic Coupling Effect for Monitoring Hand Rehabilitation

Visualization of training effectiveness is critical to patients' confidence and eventual rehabilitation. Here, an innovative magnetoinductive pressure sensor is proposed for monitoring hand rehabilitation in stroke hemiplegic patients. It couples the giant magneto and stress-impedance effects of a square spiral amorphous wire with the giant magnetoelastic effect of a polymer magnet (NdFeB@PDMS). The addition of the magnetoelastic layer results in a sensitivity improvement of 178%, a wide sensing range (up to 1 MPa), fast response/recovery times (40 ms), and excellent mechanical robustness (over 15 000 cycles). Further integration with an LC oscillation circuit enables frequency adjustment into the MHz range resulting in a sensitivity of 6.6% kPa-1 and outstanding linearity (R2 =  0.99717) over a stress range of up to 100 kPa. When attached to a commercial split-fingerboard, the sensor is capable of dynamically monitoring the force in each finger, providing a reading of the rehabilitation process. Unlike conventional inductive sensors, the sensor is based on an inductive force-responsive material (amorphous wire), which significantly boosts the sensitivity. The approach also demonstrates the potential of magnetoelasticity in static pressure sensing, which is highly sensitive to dynamic pressure only through electromagnetic induction. This makes it more suitable for long-term and continuous human health monitoring.

Flexible Electronics: Advancements and Applications of Flexible Piezoelectric Composites in Modern Sensing Technologies

The piezoelectric effect refers to a physical phenomenon where piezoelectric materials generate an electric field when subjected to mechanical stress or undergo mechanical deformation when subjected to an external electric field. This principle underlies the operation of piezoelectric sensors. Piezoelectric sensors have garnered significant attention due to their excellent self-powering capability, rapid response speed, and high sensitivity. With the rapid development of sensor techniques achieving high precision, increased mechanical flexibility, and miniaturization, a range of flexible electronic products have emerged. As the core constituents of piezoelectric sensors, flexible piezoelectric composite materials are commonly used due to their unique advantages, including high conformability, sensitivity, and compatibility. They have found applications in diverse domains such as underwater detection, electronic skin sensing, wearable sensors, targeted therapy, and ultrasound diagnostics for deep tissue. The advent of flexible piezoelectric composite materials has revolutionized the design concepts and application scenarios of traditional piezoelectric materials, playing a crucial role in the development of next-generation flexible electronic products. This paper reviews the research progress on flexible piezoelectric composite materials, covering their types and typical fabrication techniques, as well as their applications across various fields. Finally, a summary and outlook on the existing issues and future development of these composite materials are provided.

Modulus-tunable multifunctional hydrogel ink with nanofillers for 3D-Printed soft electronics

Seamless integration and conformal contact of soft electronics with tissue surfaces have emerged as major challenges in realizing accurate monitoring of biological signals. However, the mechanical mismatch between the electronics and biological tissues impedes the conformal interfacing between them. Attempts have been made to utilize soft hydrogels as the bioelectronic materials to realize tissue-comfortable bioelectronics. However, hydrogels have several limitations in terms of their electrical and mechanical properties. In this study, we present the development of a 3D-printable modulus-tunable hydrogel with multiple functionalities. The hydrogel has a cross-linked double network, which greatly improves its mechanical properties. Functional fillers such as XLG or functionalized carbon nanotubes (fCNT) can be incorporated into the hydrogel to provide tunable mechanics (Young's modulus of 10-300 kPa) and electrical conductivity (electrical conductivity of ∼20 S/m). The developed hydrogel exhibits stretchability (∼1000% strain), self-healing ability (within 5 min), toughness (400-731 kJ/m3) viscoelasticity, tissue conformability, and biocompatibility. Upon examining the rheological properties in the modulated region, hydrogels can be 3D printed to customize the shape and design of the bioelectronics. These hydrogels can be fabricated into ring-shaped strain sensors for wearable sensor applications.

A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality

Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.

Flexible Metasurfaces for Multifunctional Interfaces

Optical metasurfaces, capable of manipulating the properties of light with a thickness at the subwavelength scale, have been the subject of extensive investigation in recent decades. This research has been mainly driven by their potential to overcome the limitations of traditional, bulky optical devices. However, most existing optical metasurfaces are confined to planar and rigid designs, functions, and technologies, which greatly impede their evolution toward practical applications that often involve complex surfaces. The disconnect between two-dimensional (2D) planar structures and three-dimensional (3D) curved surfaces is becoming increasingly pronounced. In the past two decades, the emergence of flexible electronics has ushered in an emerging era for metasurfaces. This review delves into this cutting-edge field, with a focus on both flexible and conformal design and fabrication techniques. Initially, we reflect on the milestones and trajectories in modern research of optical metasurfaces, complemented by a brief overview of their theoretical underpinnings and primary classifications. We then showcase four advanced applications of optical metasurfaces, emphasizing their promising prospects and relevance in areas such as imaging, biosensing, cloaking, and multifunctionality. Subsequently, we explore three key trends in optical metasurfaces, including mechanically reconfigurable metasurfaces, digitally controlled metasurfaces, and conformal metasurfaces. Finally, we summarize our insights on the ongoing challenges and opportunities in this field.