Hierarchically patterned self-powered sensors for multifunctional tactile sensing

Muscle-Inspired Anisotropic Aramid Nanofibers Aerogel Exhibiting High-Efficiency Thermoelectric Conversion and Precise Temperature Monitoring for Firefighting Clothing

Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated, but it remains a major challenge. Herein, inspired by the human muscle, an anisotropic fire safety aerogel (ACMCA) with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network. By combining the two synergies of the negative temperature-dependent thermal conductive eicosane, which induces a high-temperature differential, and directionally ordered MXene that establishes a conductive network along the directional freezing direction. The resultant ACMCA exhibited remarkable thermoelectric properties, with S values reaching 46.78 μV K-1 and κ values as low as 0.048 W m-1 K-1 at room temperature. Moreover, the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations, facilitating its application in intelligent temperature monitoring systems. The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer, demonstrating a wide temperature sensing range (50-400 °C) and a rapid response time for early high-temperature alerts (~ 1.43 s). This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.

Nanostructures and Nanomaterials Integrated into Triboelectric Nanogenerators

The pursuit of eco-friendly and renewable power generation has driven technological breakthroughs in nanoscale engineering, particularly regarding triboelectric nanogenerators (TENGs). These devices have become a focus of interest due to their capacity to effectively transform kinetic energy into electrical power via combined triboelectrification and electrostatic charge separation mechanisms. TENGs now find expanding implementations across multiple fields including in flexible electronics, autonomous sensing systems, and ambient energy conversion technologies. Enhancing TENG performance critically depends on the strategic design and application of nanostructures and nanomaterials. Nonetheless, challenges such as material selection, compatibility, homogeneous dispersion, interfacial stability, and production scalability must be overcome to advance TENG technology. Moreover, the mechanisms by which nanomaterials contribute to the triboelectric effect remain insufficiently understood, underscoring the necessity for systematic theoretical models. This review provides a comprehensive overview of recent advancements in integrating nanostructures and nanomaterials into TENGs, elucidating their roles, advantages, and underlying mechanisms in enhancing energy conversion efficiency, while identifying key challenges and proposing future research directions.

Wireless, Multisensor Integrated Bioelectronics for Real-Time Monitoring and Assessment of Muscle Atrophy

Real-time monitoring and evaluation of muscle atrophy are vital for efficient treatment and effective diagnosis. Although some systems have been developed to monitor loss of muscle mass or strength, they are bulky and nonspecific, cannot be applied to the body, and cannot assess the degree of muscle atrophy. Our research focuses on developing a wireless multisensor wearable system (WMWS) for on-body monitoring and assessment of atrophy, which utilizes a single-electrode triboelectric nanogenerator (S-TENG) and electrochemical creatinine (CREA) sensor to achieve real-time acquisition of plantar pressure and interstitial fluid (ISF) CREA concentration. In addition, LSTM (long short-term memory) and SVM (support vector machine) machine learning (ML) algorithms also prove that our multisensor strategy can effectively improve the recognition rate of different degrees of atrophy (the highest accuracy reached 92.32%). Overall, our work makes it possible to monitor and grade muscle atrophy remotely in real time.

Simultaneous Visualization of Dynamical and Static Tactile Perception Using Piezoelectric-Ultrasonic Bimodal Electronic Skin Based on In Situ Polarized PVDF-TrFE/2DBP Composites and the TFT Array

The key to realizing completed bionic tactile perception of human skin using electronic skin relies on simultaneously distinguishing dynamic and static stimuli and restoring their characteristic information, which is realized by integration of several individual sensors but remains certain limitations including large physical size and high energy consumption. In this study, a piezoelectric-ultrasonic bimodal electronic skin (PUVE) based on in situ polarized PVDF-TrFE/2DBP composites and a thin-film transistor (TFT) array is fabricated. The incorporation of 2DBP into the PVDF-TrFE film and the in situ polarization approach provide excellent piezoelectric and ultrasonic performances of PVDF-TrFE/2DBP composites. PUVE has an ultrahigh sensitivity of 3.2 mV kPa-1 over a wide pressure (0-310 kPa) range, with excellent spatial resolution (50 μm) and response time (40 ms). Meanwhile, the PUVE demonstrated outstanding repeatability and bending stability in 1500 cycles of cyclic pressure and 4000 cycles of 180° bending. The integrated piezoelectric and ultrasonic functions of PUVE can respond individually to dynamic and static tactile stimuli to ensure perceiving and decoupling of the dynamical and static mechanical signals with one single sensor. The PVDF-TrFE/2DBP composites is further integrated with the TFT array, realizing visualization function of contacting objects and restoring their characteristic information including the texture and location. Thus, the PUVE is expected to have a wide range of applications in intelligent robots and human prostheses.

Advances in Soft Strain and Pressure Sensors

Soft strain and pressure sensors represent a breakthrough in material engineering and nanotechnology, providing accurate and reliable signal detection for applications in health monitoring, sports management, human-machine interface, or soft robotics, when compared to traditional rigid sensors. However, their performance is often compromised by environmental interference and off-axis mechanical deformations, which lead to nonspecific responses, as well as unstable and inaccurate measurements. These challenges can be effectively addressed by enhancing the sensors' specificity, making them responsive only to the desired stimulus while remaining insensitive to unwanted stimuli. This review systematically examines various materials and design strategies for developing strain and pressure sensors with high specificity for target physical signals, such as tactility, pressure distribution, body motions, or artery pulse. This review highlights approaches in materials engineering that impart special properties to the sensors to suppress interference from factors such as temperature, humidity, and liquid contact. Additionally, it details structural designs that improve sensor performance under different types of off-axis mechanical deformations. This review concludes by discussing the ongoing challenges and opportunities for inspiring the future development of highly specific electromechanical sensors.

Band Alignment Semimetal Heterojunction-Based Ultrabroadband Photodetector for Noncontact Gesture Interaction with Low Latency

Non-contact gesture recognition and interaction (NGRI) revolutionizes the natural user interface, fundamentally transforming human interactions with daily-use technology. Conventional NGRI systems frequently encounter obstacles such as pronounced latency and environmental disturbances, including humidity or lighting conditions, resulting in compromised system fluidity and robustness. This study highlights the utilization of silicon-based semimetal heterojunction photodetectors for precise gesture recognition and seamless human-machine interaction. Through the application of band alignment theory and sophisticated TCAD simulation, heterojunction barriers are successfully optimized by fine-tuning parameters including Si doping concentration and semimetal thickness. By strategically aligning vertical material growth and implementing vertical heterojunction configuration, a room temperature detector with exceptional sensitivity (specific detectivity (D*): ≈1011 Jones), ultra-broad spectral range (405-10600 nm), and rapid response time (≈ µs) is achieved. Harnessing its distinguished speed and sensitivity in detecting human infrared radiation, in conjunction with an advanced spatial-temporal comparison algorithm and a multi-channel high-frequency sampling processing design, a NGRI system with low latency, high precision, minimal energy consumption, and versatility across diverse scenarios has been developed. The results pave the way for non-contact sensor design and may further enhance the practicality and user experience of non-contact human-machine interaction systems.

Smart Driving Hardware Augmentation by Flexible Piezoresistive Sensor Matrices with Grafted-on Anticreep Composites

Signal drift and hysteresis of flexible piezoresistive sensors pose significant challenges against the widespread applications in emerging fields such as electronic skin, wearable equipment for metaverse and human-AI (artificial intelligence) interfaces. To address the creep and relaxation issues associated with pressure-sensitive materials, a highly stable piezoresistive composite is proposed, using polyamide-imide (PAI) fibers as the matrix and in situ grafted-polymerized polyaniline (PANI) as the semi-conducting layer. The PAI with large rigid fluorenylidene groups exhibits a high glass transition temperature of 372 °C (PAI 5-5), which results in an extremely long relaxation time at room temperature and consequently offers outstanding anti-creep/relaxation performances. The enhancement of PAI-PANI interfacial bonding through in situ grafting improves the sensor reliably. The sensor presents high linear sensitivity of 35.3 kPa-1 over a pressure range of 0.2-20 kPa, outstanding repeatability, and excellent dynamic stability with only a 3.8% signal deviation through ≈10 000 cycles. Real-time visualization of pressure distribution is realized by sensor matrices, which demonstrate the capability of tactile gesture recognition on both flat and curved surfaces. The recognition of sitting postures is achieved by two 12 × 12 matrices facilitated by machine learning, which prompts the potential for the augmentation of smart driving.

A Force-Thermal-Magnetic Trimodal Flexible Sensor for Ultrafine Recognition of Metallic Materials

Humans possess the remarkable ability to perceive the intricate world by integrating multiple senses. However, the challenge of enabling humanoid robots to achieve multimodal sensing and fine recognition of metallic materials persists. In this study, we propose a flexible tactile sensor that mimics the sensory patterns of human skin, which is assembled by a flexible electromagnetic coil that is engraved on the surface of a polyimide substrate and porous MXene/CNT aerogel. This sensor is capable of detecting pressure, temperature, and inductive signals with minimal interference via three disparate response mechanisms of the piezoresistive sensing, the thermoelectric principle, and the electromagnetic induction effect, allowing the device with the abilities of sensing grasp forces and selectively identifying ferromagnetic and nonferromagnetic metals, which has a high accuracy rate of 99.2% in distinguishing mixed metals with varying ratios based on the fusion algorithm of multimodal sensory data. Further, the sensor was integrated on a humanoid robotic hand to demonstrate its recognition capacity of objects used in a kitchen setting and a simulated scenario of mineral exploration, achieving a remarkable ultrafine accuracy of 100% in distinguishing 16 common metal products. These findings will pave the way for humanoid robots to attain heightened levels of perception and recognition.

A High-Repeatability Three-Dimensional Force Tactile Sensing System for Robotic Dexterous Grasping and Object Recognition

Robotic devices with integrated tactile sensors can accurately perceive the contact force, pressure, sliding, and other tactile information, and they have been widely used in various fields, including human-robot interaction, dexterous manipulation, and object recognition. To address the challenges associated with the initial value drift, and to improve the durability and accuracy of the tactile detection for a robotic dexterous hand, in this study, a flexible tactile sensor is designed with high repeatability by introducing a supporting layer for pre-separation. The proposed tactile sensor has a detection range of 0-5 N with a resolution of 0.2 N, and the repeatability error is as relatively small as 1.5%. In addition, the response time of the proposed tactile sensor under loading and unloading conditions are 80 ms and 160 ms, respectively. Moreover, a three-dimensional force decoupling detection method is developed by distributing tactile sensor units on a non-coplanar robotic fingertip. Finally, using a backpropagation neural network, the classification and recognition processes of nine types of objects with different shapes and categories are realized, achieving an accuracy higher than 95%. The results show that the proposed three-dimensional force tactile sensing system could be beneficial for the delicate manipulation and recognition for robotic dexterous hands.

Highly stable and ultra-fast vibration-responsive flexible iontronic sensors for accurate acoustic signal recognition

Wearable verbal language servers function as sophisticated and effective tools for fostering intelligent interactions between humans and machines. In the realm of collecting acoustic vibration signals, flexible iontronic pressure sensors have demonstrated their efficacy by incorporating microstructures into the functional layer, resulting in heightened pressure sensitivity. However, the substantial viscosity of the integrated iontronic materials or the lack of bonding at the heterogeneous interface emerges as a significant hindrance to capacitance recovery, leading to sluggish response speeds and mechanical instability. Here, we address the issue by introducing hydrogen bonding between naturally microstructured protein micro-fibers and hydrophilic ionic hydrogel into the dielectric layer. Due to the good resilience of protein micro-fibers and the enahnced interfacial bonding, this flexible vibration sensor demonstrates outstanding performance characteristics, featuring exceptional signal stability, a high-pressure resolution of 522 pF kPa-1, an ultra-fast response time of 0.6 ms, and a relaxation time of 0.6 ms, with a limit of detection (LOD) of 0.12 Pa, making it well-suited for acoustic vibration acquisition. By using a one-dimensional convolutional neural network (1D-CNN) deep learning to process and recognize collected acoustic signals, our sensor achieved an impressive accuracy of 98.2%. These wearable vibration sensors exemplify promising versatile applications in biometric authentication, personalized services, and human-computer interaction.

Flexible Pressure, Humidity, and Temperature Sensors for Human Health Monitoring

The rapid advancements in artificial intelligence, micro-nano manufacturing, and flexible electronics technology have unleashed unprecedented innovation and opportunities for applying flexible sensors in healthcare, wearable devices, and human-computer interaction. The human body's tactile perception involves physical parameters such as pressure, temperature, and humidity, all of which play an essential role in maintaining human health. Inspired by the sensory function of human skin, many bionic sensors have been developed to simulate human skin's perception to various stimuli and are widely applied in health monitoring. Given the urgent requirements for sensing performance and integration of flexible sensors in the field of wearable devices and health monitoring, here is a timely overview of recent advances in pressure, humidity, temperature, and multi-functional sensors for human health monitoring. It covers the fundamental components of flexible sensors and categorizes them based on different response mechanisms, including resistive, capacitive, voltage, and other types. Specifically, the application of these flexible tactile sensors in the area of human health monitoring is highlighted. Based on this, an extended overview of recent advances in dual/triple-mode flexible sensors integrating pressure, humidity, and temperature tactile sensing is presented. Finally, the challenges and opportunities of flexible sensors are discussed.

Deep learning-assisted object recognition with hybrid triboelectric-capacitive tactile sensor

Tactile sensors play a critical role in robotic intelligence and human-machine interaction. In this manuscript, we propose a hybrid tactile sensor by integrating a triboelectric sensing unit and a capacitive sensing unit based on porous PDMS. The triboelectric sensing unit is sensitive to the surface material and texture of the grasped objects, while the capacitive sensing unit responds to the object's hardness. By combining signals from the two sensing units, tactile object recognition can be achieved among not only different objects but also the same object in different states. In addition, both the triboelectric layer and the capacitor dielectric layer were fabricated through the same manufacturing process. Furthermore, deep learning was employed to assist the tactile sensor in accurate object recognition. As a demonstration, the identification of 12 samples was implemented using this hybrid tactile sensor, and an recognition accuracy of 98.46% was achieved. Overall, the proposed hybrid tactile sensor has shown great potential in robotic perception and tactile intelligence.

Intelligent Song Recognition via a Hollow-Microstructure-Based, Ultrasensitive Artificial Eardrum

Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa-1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1-2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow-microstructure-based sensor, indicating its potential applications in human-machine interaction and wearable acoustical technologies.

A Multifunctional Tactile Sensory System for Robotic Intelligent Identification and Manipulation Perception

Humans recognize and manipulate objects relying on the multidimensional force features captured by the tactile sense of skin during the manipulation. Since the current sensors integrated in robots cannot support the robots to sense the multiple interaction states between manipulator and objects, achieving human-like perception and analytical capabilities remains a major challenge for service robots. Prompted by the tactile perception involved in robots performing complex tasks, a multimodal tactile sensory system is presented to provide in situ simultaneous sensing for robots when approaching, touching, and manipulating objects. The system comprises a capacitive sensor owning the high sensitivity of 1.11E-2 pF mm-1, a triboelectricity nanogenerator with the fast response speed of 30 ms, and a pressure sensor array capable of 3D force detection. By Combining transfer learning models, which fuses multimodal tactile information to achieve high-precision (up to 95%) recognition of the multi-featured targets such as random hardness and texture information under random sampling conditions, including random grasp force and velocity. This sensory system is expected to enhance the intelligent recognition and behavior-planning capabilities of autonomous robots when performing complex tasks in undefined surrounding environments.

Artificial olfactory memory system based on conductive metal-organic frameworks

The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots. Compared to active sensing devices, passive piezoelectric and triboelectric tactile sensors consume less power, but lack the capability to resolve static stimuli. Here, we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired, passive, and bio-friendly tactile sensors for resolving both static and dynamic stimuli. Specifically, to emulate the polarization process of natural sensory cells, conjugated polymers (including poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate), polyaniline, or polypyrrole) are controllably polarized into two opposite states to create artificial potential differences. The controllable and reversible polarization process of the conjugated polymers is fully in situ characterized. Then, a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference outputs. Compared with the currently existing tactile sensing devices, the developed tactile sensors feature distinct characteristics including fully organic composition, high sensitivity (up to 773 mV N-1), ultralow power consumption (nW), as well as superior bio-friendliness. As demonstrations, both single point tactile perception (surface texture perception and material property perception) and two-dimensional tactile recognitions (shape or profile perception) with high accuracy are successfully realized using self-defined machine learning algorithms. This tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

Reversible Molecule Interactions Enable Ultrastretchable and Recyclable Ionogels for Wearable Piezoionic Sensors

Ionogel-based piezoionic sensors feel motions and strains like human skin relying on reversible ion migrations under external mechanical stimulus and are of great importance to artificial intelligence. However, conventional ion-conductive polymers behave with degraded electrical and mechanical properties after thousands of strain cycles, and the discarded materials and devices become electronic wastes as well. Here, we develop ultrastretchable ionogels with superior electrical properties via the mediation of metal-organic frameworks, whose properties are attributed to reversible molecule interactions inside the material system. Ionogels present excellent mechanical properties with breaking elongation as high as 850%, exceeding most previously reported similar materials, and the high conductivity enables further application in sensor devices. In addition, our ionogels display superior recyclability because of the reversible physical and chemical interactions inside material molecules, which are eco-friendly to the environment. As a result, the ionogel-based piezoionic sensors deliver high sensitivity, flexibility, cyclic stability, and signal reliability, which are of great significance to wearable applications in human-motion detections such as throat vibration, facial expression, joint mobility, and finger movement. Our study paves the way for ultrastretchable and eco-friendly ionogel design for flexible electrochemical devices.

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.

Additively Manufactured Flexible Liquid Metal-Coated Self-Powered Magnetoelectric Sensors with High Design Freedom

Although additive manufacturing enables controllable structural design and customized performance for magnetoelectric sensors, their design and fabrication still require careful matching of the size and modulus between the magnetic and conductive components. Achieving magnetoelectric integration remains challenging, and the rigid coils limit the flexibility of the sensors. To overcome these obstacles, this study proposes a composite process combining selective laser sintering (SLS) and 3D transfer printing for fabricating flexible liquid metal-coated magnetoelectric sensors. The liquid metal forms a conformal conductive network on the SLS-printed magnetic lattice structure. Deformation of the structure alters the magnetic flux passing through it, thereby generating voltage. A reverse model segmentation and summation method is established to calculate the theoretical magnetic flux. The impact of the volume fraction, unit size, and height of the sensors on the voltage is studied, and optimization of these factors yields a maximum voltage of 45.6 µV. The sensor has excellent sensing performance with a sensitivity of 10.9 kPa-1 and a minimum detection pressure of 0.1 kPa. The voltage can be generated through various external forces. This work presents a significant advancement in fabricating liquid metal-based magnetoelectric sensors by improving their structural flexibility, magnetoelectric integration, and design freedom.

Zwitterionic Eutectogels with High Ionic Conductivity for Environmentally Tolerant and Self-Healing Triboelectric Nanogenerators

Eutectogels have garnered considerable attention for the development of wearable devices, owing to their inherent mechanical elasticity, ionic conductivity, affordability, and environmental compatibility. However, the low conductivity of existing eutectogels has impeded their progression in electronic applications. Here, we report a zwitterionic eutectogel with an impressive ionic conductivity of up to 15.7 mS cm-1. The incorporation of zwitterionic groups into the eutectogel creates ample mobile charges by dissociating the cation and anion of solvents, thereby yielding exceptional ionic conductivity. Moreover, the abundant electrostatic and hydrogen bonding interactions within the eutectogel endow it with prominent self-healing and adhesive properties. By integrating the eutectogel with a roughly patterned polydimethylsiloxane film, we have successfully constructed a triboelectric nanogenerator (TENG) with a maximum output power density of 112 mW m-2. This TENG is capable of generating stable electrical signals even in extreme temperature conditions ranging from -80 to 100 °C and effectively powering electronic devices. Furthermore, the assembled TENG displays high sensitivity as a self-powered sensor, enabling real-time and precise monitoring of signals derived from human motions. This study establishes a promising approach for the development of sustainable and multifunctional flexible electronics that are resilient in extreme environments.

Recent Advances in Self-Powered Wearable Flexible Sensors for Human Gaits Analysis

The rapid progress of flexible electronics has met the growing need for detecting human movement information in exoskeleton auxiliary equipment. This study provides a review of recent advancements in the design and fabrication of flexible electronics used for human motion detection. Firstly, a comprehensive introduction is provided on various self-powered wearable flexible sensors employed in detecting human movement information. Subsequently, the algorithms utilized to provide feedback on human movement are presented, followed by a thorough discussion of their methods and effectiveness. Finally, the review concludes with perspectives on the current challenges and opportunities in implementing self-powered wearable flexible sensors in exoskeleton technology.

Advances in Energy Harvesting Technologies for Wearable Devices

The development of wearable electronics is revolutionizing human health monitoring, intelligent robotics, and informatics. Yet the reliance on traditional batteries limits their wearability, user comfort, and continuous use. Energy harvesting technologies offer a promising power solution by converting ambient energy from the human body or surrounding environment into electrical power. Despite their potential, current studies often focus on individual modules under specific conditions, which limits practical applicability in diverse real-world environments. Here, this review highlights the recent progress, potential, and technological challenges in energy harvesting technology and accompanying technologies to construct a practical powering module, including power management and energy storage devices for wearable device developments. Also, this paper offers perspectives on designing next-generation wearable soft electronics that enhance quality of life and foster broader adoption in various aspects of daily life.

A Skin-Inspired High-Performance Tactile Sensor for Accurate Recognition of Object Softness

High-performance tactile sensors with skin-sensing properties are crucial for intelligent perception in next-generation smart devices. However, previous studies have mainly focused on the sensitivity and response range of tactile sensation while neglecting the ability to recognize object softness. Therefore, achieving a precise perception of the softness remains a challenge. Here, we report an integrated tactile sensor consisting of a central hole gradient structure pressure sensor and a planar structure strain sensor. The recognition of softness and tactile perception is achieved through the synergistic effect of pressure sensors that sense the applied pressure and strain sensors that recognize the strain of the target object. The results indicate that the softness evaluation parameter (SC) of the integrated structural tactile sensor increases from 0.14 to 0.47 along with Young's modulus of the object decreasing from 2.74 to 0.45 MPa, demonstrating accurate softness recognition. It also exhibits a high sensitivity of 10.55 kPa-1 and an ultrawide linear range of 0-1000 kPa, showing an excellent tactile sensing capability. Further, an intelligent robotic hand system based on integrated structural tactile sensors was developed, which can identify the softness of soft foam and glass and grasp them accurately, indicating human skin-like sensing and grasping capabilities.

Advanced Design of Soft Robots with Artificial Intelligence

A comprehensive review focused on the whole systems of the soft robotics with artificial intelligence, which can feel, think, react and interact with humans, is presented. The design strategies concerning about various aspects of the soft robotics, like component materials, device structures, prepared technologies, integrated method, and potential applications, are summarized. A broad outlook on the future considerations for the soft robots is proposed.

In recent years, breakthrough has been made in the field of artificial intelligence (AI), which has also revolutionized the industry of robotics. Soft robots featured with high-level safety, less weight, lower power consumption have always been one of the research hotspots. Recently, multifunctional sensors for perception of soft robotics have been rapidly developed, while more algorithms and models of machine learning with high accuracy have been optimized and proposed. Designs of soft robots with AI have also been advanced ranging from multimodal sensing, human–machine interaction to effective actuation in robotic systems. Nonetheless, comprehensive reviews concerning the new developments and strategies for the ingenious design of the soft robotic systems equipped with AI are rare. Here, the new development is systematically reviewed in the field of soft robots with AI. First, background and mechanisms of soft robotic systems are briefed, after which development focused on how to endow the soft robots with AI, including the aspects of feeling, thought and reaction, is illustrated. Next, applications of soft robots with AI are systematically summarized and discussed together with advanced strategies proposed for performance enhancement. Design thoughts for future intelligent soft robotics are pointed out. Finally, some perspectives are put forward.

Manipulating Hetero-Nanowire Films for Flexible and Multifunctional Thermoelectric Devices

Flexible thermoelectric devices hold significant promise in wearable electronics owing to their capacity for green energy generation, temperature sensing, and comfortable wear. However, the simultaneous achievement of excellent multifunctional sensing and power generation poses a challenge in these devices. Here, ordered tellurium-based hetero-nanowire films are designed for flexible and multifunctional thermoelectric devices by optimizing the Seebeck coefficient and power factor. The obtained devices can efficiently detect both object and environment temperature, thermal conductivity, heat proximity, and airflow. In addition, combining the thermoelectric units with radiative cooling materials exhibits remarkable thermal management capabilities, preventing device overheating and avoiding degradation in power generation. Impressively, this multifunctional electronics exhibits excellent resistance in extreme low earth orbit environments. The fabrication of such thermoelectric devices provides innovative insights into multimodal sensing and energy harvesting.

Research Progress and Application of Multimodal Flexible Sensors for Electronic Skin

In recent years, wearable electronic skin has garnered significant attention due to its broad range of applications in various fields, including personal health monitoring, human motion perception, human-computer interaction, and flexible display. The flexible multimodal sensor, as the core component of electronic skin, can mimic the multistimulus sensing ability of human skin, which is highly significant for the development of the next generation of electronic devices. This paper provides a summary of the latest advancements in multimodal sensors that possess two or more response capabilities (such as force, temperature, humidity, etc.) simultaneously. It explores the relationship between materials and multiple sensing capabilities, focusing on both active materials that are the same and different. The paper also discusses the preparation methods, device structures, and sensing properties of these sensors. Furthermore, it introduces the applications of multimodal sensors in human motion and health monitoring, as well as intelligent robots. Finally, the current limitations and future challenges of multimodal sensors will be presented.

A multifunctional flexible sensor based on PI-MXene/SrTiO3 hybrid aerogel for tactile perception

The inadequacy of tactile perception systems in humanoid robotic manipulators limits the breadth of available robotic applications. Here, we designed a multifunctional flexible tactile sensor for robotic fingers that provides capabilities similar to those of human skin sensing modalities. This sensor utilizes a novel PI-MXene/SrTiO3 hybrid aerogel developed as a sensing unit with the additional abilities of electromagnetic transmission and thermal insulation to adapt to certain complex environments. Moreover, polyimide (PI) provides a high-strength skeleton, MXene realizes a pressure-sensing function, and MXene/SrTiO3 achieves both thermoelectric and infrared radiation response behaviors. Furthermore, via the pressure response mechanism and unsteady-state heat transfer, these aerogel-derived flexible sensors realize multimodal sensing and recognition capabilities with minimal cross-coupling. They can differentiate among 13 types of hardness and four types of material from objects with accuracies of 94% and 85%, respectively, using a decision tree algorithm. In addition, based on the infrared radiation-sensing function, a sensory array was assembled, and different shapes of objects were successfully recognized. These findings demonstrate that this PI-MXene/SrTiO3 aerogel provides a new concept for expanding the multifunctionality of flexible sensors such that the manipulator can more closely reach the tactile level of the human hand. This advancement reduces the difficulty of integrating humanoid robots and provides a new breadth of application scenarios for their possibility.

Biomimetic Multimodal Receptors for Comprehensive Artificial Human Somatosensory System

Electronic skin (e-skin) capable of acquiring environmental and physiological information has attracted interest for healthcare, robotics, and human-machine interaction. However, traditional 2D e-skin only allows for in-plane force sensing, which limits access to comprehensive stimulus feedback due to the lack of out-of-plane signal detection caused by its 3D structure. Here, a dimension-switchable bioinspired receptor is reported to achieve multimodal perception by exploiting film kirigami. It offers the detection of in-plane (pressure and bending) and out-of-plane (force and airflow) signals by dynamically inducing the opening and reclosing of sensing unit. The receptor's hygroscopic and thermoelectric properties enable the sensing of humidity and temperature. Meanwhile, the thermoelectric receptor can differentiate mechanical stimuli from temperature by the voltage. The development enables a wide range of sensory capabilities of traditional e-skin and expands the applications in real life.

Flexible Tactile Sensors for 3D Force Detection

As tactile force sensing has become increasingly significant in the field of machine haptics, achieving multidimensional force sensing remains a challenge. We propose a 3D flexible force sensor that consists of an axisymmetric hemispherical protrusion and four equally sized quarter-circle electrodes. By simulating the device using a force and electrical field model, it has been found that the magnitude and direction of the force can be expressed through the voltage relationship of the four electrodes when the magnitude of the shear force remains constant and its direction varies within 0-360°. The experimental results show that a resolution of 15° can be achieved in the range 0-90°. Additionally, we installed the sensor on a robotic hand, enabling it to perceive the magnitude and direction of touch and grasp actions. Based on this, the designed 3D flexible tactile force sensor provides valuable insights for multidimensional force detection and applications.

Self-Powered Pressure-Temperature Bimodal Sensing Based on the Piezo-Pyroelectric Effect for Robotic Perception

Multifunctional sensors have played a crucial role in constructing high-integration electronic networks. Most of the current multifunctional sensors rely on multiple materials to simultaneously detect different physical stimuli. Here, we demonstrate the large piezo-pyroelectric effect in ferroelectric Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) single crystals for simultaneous pressure and temperature sensing. The outstanding piezoelectric and pyroelectric properties of PMN-PT result in rapid response speed and high sensitivity, with values of 46 ms and 28.4 nA kPa-1 for pressure sensing, and 1.98 s and 94.66 nC °C-1 for temperature detection, respectively. By leveraging the distinct differences in the response speed of piezoelectric and pyroelectric responses, the piezo-pyroelectric effect of PMN-PT can effectively detect pressure and temperature from mixed-force thermal stimuli, which enables a robotic hand for stimuli classification. With appealing multifunctionality, fast speed, high sensitivity, and compact structure, the proposed self-powered bimodal sensor therefore holds significant potential for high-performance artificial perception.

Highly Thermally Conductive Aramid Nanofiber Composite Films with Synchronous Visible/Infrared Camouflages and Information Encryption

The development of highly thermally conductive composites that combine visible light/infrared camouflage and information encryption has been endowed with great significance in facilitating the application of 5G communication technology in military fields. This work uses aramid nanofibers (ANF) as the matrix, hetero-structured silver nanowires@boron nitride nanosheets (AgNWs@BNNS) prepared by in situ growth as fillers, which are combined to fabricate sandwich structured thermally conductive and electrically insulating (BNNS/ANF)-(AgNWs@BNNS)-(BNNS/ANF) (denoted as BAB) composite films by "filtration self-assembly, air spraying, and hot-pressing" method. When the mass ratio of AgNWs@BNNS to BNNS is 1 : 1 and the total mass fraction is 50 wt %, BAB composite film has the maximum in-plane thermal conductivity coefficient (λ∥ of 10.36 W/(m ⋅ K)), excellent electrical insulation (breakdown strength and volume resistivity of 41.5 kV/mm and 1.21×1015 Ω ⋅ cm, respectively) and mechanical properties (tensile strength of 170.9 MPa). 50 wt % BAB composite film could efficiently reduce the equilibrium temperature of the central processing unit (CPU) working at full power, resulting in 7.0 °C lower than that of the CPU solely integrated with ANF directly. In addition, BAB composite film boasts adaptive visible light/infrared dual camouflage properties on cement roads and jungle environments, as well as the function of fast encryption of QR code information within 24 seconds.

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.

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.

Intuition-and-Tactile Bimodal Sensing Based on Artificial-Intelligence-Motivated All-Fabric Bionic Electronic Skin for Intelligent Material Perception

Developing electronic skins (e-skins) with extraordinary perception through bionic strategies has far-reaching significance for the intellectualization of robot skins. Here, an artificial intelligence (AI)-motivated all-fabric bionic (AFB) e-skin is proposed, where the overall structure is inspired by the interlocked bionics of the epidermis-dermis interface inside the skin, while the structural design inspiration of the dielectric layer derives from the branch-needle structure of conifers. More importantly, AFB e-skin achieves intuition sensing in proximity mode and tactile sensing in pressure mode based on the fringing and iontronic effects, respectively, and is simulated and verified through COMSOL finite element analysis. The proposed AFB e-skin in pressure mode exhibits maximum sensitivity of 15.06 kPa-1 (<50 kPa), linear sensitivity of 6.06 kPa-1 (50-200 kPa), and fast response/recovery time of 5.6 ms (40 kPa). By integrating AFB e-skin with AI algorithm, and with the support of material inference mechanisms based on dielectric constant and softness/hardness, an intelligent material perception system capable of recognizing nine materials with indistinguishable surfaces within one proximity-pressure cycle is established, demonstrating abilities that surpass human perception.

Age of Flexible Electronics: Emerging Trends in Soft Multifunctional Sensors

With the commercialization of first-generation flexible mobiles and displays in the late 2010s, humanity has stepped into the age of flexible electronics. Inevitably, soft multifunctional sensors, as essential components of next-generation flexible electronics, have attracted tremendous research interest like never before. This review is dedicated to offering an overview of the latest emerging trends in soft multifunctional sensors and their accordant future research and development (R&D) directions for the coming decade. First, key characteristics and the predominant target stimuli for soft multifunctional sensors are highlighted. Second, important selection criteria for soft multifunctional sensors are introduced. Next, emerging materials/structures and trends for soft multifunctional sensors are identified. Specifically, the future R&D directions of these sensors are envisaged based on their emerging trends, namely i) decoupling of multiple stimuli, ii) data processing, iii) skin conformability, and iv) energy sources. Finally, the challenges and potential opportunities for these sensors in future are discussed, offering new insights into prospects in the fast-emerging technology.

Harness High-Temperature Thermal Energy via Elastic Thermoelectric Aerogels

Despite notable progress in thermoelectric (TE) materials and devices, developing TE aerogels with high-temperature resistance, superior TE performance and excellent elasticity to enable self-powered high-temperature monitoring/warning in industrial and wearable applications remains a great challenge. Herein, a highly elastic, flame-retardant and high-temperature-resistant TE aerogel, made of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)/single-walled carbon nanotube (PEDOT:PSS/SWCNT) composites, has been fabricated, displaying attractive compression-induced power factor enhancement. The as-fabricated sensors with the aerogel can achieve accurately pressure stimuli detection and wide temperature range monitoring. Subsequently, a flexible TE generator is assembled, consisting of 25 aerogels connected in series, capable of delivering a maximum output power of 400 μW when subjected to a temperature difference of 300 K. This demonstrates its outstanding high-temperature heat harvesting capability and promising application prospects for real-time temperature monitoring on industrial high-temperature pipelines. Moreover, the designed self-powered wearable sensing glove can realize precise wide-range temperature detection, high-temperature warning and accurate recognition of human hand gestures. The aerogel-based intelligent wearable sensing system developed for firefighters demonstrates the desired self-powered and highly sensitive high-temperature fire warning capability. Benefitting from these desirable properties, the elastic and high-temperature-resistant aerogels present various promising applications including self-powered high-temperature monitoring, industrial overheat warning, waste heat energy recycling and even wearable healthcare.

Integrating In-Plane Thermoelectricity and Out-Plane Piezoresistivity for Fully Decoupled Temperature-Pressure Sensing

A flexible sensor that simultaneously senses temperature and pressure is crucial in various fields, such as human-machine interaction, artificial intelligence, and biomedical applications. Previous research has mainly focused on single-function flexible sensors for e-skins or smart devices, and integrated bimodal sensing of temperature and pressure without complex crosstalk decoupling algorithms remains challenging. In this work, a flexible bimodal sensor is proposed that utilizes spatial orthogonality between in-plane thermoelectricity and out-plane piezoresistivity, which enables fully decoupled temperature-pressure sensing. The proposed bimodal sensor exhibits a high sensitivity of 281.46 µV K-1 for temperature sensing and 2.181 kPa-1 for pressure sensing. In the bimodal sensing mode, the sensor exhibits negligible mutual interference, providing a measurement error of ± 7% and ± 8% for temperature and pressure, respectively, within a 120 kPa pressure range and a 40 K temperature variation. Additionally, simultaneous spatial mapping of temperature and pressure with a bimodal sensor array enables contact shape identification with enhanced accuracy beyond the limit imposed by the number of sensing units. The proposed integrated bimodal sensing strategy does not require complex crosstalk decoupling algorithms, which represents a significant advancement in flexible sensors for applications that necessitate simultaneous sensing of temperature and pressure.

Split-Type Magnetic Soft Tactile Sensor with 3D Force Decoupling

Tactile sensory organs for sensing 3D force, such as human skin and fish lateral lines, are indispensable for organisms. With their sensory properties enhanced by layered structures, typical sensory organs can achieve excellent perception as well as protection under frequent mechanical contact. Here, inspired by these layered structures, a split-type magnetic soft tactile sensor with wireless 3D force sensing and a high accuracy (1.33%) fabricated by developing a centripetal magnetization arrangement and theoretical decoupling model is introduced. The 3D force decoupling capability enables it to achieve a perception close to that of human skin in multiple dimensions without complex calibration. Benefiting from the 3D force decoupling capability and split design with a long effective distance (>20 mm), several sensors are assembled in air and water to achieve delicate robotic operation and water flow-based navigation with an offset <1.03%, illustrating the extensive potential of magnetic tactile sensors in flexible electronics, human-machine interactions, and bionic robots.

Touchless Thermosensation Enabled by Flexible Infrared Photothermoelectric Detector for Temperature Prewarning Function of Electronic Skin

Artificial skin, endowed with the capability to perceive thermal stimuli without physical contact, will bring innovative interactive experiences into smart robotics and augmented reality. The implementation of touchless thermosensation, responding to both hot and cold stimuli, relies on the construction of a flexible infrared detector operating in the long-wavelength infrared range to capture the spontaneous thermal radiation. This imposes rigorous requirements on the photodetection performance and mechanical flexibility of the detector. Herein, a flexible and wearable infrared detector is presented, on basis of the photothermoelectric coupling of the tellurium-based thermoelectric multilayer film and the infrared-absorbing polyimide substrate. By suppressing the optical reflection loss and aligning the destructive interference position with the absorption peak of polyimide, the fabricated thermopile detector exhibits high sensitivity to the thermal radiation over a broad source temperature range from -50 to 110 °C, even capable of resolving 0.05 °C temperature change. Spatially resolved radiation distribution sensing is also achieved by constructing an integrated thermopile array. Furthermore, an established temperature prewarning system is demonstrated for soft robotic gripper, enabling the identification of noxious thermal stimuli in a contactless manner. A feasible strategy is offered here to integrate the infrared detection technique into the sensory modality of electronic skin.

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.

Robust and sensitive conductive nanocomposite hydrogel with bridge cross-linking-dominated hierarchical structural design

Conductive hydrogels have a remarkable potential for applications in soft electronics and robotics, owing to their noteworthy attributes, including electrical conductivity, stretchability, biocompatibility, etc. However, the limited strength and toughness of these hydrogels have traditionally impeded their practical implementation. Inspired by the hierarchical architecture of high-performance biological composites found in nature, we successfully fabricate a robust and sensitive conductive nanocomposite hydrogel through self-assembly-induced bridge cross-linking of MgB2 nanosheets and polyvinyl alcohol hydrogels. By combining the hierarchical lamellar microstructure with robust molecular B─O─C covalent bonds, the resulting conductive hydrogel exhibits an exceptional strength and toughness. Moreover, the hydrogel demonstrates exceptional sensitivity (response/relaxation time, 20 milliseconds; detection lower limit, ~1 Pascal) under external deformation. Such characteristics enable the conductive hydrogel to exhibit superior performance in soft sensing applications. This study introduces a high-performance conductive hydrogel and opens up exciting possibilities for the development of soft electronics.

Biomimetic Wearable Sensors: Emerging Combination of Intelligence and Electronics

Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.

Porous nanocomposites with enhanced intrinsic piezoresistive sensitivity for bioinspired multimodal tactile sensors

In this work, we propose porous fluororubber/thermoplastic urethane nanocomposites (PFTNs) and explore their intrinsic piezoresistive sensitivity to pressure. Our experiments reveal that the intrinsic sensitivity of the PFTN-based sensor to pressure up to 10 kPa increases up to 900% compared to the porous thermoplastic urethane nanocomposite (PTN) counterpart and up to 275% compared to the porous fluororubber nanocomposite (PFN) counterpart. For pressures exceeding 10 kPa, the resistance-pressure relationship of PFTN follows a logarithmic function, and the sensitivity is 221% and 125% higher than that of PTN and PFN, respectively. With the excellent intrinsic sensitivity of the thick PFTN film, a single sensing unit with integrated electrode design can imitate human skin for touch detection, pressure perception and traction sensation. The sensing range of our multimodal tactile sensor reaches ~150 Pa, and it exhibits a linear fit over 97% for both normal pressure and shear force. We also demonstrate that an electronic skin, made of an array of sensing units, is capable of accurately recognizing complex tactile interactions including pinch, spread, and tweak motions.

Soft touchless sensors and touchless sensing for soft robots

Soft robots are characterized by their mechanical compliance, making them well-suited for various bio-inspired applications. However, the challenge of preserving their flexibility during deployment has necessitated using soft sensors which can enhance their mobility, energy efficiency, and spatial adaptability. Through emulating the structure, strategies, and working principles of human senses, soft robots can detect stimuli without direct contact with soft touchless sensors and tactile stimuli. This has resulted in noteworthy progress within the field of soft robotics. Nevertheless, soft, touchless sensors offer the advantage of non-invasive sensing and gripping without the drawbacks linked to physical contact. Consequently, the popularity of soft touchless sensors has grown in recent years, as they facilitate intuitive and safe interactions with humans, other robots, and the surrounding environment. This review explores the emerging confluence of touchless sensing and soft robotics, outlining a roadmap for deployable soft robots to achieve human-level dexterity.

Micropyramid Array Bimodal Electronic Skin for Intelligent Material and Surface Shape Perception Based on Capacitive Sensing

Developing electronic skins (e-skins) that are comparable to or even beyond human tactile perception holds significant importance in advancing the process of intellectualization. In this context, a machine-learning-motivated micropyramid array bimodal (MAB) e-skin based on capacitive sensing is reported, which enables spatial mapping applications based on bimodal sensing (proximity and pressure) implemented via fringing and iontronic effects, such as contactless measurement of 3D objects and contact recognition of Braille letters. Benefiting from the iontronic effect and single-micropyramid structure, the MAB e-skin in pressure mode yields impressive features: a maximum sensitivity of 655.3 kPa-1 (below 0.5 kPa), a linear sensitivity of 327.9 kPa-1 (0.5-15 kPa), and an ultralow limit of detection of 0.2 Pa. With the assistance of multilayer perceptron and convolutional neural network, the MAB e-skin can accurately perceive 6 materials and 10 surface shapes based on the training and learning using the collected datasets from proximity and pressure modes, thus allowing it to achieve the precise perception of different objects within one proximity-pressure cycle. The development of this MAB e-skin opens a new avenue for robotic skin and the expansion of advanced applications.

Micro-/Nanohierarchical Structures Physically Engineered on Surfaces: Analysis and Perspective

The high demand for micro-/nanohierarchical structures as components of functional substrates, bioinspired devices, energy-related electronics, and chemical/physical transducers has inspired their in-depth studies and active development of the related fabrication techniques. In particular, significant progress has been achieved in hierarchical structures physically engineered on surfaces, which offer the advantages of wide-range material compatibility, design diversity, and mechanical stability, and numerous unique structures with important niche applications have been developed. This review categorizes the basic components of hierarchical structures physically engineered on surfaces according to function/shape and comprehensively summarizes the related advances, focusing on the fabrication strategies, ways of combining basic components, potential applications, and future research directions. Moreover, the physicochemical properties of hierarchical structures physically engineered on surfaces are compared based on the function of their basic components, which may help to avoid the bottlenecks of conventional single-scale functional substrates. Thus, the present work is expected to provide a useful reference for scientists working on multicomponent functional substrates and inspire further research in this field.

Oblique Pyramid Microstructure-Patterned Flexible Sensors for Pressure and Visual Temperature Sensing

Flexible tactile sensors have garnered considerable attention in diverse fields. Among them, the sensors integrated with multifunctional tactile sensing features can simultaneously detect various stimuli, such as pressure and temperature, and are thus suitable for practical applications. However, integrating multiple sensor modalities within a solitary pixel invariably encounters various limitations encompassing interplay among disparate sensors, intricate structural design demands, and the complexities and high costs associated with fabrication. Herein, we harness a visual sensing mechanism to synergize with electric sensors, thereby realizing a tactile sensor reliant on thermochromic microstructures for simultaneous pressure and temperature sensing. The thermal distribution could be easily displayed by the color change of the sensor, avoiding inference between the sensing units, which is beneficial for low-cost mass fabrication. A capacitor sensor with dual-scale oblique pyramid microstructures in its dielectric layer is used for the pressure sensing function, resulting in improved sensitivity and an extended measurement range. This innovative tactile sensor design offers insights into tactile sensing mechanisms, paving the way for cost-effective, high-performance, and multimodal sensor fabrication.

Self-Powered Stretchable Sensor Arrays Exhibiting Magnetoelasticity for Real-Time Human-Machine Interaction

Stretchable strain sensors are highly desirable for human motion monitoring, and can be used to build new forms of bionic robots. However, the current use of flexible strain gauges is hindered by the need for an external power supply, and the demand for long-term operation. Here, a new flexible self-powered strain sensor system based on an electromagnetic generator that possesses a high stretchability in excess of 150%, a short response time of 30 ms, and an excellent linearity (R2  > 0.98), is presented. Based on this new form of sensor, a human-machine interaction system is designed to achieve remote control of a robot hand and vehicle using a human hand, which provides a new scheme for real-time gesture interaction.

Printing conformal and flexible copper networks for multimodal pressure and flow sensing

Flexible multimodal sensors with ultrasensitive detection capabilities are an indispensable component of wearable electronics and are highly sought-after involving a wide range of signal monitoring such as artificial skin and soft robotics. Here we report a flexible and wireless multimodal sensor using low-temperature additive manufacturing of copper nanoplates on elastic polyurethane substrates for temperature, pressure, and flow monitoring. The positive temperature coefficient and piezoresistive performance of the copper nanoplate network translates to a reliable temperature, steady-state and dynamic pressure/flow sensing for detecting pressures as small as 0.64 Pa with a response time of 130 ms, as well as velocity detection ranging from 2.5-6.8 m s-1. Additionally, by incorporating a printed antenna, it enables a self-powered, battery-free system, offering a wireless readout of printed multimodal sensors with superior real-time sensing performance in conjunction with wearable flexibility.

Synergy of Organic/Inorganic and Inner/Outer Cooperative Conductive Networks in Polydimethylsiloxane-Based Porous Foam on High-Performance Flexible Sensors

The development of low-cost and high-performance flexible sensor materials is crucial for the advancement of wearable electronic devices, medical monitoring, and human-machine interfaces. In this study, a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)-coated multiwalled carbon nanotube (MWCNT)-reinforced polydimethylsiloxane (PDMS) composite foam with a uniform organic/inorganic and inner/outer cooperative conductive network was developed to detect tensile and compressive forces. The study demonstrates that the internally cross-linked MWCNTs and PEDOT:PSS coatings within the foam framework play a crucial role in the porous structure and sensing properties of the composite foam. Due to the excellent hierarchical pore structure and dual-channel electronic pathway of the PP@MWCNTs/PDMS foam, the sensor exhibited not only high sensitivity to small pressures but also notable perception capability within the stretchable range. It also maintained excellent stability during multiple stretching and compression loading cycles. In terms of applications, the sensor could be used not only to monitor external stimuli and detect subtle movements within the human body in the field of wearable monitoring but also to sense spatial pressure distribution, which validates its potential in the development of flexible wearable sensing devices.