Microstructured Polyelectrolyte Elastomer-Based Ionotronic Sensors with High Sensitivities and Excellent Stability for Artificial Skins

Flexible iontronic sensing

The emerging flexible iontronic sensing (FITS) technology has introduced a novel modality for tactile perception, mimicking the topological structure of human skin while providing a viable strategy for seamless integration with biological systems. With research progress, FITS has evolved from focusing on performance optimization and structural enhancement to a new phase of integration and intelligence, positioning it as a promising candidate for next-generation wearable devices. Therefore, a review from the perspective of technological development trends is essential to fully understand the current state and future potential of FITS devices. In this review, we examine the latest advancements in FITS. We begin by examining the sensing mechanisms of FITS, summarizing research progress in material selection, structural design, and the fabrication of active and electrode layers, while also analysing the challenges and bottlenecks faced by different segments in this field. Next, integrated systems based on FITS devices are reviewed, highlighting their applications in human-machine interaction, healthcare, and environmental monitoring. Additionally, the integration of artificial intelligence into FITS is explored, focusing on optimizing front-end device design and improving the processing and utilization of back-end data. Finally, building on existing research, future challenges for FITS devices are identified and potential solutions are proposed.

Octopus Tentacle-Inspired In-Sensor Adaptive Integral for Edge-Intelligent Touch Intention Recognition

Electronics continue to drive technological innovation and diversified applications. To ensure efficiency and effectiveness across various interactive contexts, the ability to adjust operating functions or parameters according to environmental shifts or user requirements is highly desirable. However, due to the inherent limitations of nonadaptive device structures and materials, the current development of touch electronics faces challenges, e.g., limited hardware resources, poor adaptability, weak deformation stability, and bottlenecks in sensing data processing. Here, a reconfigurable and adaptive intelligent (RAI) touch sensor is proposed, inspired by octopus's tentacle cognitive behavior. It realizes remarkable deformability and highly efficient multitouch interactions. The geometric progression structure of the sensing element equips the RAI touch sensor with a unique integrated-in-sensing mechanism and programmable logic. This greatly compresses sensing data dimensionality at the edge, yielding concise and undistorted interactive signals. By leveraging the advantages of hard-soft bonding and interface modulation of functional materials, the adaptability is achieved with a 200% strain range a 180° twist tolerance, and exceptional deformation stability of >10 000 cycles. The diverse application-specific configurations of the RAI touch sensor, enable a dynamic intention recognition accuracy of over 99%, advancing next-generation Internet of Things and edge computing research and innovation.

Polyelectrolyte-based wireless and drift-free iontronic sensors for orthodontic sensing

The real-time monitoring of health conditions of humans is a long-lasting topic, but there are two major challenges. First, many biomedical applications accept only implanted sensors. Second, tissue-like soft sensors often suffer from viscoelasticity-induced signal drift, causing inaccurate measurements. Here, we report a wireless and drift-free sensory system enabled by a low-creep polyelectrolyte elastomer. The system consists of the iontronic pressure sensors incorporating inductance-capacitance (LC) oscillators, exhibiting combined low drift ratio, high Q factor, high robustness to interferences, and wide-range measurement, superior to other capacitive sensors using regular dielectrics or ionogels. We have recorded 14-day orthodontic loads of two subjects using the system, showing pressure decreasing from 300 to 50 kPa and torque from 12.5 to 0.5 N·mm. The wireless, drift-free sensory system may be extended to other implants for long-term and accurate sensing.

Hierarchical Iontronic Flexible Sensor with High Sensitivity over Ultrabroad Range Enabled by Equilibration of Microstructural Compressibility and Stability

Despite improved sensitivity of iontronic pressure sensors with microstructures, structural compressibility and stability issues hinder achieving exceptional sensitivity across a wide pressure range. Herein, the interplay between ion concentration, mechanical properties, structural geometry, and aspect ratio (AR) on the sensitivity of lithium bis(trifluoromethanesulfonyl) imide/thermoplastic polyurethane (LiTFSI/TPU) ionogel is delved into. The results indicate that cones exhibit superior compressibility compared to pyramids and hemispheres, manifesting in an enhanced sensitivity toward the LiTFSI/TPU ionogel. Subsequently, by strategically combining cones with varying ARs, a harmonious balance between structural stability and compressibility is achieved, culminating in the fabrication of hierarchical iontronic flexible sensors (HIFS). Remarkably, HIFS-III with a three-level hierarchical conical microstructure demonstrates a preeminent sensitivity of 127.65 kPa-1 within ∼500 kPa. Even within the ultrabroad pressure range of 1500-3000 kPa, the sensitivity remains exceeding 10 kPa-1. Furthermore, HIFS-III boasts swift response and relaxation times (∼11 and 18 ms, respectively), a low detection limit (∼6.35 Pa), as well as remarkable durability (15,000 cycles). The exceptional sensing capabilities of HIFS-III underscore its emergence as a promising high-performance sensing and feedback solution tailored for applications in human-machine interaction and e-skin.

Advanced Morphological and Material Engineering for High-Performance Interfacial Iontronic Pressure Sensors

High-performance flexible pressure sensors are crucial for applications such as wearable electronics, interactive systems, and healthcare technologies. Among these, iontronic pressure sensors have garnered particular attention due to their superior sensitivity, enabled by the giant capacitance variation of the electric double layer (EDL) at the ionic-electronic interface under deformation. Key advancements, such as incorporating microstructures into ionic layers and employing diverse materials, have significantly improved sensor properties like sensitivity, accuracy, stability, and response time. This review highlights advancements in flexible EDL pressure sensors, focusing on structural designs and material engineering. These strategies are tailored to optimize key metrics such as sensitivity, detection limit, linearity, stability, response speed, hysteresis, transparency, wearability, selectivity, and multifunctionality. Key fabrication techniques, including micropatterning and externally assisted methods, are reviewed, along with strategies for sensor comparison and guidelines for selecting appropriate sensors. Emerging applications in healthcare, environmental and aerodynamic sensing, human-machine interaction, robotics, and machine learning-assisted intelligent sensing are explored. Finally, this review discusses the challenges and future directions for advancing EDL-based pressure sensors.

Cilia-Inspired Bionic Tactile E-Skin: Structure, Fabrication and Applications

The rapid advancement of tactile electronic skin (E-skin) has highlighted the effectiveness of incorporating bionic, force-sensitive microstructures in order to enhance sensing performance. Among these, cilia-like microstructures with high aspect ratios, whose inspiration is mammalian hair and the lateral line system of fish, have attracted significant attention for their unique ability to enable E-skin to detect weak signals, even in extreme conditions. Herein, this review critically examines recent progress in the development of cilia-inspired bionic tactile E-skin, with a focus on columnar, conical and filiform microstructures, as well as their fabrication strategies, including template-based and template-free methods. The relationship between sensing performance and fabrication approaches is thoroughly analyzed, offering a framework for optimizing sensitivity and resilience. We also explore the applications of these systems across various fields, such as medical diagnostics, motion detection, human-machine interfaces, dexterous robotics, near-field communication, and perceptual decoupling systems. Finally, we provide insights into the pathways toward industrializing cilia-inspired bionic tactile E-skin, aiming to drive innovation and unlock the technology's potential for future applications.

Sunflower-like self-sustainable plant-wearable sensing probe

Powering and communicating with wearable devices on bio-interfaces is challenging due to strict weight, size, and resource constraints. This study presents a sunflower-like plant-wearable sensing device that harnesses solar energy, achieving complete energy self-sustainability for long-term monitoring of plant sap flow, a crucial indicator of plant health. It features foldable solar panels along with all essential flexible electronic components, resulting in a compact system that is lightweight enough for small plants. To tackle the low-energy density of solar power, we developed an ultralow-energy light communication mechanism inspired by fireflies. Together with unmanned aerial vehicles and deep learning algorithms, this approach enables efficient data retrieval from multiple devices across large agricultural fields. With its simple deployment, it shows great potential as a low-cost plant phenotyping tool. We believe our energy and communication solution for wearable devices can be extended to similar resource-limited and challenging scenarios, leading to exciting applications.

Enabling High Strength and Toughness Polyurethane through Disordered-Hydrogen Bonds for Printable, Recyclable, Ultra-Fast Responsive Capacitive Sensors

The rapid advancement of smart, flexible electronic devices has paralleled a surge in electronic waste (e-waste), exacerbating massive resource depletion and serious environmental pollution. Recyclable materials are extensively investigated to address these challenges. Herein, this study designs a unique polyurethane (SPPUs) with ultra-high strength up to 60 MPa and toughness of 360 MJ m-3. This synthetic SPPUs can be fully recycled at room temperature by using green solvents of ethanol. Accordingly, the resultant SPPU-Ni composites, created by mixing the ethanol-dissolved SPPUs solution with nickel (Ni) powder, effectively combine the flexibility and recyclability of SPPUs with the electrical conductivity of the nickel filler. Notably, this work develops the printable capacitive sensors (PCBS) through transcribing the paste of SPPUs-Ni slurry onto PET film and paper using screen-printing technology. The devised PCBS have fast response time ≈50 ms, high resolution, and multiple signal recognition capabilities. Remarkably, SPPUs and Ni powder can be fully recycled by only dissolving the waste PCBS in ethanol. This work offers a sustainable solution to the growing e-waste problem in recyclable flexible electronics.

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.

Microbubble-based fabrication of resilient porous ionogels for high-sensitivity pressure sensors

High-sensitivity flexible pressure sensors have obtained extensive attention because of their expanding applications in e-skins and wearable medical devices for various disease diagnoses. As the representative candidate for these sensors, the iontronic microstructure has been widely proven to enhance sensation behaviors such as the sensitivity and limits of detection. However, the fast and tunable fabrication of ionic-porous sensing elastomers remains challenging because of the current template-dissolved or 3D printing methods. Here, we report a microbubble-based fabrication process that enables microporous and resilient-compliance ionogels for high-sensitivity pressure sensors. Periodic motion sliding results in a relative velocity between the imported airflow and the fluid solution, converts the airflow to microbubbles in the high-viscosity ionic fluid and promptly solidifies the fluid into a porous ionogel under ultraviolet exposure. The ultrahigh porosity of up to 95% endows the porous ionogel with superelasticity and a Young's modulus near 7 kPa. Due to the superelastic compliance and iontronic electrical double-layer effect, the porous ionogel packaged into two electrodes endows the pressure sensor with high sensitivity (684.4 kPa-1) over an ultrabroad range (~1 MPa) and a high-pressure resolution of 0.46%. Furthermore, the pressure sensor successfully captures high-yield broad-range signals from the fingertip low-pressure pulses (<1 kPa) to foot high-pressure activities (>500 kPa), even the grasping force of soft machine hands via an array-scanning circuit during object recognition. This microbubble-based fabrication process for porous ionogels paves the way for designing wearable sensors or permeable electronics to monitor and diagnose various diseases.

Crystallization Control of Anionic Thiacalixarenes on Silicon Surface Coated with Cationic Poly(ethyleneimine)

Surface modification of solid substrates with organic molecules and polyelectrolytes is a promising strategy toward advanced soft materials due to the control of molecular arrangement and supramolecular organization; however, understanding the nature of interactions within the assembly is challenging. Here a facile approach to the control of the architecture of calixarene macrocycles on soft surfaces is presented through the interplay of weak interactions involving a solid silicon substrate, a cationic polyelectrolyte layer, and anionic sulfonatothiacalix[4]arene (STCA). Topological analysis of atomic force microscopy (AFM) images of STCA on silicon, as well as silicon wafers modified with neutral polyethylenimine (PEI) and cationic PEI-H+, indicates different surface morphology and assembly behavior of STCA on such substrates. Drop-casting a calixarene solution onto silicon induces the formation of chaotically oriented needle crystals. When there is globular PEI, a nucleation point for the STCA crystals is formed on the polyelectrolyte surface, which grows into rosette structures. In contrast, protonated PEI with a chain-like structure alters the self-organization of STCA on silicon surfaces, leading to a dense uniform fiber-like network. Density functional theory modeling of the system components' self-assembly reveals thermodynamically favorable face-to-face antiparallel aggregation of STCA monomers and contribution of H-bonding into PEI(PEI-H+)-STCA and Si-STCA association.

From materials to structures: a holistic examination of achieving linearity in flexible pressure sensors

As a pivotal category in the realm of electronics skins, flexible pressure sensors have become a focal point due to their diverse applications such as robotics, aerospace industries, and wearable devices. With the growing demands for measurement accuracy, data reliability, and electrical system compatibility, enhancing sensor's linearity has become increasingly critical. Analysis shows that the nonlinearity of flexible sensors primarily originates from mechanical nonlinearity due to the nolinear deformation of polymers and electrical nonlinearity caused by changes in parameters such as resistance. These nonlinearities can be mitigated through geometric design, material design or combination of both. This work reviews linear design strategies for sensors from the perspectives of structure and materials, covering the following main points: (a) an overview of the fundamental working mechanisms for various sensors; (b) a comprehensive explanation of different linear design strategies and the underlying reasons; (c) a detailed review of existing work employing these strategies and the achieved effects. Additionally, this work delves into diverse applications of linear flexible pressure sensors, spanning robotics, safety, electronic skin, and health monitoring. Finally, existing constraints and future research prospects are outlined to pave the way for the further development of high-performance flexible pressure sensors.

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.

Scalable Layered Heterogeneous Hydrogel Fibers with Strain-Induced Crystallization for Tough, Resilient, and Highly Conductive Soft Bioelectronics

The advancement of soft bioelectronics hinges critically on the electromechanical properties of hydrogels. Despite ongoing research into diverse material and structural strategies to enhance these properties, producing hydrogels that are simultaneously tough, resilient, and highly conductive for long-term, dynamic physiological monitoring remains a formidable challenge. Here, a strategy utilizing scalable layered heterogeneous hydrogel fibers (LHHFs) is introduced that enables synergistic electromechanical modulation of hydrogels. High toughness (1.4 MJ m-3) and resilience (over 92% recovery from 200% strain) of LHHFs are achieved through a damage-free toughening mechanism that involves dense long-chain entanglements and reversible strain-induced crystallization of sodium polyacrylate. The unique symmetrical layered structure of LHHFs, featuring distinct electrical and mechanical functional layers, facilitates the mixing of multi-walled carbon nanotubes to significantly enhance electrical conductivity (192.7 S m-1) without compromising toughness and resilience. Furthermore, high-performance LHHF capacitive iontronic strain/pressure sensors and epidermal electrodes are developed, capable of accurately and stably capturing biomechanical and bioelectrical signals from the human body under long-term, dynamic conditions. The LHHF offers a promising route for developing hydrogels with uniquely integrated electromechanical attributes, advancing practical wearable healthcare applications.

Flexible Artificial Tactility with Excellent Robustness and Temperature Tolerance Based on Organohydrogel Sensor Array for Robot Motion Detection and Object Shape Recognition

Hydrogel-based flexible artificial tactility is equipped to intelligent robots to mimic human mechanosensory perception. However, it remains a great challenge for hydrogel sensors to maintain flexibility and sensory performances during cyclic loadings at high or low temperatures due to water loss or freezing. Here, a flexible robot tactility is developed with high robustness based on organohydrogel sensor arrays with negligent hysteresis and temperature tolerance. Conductive polyaniline chains are interpenetrated through a poly(acrylamide-co-acrylic acid) network with glycerin/water mixture with interchain electrostatic interactions and hydrogen bonds, yielding a high dissipated energy of 1.58 MJ m-3, and ultralow hysteresis during 1000 cyclic loadings. Moreover, the binary solvent provides the gels with outstanding tolerance from -100 to 60 °C and the organohydrogel sensors remain flexible, fatigue resistant, conductive (0.27 S m-1), highly strain sensitive (GF of 3.88) and pressure sensitive (35.8 MPa-1). The organohydrogel sensor arrays are equipped on manipulator finger dorsa and pads to simultaneously monitor the finger motions and detect the pressure distribution exerted by grasped objects. A machine learning model is used to train the system to recognize the shape of grasped objects with 100% accuracy. The flexible robot tactility based on organohydrogels is promising for novel intelligent robots.

A Flexible Smart Healthcare Platform Conjugated with Artificial Epidermis Assembled by Three-Dimensionally Conductive MOF Network for Gas and Pressure Sensing

The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin's three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu3(HHTP)2 particles onto the hollow spherical Ti3C2Tx surface, aiming to concurrently emulate the spinous and granular layers of the skin's epidermis. The bionic Ti3C2Tx@Cu3(HHTP)2 exhibits independent NO2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.

Highly Stretchable, Transparent, Self-Healing Ion-Conducting Elastomers for Long-Term Reliable Human Motion Detection

The flexible electronic sensor is a critical component of wearable devices, generally requiring high stretchability, excellent transmittance, conductivity, self-healing capability, and strong adhesion. However, designing ion-conducting elastomers meeting all these requirements simultaneously remains a challenge. In this study, a novel approach is presented to fabricate highly stretchable, transparent, and self-healing ion-conducting elastomers, which are synthesized via photo-polymerization of two polymerizable deep eutectic solvents (PDESs) monomers, i.e., methacrylic acid (MAA)/choline chloride (ChCl) and itaconic acid (IA)/ChCl. The as-prepared ion-conducting elastomers possess outstanding properties, including high transparency, conductivity, and the capability to adhere to various substrates. The elastomers also demonstrate ultra-stretchability (up to 3900%) owing to a combination of covalent cross-linking and noncovalent cross-linking. In addition, the elastomers can recover up to 3250% strain and over 94.5% of their original conductivity after self-healing at room temperature for 5 min, indicating remarkable mechanical and conductive self-healing abilities. When utilized as strain sensors to monitor real-time motion of human fingers, wrist, elbow, and knee joints, the elastomers exhibit stable and strong repetitive electrical signals, demonstrating excellent sensing performance for large-scale movements of the human body. It is anticipated that these ion-conducting elastomers will find promising applications in flexible and wearable electronics.

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

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

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

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

Creep-free polyelectrolyte elastomer for drift-free iontronic sensing

Artificial pressure sensors often use soft materials to achieve skin-like softness, but the viscoelastic creep of soft materials and the ion leakage, specifically for ionic conductors, cause signal drift and inaccurate measurement. Here we report drift-free iontronic sensing by designing and copolymerizing a leakage-free and creep-free polyelectrolyte elastomer containing two types of segments: charged segments having fixed cations to prevent ion leakage and neutral slippery segments with a high crosslink density for low creep. We show that an iontronic sensor using the polyelectrolyte elastomer barely drifts under an ultrahigh static pressure of 500 kPa (close to its Young's modulus), exhibits a drift rate two to three orders of magnitude lower than that of the sensors adopting conventional ionic conductors and enables steady and accurate control for robotic manipulation. Such drift-free iontronic sensing represents a step towards highly accurate sensing in robotics and beyond.

Screen-Printable Iontronic Pressure Sensor with Thermal Expansion Microspheres for Pulse Monitoring

Constructing microstructures to improve the sensitivity of flexible pressure sensors is an effective approach. However, the preparation of microstructures usually involves inverted molds or subtractive manufacturing methods, which are difficult in large-scale (e.g., in screen printing) preparation. To solve this problem, we introduced thermally expandable microspheres for screen printing to fabricate flexible sensors. Thermally expandable microspheres can be constructed into microstructures by simple heating after printing, which simplifies the microstructure fabrication step. In addition, the added microspheres can also be used as ionic liquid reservoir materials to further increase the capacitance change and improve the sensitivity. The prepared sensors exhibited superior performance, including ultrahigh sensitivity (Smax = 49999.5 kPa-1) and wide detection range (0-350 kPa). Even after 30,000 cycles at a high pressure of 300 kPa and a low pressure of 30 kPa, the sensor showed minimal signal degradation, demonstrating long-term cycling stability. In order to verify the practical potential of the sensors, we performed human radial artery beat detection experiments using these sensors. The variations in the intensity of the 3D radial artery pulse wave can be observed very clearly, which is important for human health monitoring. The above demonstrates that our strategy can provide an effective approach for the large-scale preparation of high-performance flexible pressure sensors.

Marangoni-driven deterministic formation of softer, hollow microstructures for sensitivity-enhanced tactile system

Microengineering the dielectric layers with three-dimensional microstructures has proven effective in enhancing the sensitivity of flexible pressure sensors. However, the widely employed geometrical designs of solid microstructures exhibit limited sensitivity over a wide range of pressures due to their inherent but undesired structural compressibility. Here, a Marangoni-driven deterministic formation approach is proposed for fabricating hollow microstructures, allowing for greater deformation while retarding structural stiffening during compression. Fluid convective deposition enables solute particles to reassemble in template microstructures, controlling the interior cavity with a void ratio exceeding 90%. The hollow micro-pyramid sensor exhibits a 10-fold sensitivity improvement across wider pressure ranges over the pressure sensor utilizing solid micro-pyramids, and an ultra-low detect limit of 0.21 Pa. With the advantages of facilitation, scalability, and large-area compatibility, such an approach for hollow microstructures can be expanded to other sensor types for superior performance and has considerable potential in robotic tactile and epidermal devices.