Contact-Resistance-Free Stretchable Strain Sensors with High Repeatability and Linearity

Bioinspired High-Linearity, Wide-Sensing-Range Flexible Stretchable Bioelectronics Based on MWCNTs/GR/Nd2Fe14B/PDMS Nanocomposites for Human-Computer Interaction and Biomechanics Detection

In recent years, flexible and stretchable strain sensors have emerged as a prominent area of research, primarily due to their remarkable stretchability and extremely low strain detection threshold. Nevertheless, the advancement of sensors is currently constrained by issues such as complexity, high costs, and limited durability. To tackle the aforementioned issues, this study introduces a lepidophyte-inspired flexible, stretchable strain sensor (LIFSSS). The stretchable bioelectronics composites were composed of multiwalled carbon nanotubes, graphene, neodymium iron boron, and polydimethylsiloxane. Unique biolepidophyted microstructures and magnetic conductive nanocomposites interact with each other through synergistic interactions, resulting in the effective detection of tensile strain and magnetic excitation. The LIFSSS exhibits a 170% tensile range, a linearity of 0.99 in 50-170% strain (0.96 for full-scale range), and a fine durability of 7000 cycles at 110% tensile range. The sensor accurately detects variations in linear tensile force, human movement, and microexpressions. Moreover, LIFSSS demonstrates enhanced efficacy in sign language recognition for individuals with hearing impairments and magnetic grasping for robotic manipulators. Hence, the LIFSSS proposed in this study shows potential applications in various fields, including bioelectronics, electronic skin, and physiological activity monitoring.

Curved Structure Regulated Single Metal Sites for Advanced Electrocatalytic Reactions

Curved surface with defined local electronic structures and regulated surface microenvironments is significant for advanced catalytic engineering. Since single-atom catalysts are highly efficient and active, they have attracted much attention in recent years. The curvature carrier has a significant effect on the electronic structure regulation of single-atom sites, which effectively promote the catalytic efficiency. Here, the effect of the curvature structure with exposed metal atoms for catalysis is comprehensively summarized. First, the substrates with curvature features are reviewed. Second, the applications of single-atom catalysts containing curvature in a variety of different electrocatalytic reactions are discussed in depth. The impact of curvature effects in catalytic reactions is further analyzed. Finally, prospects and suggestions for their application and future development are presented. This review paves the way for the construction of high curvature-containing surface carriers, which is of great significance for single-atom catalysts development.

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

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

Flexible Sensors Based on Conductive Polymer Composites

Elastic polymer-based conductive composites (EPCCs) are of great potential in the field of flexible sensors due to the advantages of designable functionality and thermal and chemical stability. As one of the popular choices for sensor electrodes and sensitive materials, considerable progress in EPCCs used in sensors has been made in recent years. In this review, we introduce the types and the conductive mechanisms of EPCCs. Furthermore, the recent advances in the application of EPCCs to sensors are also summarized. This review will provide guidance for the design and optimization of EPCCs and offer more possibilities for the development and application of flexible sensors.

Review of Recent Progress on Silicone Rubber Composites for Multifunctional Sensor Systems

The latest progress (the year 2021-2024) on multifunctional sensors based on silicone rubber is reported. These multifunctional sensors are useful for real-time monitoring through relative resistance, relative current change, and relative capacitance types. The present review contains a brief overview and literature survey on the sensors and their multifunctionalities. This contains an introduction to the different functionalities of these sensors. Following the introduction, the survey on the types of filler or rubber and their fabrication are briefly described. The coming section deals with the fabrication methodology of these composites where the sensors are integrated. The special focus on mechanical and electro-mechanical properties is discussed. Electro-mechanical properties with a special focus on response time, linearity, and gauge factor are reported. The next section of this review reports the filler dispersion and its role in influencing the properties and applications of these sensors. Finally, various types of sensors are briefly reported. These sensors are useful for monitoring human body motions, breathing activity, environment or breathing humidity, organic gas sensing, and, finally, smart textiles. Ultimately, the study summarizes the key takeaway from this review article. These conclusions are focused on the merits and demerits of the sensors and are followed by their future prospects.

Freestanding Serpentine Silicon Strips with Ultrahigh Stretchability over 300% for Wearable Electronics

Well-functionalized electronic materials, such as silicon, in a stretchable format are desirable for high-performance wearable electronics. However, obtaining Si materials that meet the required stretchability of over 100% for wearable applications remains a significant challenge. Herein, a rational design strategy is proposed to achieve freestanding serpentine Si strips (FS-Si strips) with ultrahigh stretchability, fulfilling wearable requirements. The self-supporting feature makes the strips get rid of excessive constraints from substrates and enables them to deform with the minimum strain energy. Micrometer-scale thicknesses enhance robustness, and large diameter-to-width ratios effectively reduce strain concentration. Consequently, the FS-Si strips with the optimum design could withstand 300% stretch, bending, and torsion without fracturing, even under rough manual operation. They also exhibit excellent stability and durability over 50,000 cycles of 100% stretching cycles. For wearable applications, the FS-Si strips can maintain conformal contact with the skin and have a maximum stretchability of 120%. Moreover, they are electrically insensitive to large deformations, which ensure signal stability during their daily use. Combined with mature processing techniques and the excellent semiconductor properties of Si, FS-Si strips are promising core stretchable electronic materials for wearable electronics.

One-step of ionic liquid-assisted stabilization and dispersion: Exfoliated graphene and its applications in stimuli-responsive conductive hydrogels based on chitosan

Conductive hydrogels, as novel flexible biosensors, have demonstrated significant potential in areas such as soft robotics, electronic devices, and wearable technology. Graphene is a promising conductive material, but its dispersibility in aqueous solutions exists difficulties. Here, we discover that untreated graphene, after exfoliation by different ionic liquids, can disperse well in aqueous solutions. We investigate the impact of four ionic liquids with varying alkyl chain lengths ([Bmim]Cl, [Omim]Cl, [Dmim]Cl, [Hmim]Cl) on the dispersibility of grapheme, and a dual physically cross-linked network hydrogel structure is designed using acrylamide (AM), acrylic acid (AA), methyl methacrylate octadecyl ester (SMA), ionic liquid@graphene (ILs@GN), and chitosan (CS). Notably, SMA, CS, AA and AM act as dynamic cross-linking points through hydrophobic interactions and hydrogen bonding, playing a crucial role in energy dissipation. The resulting hydrogel exhibits outstanding stretchability (2250 %), remarkable toughness (1.53 MJ/m3) in tensile deformation performance, high compressive strength (1.13 MPa), rapid electrical responsiveness (response time ∼ 50 ms), high electrical conductivity (12.11 mS/cm), and excellent strain sensing capability (GF = 12.31, strain = 1000 %). These advantages make our composite hydrogel demonstrate high stability in extensive deformations, offering repeatability in pressure and strain and making it a promising candidate for multifunctional sensors and flexible electrodes.

Silver Nanowire-Based Flexible Strain Sensor for Human Motion Detection

Accurately capturing human movements is a crucial element of health status monitoring and a necessary precondition for realizing future virtual reality/augmented reality applications. Flexible motion sensors with exceptional sensitivity are capable of detecting physical activities by converting them into resistance fluctuations. Silver nanowires (AgNWs) have become a preferred choice for the development of various types of sensors due to their outstanding electrical conductivity, transparency, and flexibility within polymer composites. Herein, we present the design and fabrication of a flexible strain sensor based on silver nanowires. Suitable substrate materials were selected, and the sensor's sensitivity and fatigue properties were characterized and tested, with the sensor maintaining reliability after 5000 deformation cycles. Different sensors were prepared by controlling the concentration of silver nanowires to achieve the collection of motion signals from various parts of the human body. Additionally, we explored potential applications of these sensors in fields such as health monitoring and virtual reality. In summary, this work integrated the acquisition of different human motion signals, demonstrating great potential for future multifunctional wearable electronic devices.

3D Printed MXene-Based Wire Strain Sensors with Enhanced Sensitivity and Anisotropy

Stretchable strain sensors play a crucial role in intelligent wearable systems, serving as the interface between humans and environment by translating mechanical strains into electrical signals. Traditional fiber strain sensors with intrinsic uniform axial strain distribution face challenges in achieving high sensitivity and anisotropy. Moreover, existing micro/nano-structure designs often compromise stretchability and durability. To address these challenges, a novel approach of using 3D printing to fabricate MXene-based flexible sensors with tunable micro and macrostructures.  Poly(tetrafluoroethylene) (PTFE) as a pore-inducing agent is added into 3D printable inks to achieve controllable microstructural modifications. In addition to microstructure tuning, 3D printing is employed for macrostructural design modifications, guided by finite element modeling (FEM) simulations. As a result, the 3D printed sensors exhibit heightened sensitivity and anisotropy, making them suitable for tracking static and dynamic displacement changes. The proposed approach presents an efficient and economically viable solution for standardized large-scale production of advanced wire strain sensors.

Temperature Self-Compensating Intelligent Wireless Measuring Contact Lens for Quantitative Intraocular Pressure Monitoring

Flexible bioelectronic devices that can perform real-time and accurate intraocular pressure (IOP) monitoring in both clinical and home settings hold significant implications for the diagnosis and treatment of glaucoma, yet they face challenges due to the open physiological environment of the ocular. Herein, we develop an intelligent wireless measuring contact lens (WMCL) incorporating a dual inductor-capacitor-resistor (LCR) resonant system to achieve temperature self-compensation for quantitative IOP monitoring in different application environments. The WMCL utilizes a compact circuitry design, which enables the integration of low-frequency and high-frequency resonators within a single layer of a sensing circuit without causing visual impairment. Mechanically guided microscale 3D encapsulation strategy combined with flexible circuit printing techniques achieves the surface-adaptive fabrication of the WMCL. The specific design of frequency separation imparts distinct temperature response characteristics to the dual resonators, and the linear combination of the dual resonators can eliminate the impact of temperature variations on measurement accuracy. The WMCL demonstrates outstanding sensitivity and linearity in monitoring the IOP of porcine eyes in vitro while maintaining satisfactory measurement accuracy even with internal temperature variations exceeding 10 °C. Overcoming the impact of temperature variations on IOP monitoring from the system level, the WMCL showcases immense potential as the next generation of all-weather IOP monitoring devices.

Achieving a Wide-Range Linear Piezoresistive Response in Electrowritten Soft-Hard Polymer Blends via Salami-Inspired Heterostructure Design

Flexible electronics capable of acquiring high-precision signals are in great demand for the development of the internet of things and intelligent artificial. However, it is currently a challenge to simultaneously achieve high signal linearity and sensitivity for stretchable resistive sensors over a wide strain range toward advanced application scenarios requiring high signal accuracy, e.g., sophisticated physiological signal discrimination and displacement measurement. Herein, a film strain sensor, which has an electrical and mechanical dual heterostructure, was fabricated via a direct near-field electrowriting and molecule-guided in situ growth of silver nanoparticles with different concentrations on high-modulus polystyrene domains and low-modulus styrene-butadiene copolymers with a salami-like morphology. Mechanism analyses from both theoretical and experimental investigations reveal that the salami-like heteromodulus microstructure regulates microcrack propagation routes, while the heteroconductivity changes the electron transport paths and amplifies the resistance increase during crack propagation. Therefore, the as-designed strain sensor shows a linear resistive response within ca. 70% strain with a gauge factor of 25, unveiling a simple and scalable strategy for trading off signal linearity and sensitivity over a wide strain range for the fabrication of high-performance linear strain sensors.

Anchoring Fe Species on the Highly Curved Surface of S and N Co-Doped Carbonaceous Nanosprings for Oxygen Electrocatalysis and a Flexible Zinc-Air Battery

Oxygen reduction reaction (ORR) is of critical significance in the advancement of fuel cells and zinc-air batteries. The iron-nitrogen (Fe-Nx ) sites exhibited exceptional reactivity towards ORR. However, the task of designing and controlling the local structure of Fe species for high ORR activity and stability remains a challenge. Herein, we have achieved successful immobilization of Fe species onto the highly curved surface of S, N co-doped carbonaceous nanosprings (denoted as FeNS/Fe3 C@CNS). The induction of this twisted configuration within FeNS/Fe3 C@CNS arose from the assembly of chiral templates. For electrocatalytic ORR tests, FeNS/Fe3 C@CNS exhibits a half-wave potential (E1/2 ) of 0.91 V in alkaline medium and a E1/2 of 0.78 V in acidic medium. The Fe single atoms and Fe3 C nanoparticles are coexistent and play as active centers within FeNS/Fe3 C@CNS. The highly curved surface, coupled with S substitution in the coordination layer, served to reduce the energy barrier for ORR, thereby enhancing the intrinsic catalytic activity of the Fe single-atom sites. We also assembled a wearable flexible Zn-air battery using FeNS/Fe3 C@CNS as electrocatalysts. This work provides new insights into the construction of highly curved surfaces within carbon materials, offering high electrocatalytic efficacy and remarkable performance for flexible energy conversion devices.

Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring

A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since the correlations of pulse waveforms to BP are highly individualized due to the diversity of the patients' physiological characteristics, wearable sensors based on universal designs and algorithms often fail to derive BP accurately when applied on individual patients. Herein, a wearable triboelectric pulse sensor based on a biomimetic nanopillar layer was developed and coupled with Personalized Machine Learning (ML) to provide accurate and continuous monitoring of BP. Flexible conductive nanopillars as the triboelectric layer were fabricated through soft lithography replication of a cicada wing, which could effectively enhance the sensor's output performance to detect weak signal characteristics of pulse waveform for BP derivation. The sensors were coupled with a personalized Partial Least-Squares Regression (PLSR) ML to derive unknown BP based on individual pulse characteristics with reasonable accuracy, avoiding the issue of individual variability that was encountered by General PLSR ML or formula algorithms. The cuffless and intelligent design endow this ML-sensor as a highly promising platform for the care and treatments of hypertensive patients.

Linear Strain Sensors via a Spatial Heteromodulus Tricontinuous Structure Design for High-Resolution Recording of Snoring Breath

Porous conductive elastomer composites are very attractive for designing flexible and air-permeable mechanical sensors for healthcare, while it is challenging to achieve a linear and sensitive electromechanical response over a wide strain range for high-resolution recording of physiological activities and body motions. Here, a scalable strategy is developed to construct porous elastomer composites with a bamboo-shaped heteromodulus microstructure in the pores for the fabrication of linear stretchable strain sensors. Such a spatial heteromodulus microstructure is fabricated via phase separation and selective location of high-modulus phase during melt compounding of elastomers and thermoplastics, together with green etching of the water-soluble plastic in the tricontinuous elastomer composites. The bamboo-shaped heteromodulus microstructure is constructed on the pore struts via the fracture of a high-modulus polymer self-assembled on the pore surface and relaxation recovery of the elastomer matrix after prestretching, which blocks the propagation of cut-through microcracks upon stretching. The composites with super low resistance after in situ growth of silver nanoparticles sustain up to 110% tensile strain with a linear and sensitive electromechanical response, demonstrating potential applications in discriminating respiration status and monitoring snoring breath. This work unveils a new approach to fabricate high-performance air-permeable strain sensors in a simple and scalable way.

A Hierarchical Theory for the Tensile Stiffness of Non-Buckling Fractal-Inspired Interconnects

The design of non-buckling interconnects with thick sections has gained important applications in stretchable inorganic electronics due to their simultaneous achievement of high stretchability, low resistance, and low heat generation. However, at the same time, such a design sharply increased the tensile stiffness, which is detrimental to the conformal fit and skin comfort. Introducing the fractal design into the non-buckling interconnects is a promising approach to greatly reduce the tensile stiffness while maintaining other excellent performances. Here, a hierarchical theory is proposed for the tensile stiffness of the non-buckling fractal-inspired interconnects with an arbitrary shape at each order, which is verified by the finite element analysis. The results show that the tensile stiffness of the non-buckling fractal-inspired interconnects decreases with the increase in either the height/span ratio or the number of fractal orders but is not highly correlated with the ratio of the two adjacent dimensions. When the ratio of the two adjacent dimensions and height/span ratio are fixed, the tensile stiffness of the serpentine fractal-inspired interconnect is smaller than that of sinusoidal and zigzag fractal-inspired interconnects. These findings are of great significance for the design of non-buckling fractal-inspired interconnects of stretchable inorganic electronics.

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

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

Highly Sensitive Artificial Skin Perception Enabled by a Bio-inspired Interface

Piezoionic strain sensors have attracted enormous attention in artificial skin perception because of high sensitivity, lightweight, and flexibility. However, their sensing properties are limited by a weak material interface based on physical adhesion, which usually leads to fast performance deterioration under mechanical conditions. In this work, a bio-inspired interface has been reported based on an in situ growth strategy and then utilized for piezoionic sensor assembly. The robust coupling interface provides fast kinetic of ion transfer and prevents interface slippage under external strains. The as-fabricated sensors give high sensing voltage with high sensitivity. It delivers excellent cycling stability with performance retention above 90% over thousands of bending cycles in air. Further, the sensors have been explored as an effective platform for skin perception, and many detections can be realized within our devices, such as skin touch, eye movement, cheek bulging, and finger movement.

A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition

Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare monitoring, and human-machine interactions. However, there still remains a critical challenge in developing a multifunctional sensing system for complex signal detection and analysis in practical applications. Here, we develop a machine learning-combined flexible sensor for real-time tactile sensing and voice recognition through laser-induced graphitization. The intelligent sensor with a triboelectric layer can convert local pressure to an electrical signal through a contact electrification effect without external bias, which has a characteristic response behavior when exposed to various mechanical stimuli. With the special patterning design, a smart human-machine interaction controlling system composed of a digital arrayed touch panel is constructed to control electronic devices. Based on machine learning, the real-time monitoring and recognition of the changes of voice are achieved with high accuracy. The machine learning-empowered flexible sensor provides a promising platform for the development of flexible tactile sensing, real-time health detection, human-machine interaction, and intelligent wearable devices.

Topological Gradients for Metal Film-Based Strain Sensors

Metal film-based stretchable strain sensors hold great promise for applications in various domains, which require superior sensitivity-stretchability-cyclic stability synergy. However, the sensitivity-stretchability trade-off has been a long-standing dilemma and the metal film-based strain sensors usually suffer from weak cyclic durability, both of which significantly limit their practical applications. Here, we propose an extremely facile, low-cost and spontaneous strategy that incorporates topological gradients in metal film-based strain sensors, composed of intrinsic (grain size and interface) and extrinsic (film thickness and wrinkle) microstructures. The topological gradient strain sensor exhibits an ultrawide stretchability of 100% while simultaneously maintaining a high sensitivity at an optimal topological gradient of 4.5, due to the topological gradients-induced multistage film cracking. Additionally, it possesses a decent cyclic stability for >10 000 cycles between 0 and 40% strain enabled by the gradient-mixed metal/elastomer interfaces. It can monitor the full-range human activities from subtle pulse signals to vigorous joint movements.

Skin bioelectronics towards long-term, continuous health monitoring

Skin bioelectronics are considered as an ideal platform for personalised healthcare because of their unique characteristics, such as thinness, light weight, good biocompatibility, excellent mechanical robustness, and great skin conformability. Recent advances in skin-interfaced bioelectronics have promoted various applications in healthcare and precision medicine. Particularly, skin bioelectronics for long-term, continuous health monitoring offer powerful analysis of a broad spectrum of health statuses, providing a route to early disease diagnosis and treatment. In this review, we discuss (1) representative healthcare sensing devices, (2) material and structure selection, device properties, and wireless technologies of skin bioelectronics towards long-term, continuous health monitoring, (3) healthcare applications: acquisition and analysis of electrophysiological, biophysical, and biochemical signals, and comprehensive monitoring, and (4) rational guidelines for the design of future skin bioelectronics for long-term, continuous health monitoring. Long-term, continuous health monitoring of advanced skin bioelectronics will open unprecedented opportunities for timely disease prevention, screening, diagnosis, and treatment, demonstrating great promise to revolutionise traditional medical practices.

Network crack-based high performance stretchable strain sensors for human activity and healthcare monitoring

In this study, high performance wearable and stretchable strain sensors are developed for human activity and healthcare monitoring, and wearable electronics.