Anisotropic, Wrinkled, and Crack-Bridging Structure for Ultrasensitive, Highly Selective Multidirectional Strain Sensors

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

Anisotropic V-Groove/Wrinkle Hierarchical Arrays for Multidirectional Strain Sensors with High Sensitivity and Exceptional Selectivity

Flexible strain sensors have been continuously optimized and widely used in various fields such as health monitoring, motion detection, and human-machine interfaces. There is a higher demand for sensors that can sensitively identify both the strain amplitude and direction in real-time to adapt to complex human movements. This study proposes a flexible strain sensor construction strategy based on V-groove/wrinkle hierarchical structures via a facile and scalable prestretching approach. A gold film is sputtered on a V-groove structure soft substrate under a vertical biaxial prestrain. When the strain is released, a variety of wondrous V-groove/wrinkle hierarchical structures are formed. The microstructure and the properties of the resulting sensor can be controlled by adjusting the prestrain, which has obvious anisotropic response characteristics and exhibits high sensitivity (maximum gauge factor up to 20,727.46) and a wide sensing range (up to 51%). In addition, the resulting multidirectional sensor based on double-sided microstructures has an exceptional directional selectivity of 67.39, at an advanced level among all stretchable multidirectional strain sensors reported so far. The sensor can detect human motion signals and distinguish motion patterns, proving its great potential in the field of human motion detection and laying a foundation for high-performance wearable devices.

Advanced Multiparallel-Connected Piezoresistive Physical Sensors: Elevating Performance Reliability of Flexible Strain and Pressure Sensors

A physical sensor with a sensing medium comprising multiparallel-connected (MPC) piezoresistive pathways in both the vertical and horizontal directions was developed to achieve improved sensing performance. The MPC sensing medium reduces the total resistance and offsets noise, offering enhanced signal stability and device reliability and providing a high-performance sensing platform. The signal change and gauge factor (GF) of the 3PW-5L strain sensor (comprising three lines and five layers of piezoresistive pathways horizontally and vertically, respectively) were, respectively, 5.9 and 4.7 times higher than those of the 1PW-1L sensor composed of a monosensing pathway; the hysteresis of the detected signal was also significantly reduced. The linearity of the detected signal increased from 0.912 for 1PW-1L to 0.995 for 3PW-5L, indicating a greater sensing reliability. The direction of the applied tensile strain was successfully detected using the MPC sensing medium with an orthogonal configuration. The MPC piezoresistive sensor composing vertically stacked piezoresistive pathways demonstrated excellent performance as a pressure sensor; the 3PW-5L pressure sensor afforded a GF of 0.121 ± 0.002 kPa-1 with a linearity of 0.998 under an applied pressure ≥16.4 kPa. The MPC piezoresistive physical sensor offers a superior sensing performance and should contribute to the future development of wearable sensors and electronic devices.

A Highly Sensitive Strain Sensor with Wide Linear Sensing Range Prepared on a Hybrid-Structured CNT/Ecoflex Film via Local Regulation of Strain Distribution

With the development of information technology, high-performance wearable strain sensors with high sensitivity and stretchability have played a significant role in motion detection. However, many high-sensitivity and outstanding-stretchability strain sensors possess a limited linear sensing range, which limits the enhancement of the flexible strain sensors' performance. Herein, we develop a hybrid-structured carbon nanotube (CNT)/Ecoflex strain sensor with laser-engraved grooves along with punched circular holes in a composite CNT/Ecoflex film by vacuum filtration and permeation. By optimizing the distribution of grooves and circular holes, the strain in the sensing layer can be locally regulated, which alters the morphology of cracks under strain and allows the hybrid-structured CNT/Ecoflex strain sensor to simultaneously exhibit high sensitivity (GF = 43.8) as well as a wide linear sensing range (200%). On the basis of excellent performance, the hybrid-structured CNT/Ecoflex strain sensor is capable of detecting movements in various parts of the human body, including movements of larynx and joint bending.

A terahertz meta-sensor array for 2D strain mapping

Large-scale stretchable strain sensor arrays capable of mapping two-dimensional strain distributions have gained interest for applications as wearable devices and relating to the Internet of Things. However, existing strain sensor arrays are usually unable to achieve accurate directional recognition and experience a trade-off between high sensing resolution and large area detection. Here, based on classical Mie resonance, we report a flexible meta-sensor array that can detect the in-plane direction and magnitude of preloaded strains by referencing a dynamically transmitted terahertz (THz) signal. By building a one-to-one correspondence between the intrinsic electrical/magnetic dipole resonance frequency and the horizontal/perpendicular tension level, arbitrary strain information across the meta-sensor array is accurately detected and quantified using a THz scanning setup. Particularly, with a simple preparation process of micro template-assisted assembly, this meta-sensor array offers ultrahigh sensor density (~11.1 cm-2) and has been seamlessly extended to a record-breaking size (110 × 130 mm2), demonstrating its promise in real-life applications.

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.

New Carbon Materials for Multifunctional Soft Electronics

Soft electronics are garnering significant attention due to their wide-ranging applications in artificial skin, health monitoring, human-machine interaction, artificial intelligence, and the Internet of Things. Various soft physical sensors such as mechanical sensors, temperature sensors, and humidity sensors are the fundamental building blocks for soft electronics. While the fast growth and widespread utilization of electronic devices have elevated life quality, the consequential electromagnetic interference (EMI) and radiation pose potential threats to device precision and human health. Another substantial concern pertains to overheating issues that occur during prolonged operation. Therefore, the design of multifunctional soft electronics exhibiting excellent capabilities in sensing, EMI shielding, and thermal management is of paramount importance. Because of the prominent advantages in chemical stability, electrical and thermal conductivity, and easy functionalization, new carbon materials including carbon nanotubes, graphene and its derivatives, graphdiyne, and sustainable natural-biomass-derived carbon are particularly promising candidates for multifunctional soft electronics. This review summarizes the latest advancements in multifunctional soft electronics based on new carbon materials across a range of performance aspects, mainly focusing on the structure or composite design, and fabrication method on the physical signals monitoring, EMI shielding, and thermal management. Furthermore, the device integration strategies and corresponding intriguing applications are highlighted. Finally, this review presents prospects aimed at overcoming current barriers and advancing the development of state-of-the-art multifunctional soft electronics.

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.

Ultrasensitive Soft Sensor from Anisotropic Conductive Biphasic Liquid Metal-Polymer Gels

Subtle vibrations, such as sound and ambient noises, are common mechanical waves that can transmit energy and signals for modern technologies such as robotics and health management devices. However, soft electronics cannot accurately distinguish ultrasmall vibrations owing to their extremely small pressure, complex vibration waveforms, and high noise susceptibility. This study successfully recognizes signals from subtle vibrations using a highly flexible anisotropic conductive gel (ACG) based on biphasic liquid metals. The relationships between the anisotropic structure, subtle vibrations, and electrical performance are investigated using rheological-electrical experiments. The refined anisotropic design successfully realized low-cost flexible electronics with ultrahigh sensitivity (Gauge Factor: 12787), extremely low detection limit (strain: 0.01%), and excellent frequency recognition accuracy (>99%), significantly surpassing those of current flexible sensors. The ultrasensitive flexible electronics in this study are beneficial for diverse advanced technologies such as acoustic engineering, wearable electronics, and intelligent robotics.

High-Throughput Manufacturing of Multimodal Epidermal Mechanosensors with Superior Detectability Enabled by a Continuous Microcracking Strategy

Non-invasive human-machine interactions (HMIs) are expected to be promoted by epidermal tactile receptive devices that can accurately perceive human activities. In reality, however, the HMI efficiency is limited by the unsatisfactory perception capability of mechanosensors and the complicated techniques for device fabrication and integration. Herein, a paradigm is presented for high-throughput fabrication of multimodal epidermal mechanosensors based on a sequential "femtosecond laser patterning-elastomer infiltration-physical transfer" process. The resilient mechanosensor features a unique hybrid sensing layer of rigid cellular graphitic flakes (CGF)-soft elastomer. The continuous microcracking of CGF under strain enables a sharp reduction in conductive pathways, while the soft elastomer within the framework sustains mechanical robustness of the structure. As a result, the mechanosensor achieves an ultrahigh sensitivity in a broad strain range (GF of 371.4 in the first linear range of 0-50%, and maximum GF of 8922.6 in the range of 61-70%), a low detection limit (0.01%), and a fast response/recovery behavior (2.6/2.1 ms). The device also exhibits excellent sensing performances to multimodal mechanical stimuli, enabling high-fidelity monitoring of full-range human motions. As proof-of-concept demonstrations, multi-pixel mechanosensor arrays are constructed and implemented in a robot hand controlling system and a security system, providing a platform toward efficient HMIs.

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.

Highly Conductive and Sensitive Wearable Strain Sensors with Metal/Nanoparticle Double Layer for Noninterference Voice Detection

Human voice recognition via skin-attachable devices has significant potential for gathering important physiological information from acoustic data without background noise interference. In this study, a highly sensitive and conductive wearable crack-based strain sensor was developed for voice-recognition systems. The sensor was fabricated using a double-layer structure of Ag nanoparticles (NPs) and Ag metal on a biocompatible polydimethylsiloxane substrate. The top metal layer acts as a conducting active layer, whereas the bottom Ag NP layer induces channel cracks in the upper layer, effectively hindering current flow. Subsequently, the double-layer film exhibits a low electrical resistance value (<5 × 10-5 Ω cm), ultrahigh sensitivity (gauge factor = 1870), and a fast response/recovery time (252/168 μs). A sound wave was detected at a high frequency of 15 kHz with a signal-to-noise ratio (SNR) over 40 dB. The sensor exhibited excellent anti-interference characteristics and effectively differentiated between different voice qualities (modal, pressed, and breathy), with a systematic analysis revealing successful detection of the laryngeal state and glottal source. This ultrasensitive wearable sensor has potential applications in various physiological signal measurement methods, personalized healthcare systems, and ubiquitous computing.

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.

Anisotropic and Highly Sensitive Flexible Strain Sensors Based on Carbon Nanotubes and Iron Nanowires for Human-Computer Interaction Systems

Flexible strain sensors for multi-directional strain detection are crucial in complicated hman-computer interaction (HCI) applications. However, enhancing the anisotropy and sensitivity of the sensors for multi-directional detection in a simple and effective method remains a significant issue. Therefore, this study proposes a flexible strain sensor with anisotropy and high sensitivity based on a high-aspect-ratio V-groove array and a hybrid conductive network of iron nanowires and carbon nanotubes (Fe NWs/CNTs). The sensor exhibits significant anisotropy, with a difference in strain detection sensitivity of up to 35.92 times between two mutually perpendicular directions. Furthermore, the dynamic performance of the sensor shows a good response rate, ranging from 223 ms to 333 ms. The sensor maintains stability and consistent performance even after undergoing 1000 testing cycles. Additionally, the constructed flexible strain sensor is tested using the remote control application of a trolley, demonstrating its high potential for usage in practical HCI systems. This research offers a significant competitive advantage in the development of flexible strain sensors in the field of HCI.

Emerging Trends in Soft Electronics: Integrating Machine Intelligence with Soft Acoustic/Vibration Sensors

In the last decade, soft acoustic/vibration sensors have gained tremendous research interest due to their unique ability to detect broadband acoustic/vibration stimuli, potentializing futuristic applications including voice biometrics, voice-controlled human-machine-interfaces, electronic skin, and skin-mountable healthcare devices. Importantly, to benefit most from these sensors, it is inevitable to use machine learning (ML) to process their output signals; with ML, a more accurate and efficient interpretation of original data is possible. This paper is dedicated to offering an overview of recent advances empowering the development of soft acoustic/vibration sensors and their signal processing using ML. First, the key performance parameters of the sensors are discussed. Second, popular transduction mechanisms for the sensors are addressed, followed by an in-depth overview of each type, covering materials used, structural designs, and sensing performances. Third, potential applications of the sensors are elaborated and fourth, a thorough discussion on ML is conducted, exploring different types of ML, specific ML algorithms suitable for processing acoustic/vibration signals, and current trends in ML-assisted applications. Finally, the challenges and potential opportunities in soft acoustic/vibration sensor and ML research are revealed to offer new insights into future prospects in these fields.

Graphene composite paper synergized with micro/nanocellulose-fiber and silk fibroin for flexible strain sensor

The fabrication of uniform and strong graphene-based conductive paper is challenging due to easy aggregation and poor film formability of graphene. Herein, on the basis of good dispersing effect of nanocellulose, high content graphene (50 wt%) composite paper with micro/nanocellulose fibers and silk fibroin (SF) was manufactured via simple casting method. The synergistic effects of cellulose microfibers (CMFs), cellulose nanofibers (CNFs) and SF result in the paper with ideal combination of flexibility, electrical conductivity and mechanical strength, where CNFs, CMFs and SF act as dispersing and film forming for GNPs, dimensional stability, and interfacial binding agents, respectively. Extraordinarily, by adding SF, graphene nanosheets are tightly coated on the surface of CMFs. The composite paper shows a tensile strength of 49.29 MPa, surface resistance of 39.0-42.1 Ω and good joints bend sensing performance. Additionally, it is found that CMFs can hinder the micro-cracks from propagating during the cyclic elbow bending test. The graphene-based conductive paper is helpful for the development of smart clothing wearable biosensing devices.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Mechanochromic Optical/Electrical Skin for Ultrasensitive Dual-Signal Sensing

Following earlier research efforts dedicated to the realization of multifunctional sensing, recent developments of artificial skins endeavor to go beyond human sensory functions by integrating interactive visualization of strain and pressure stimuli. Inspired by the microcracked structure of spider slit organs and the mechanochromic mechanism of chameleons, this work aims to design a flexible optical/electrical skin (OE-skin) capable of responding to complex stimuli with interactive feedback of human-readable structural colors. The OE-skin consists of an ionic electrode combined with an elastomer dielectric layer, a chromotropic layer containing photonic crystals and a conductive carbon nanotube/MXene layer. The electrode/dielectric layers function as a capacitive pressure sensor. The mechanochromic photonic crystals of ferroferric oxide-carbon magnetic arrays embedded in the gelatin/polyacrylamide stretchable hydrogel film perceive strain and pressure stimuli with bright color switching outputs in the full visible spectrum. The underlying microcracked conductive layer is devoted to ultrasensitive strain sensing with a gauge factor of 191.8. The multilayered OE-skin delivers an ultrafast, accurate response for capacitive pressure sensing with a detection limit of 75 Pa and long-term stability of 5000 cycles, while visualizing complex deformations in the form of high-resolution spatial colors. These findings offer deep insights into the rational design of OE-skins as multifunctional sensing devices.

Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.

Machine Learning-Enhanced Flexible Mechanical Sensing

To realize a hyperconnected smart society with high productivity, advances in flexible sensing technology are highly needed. Nowadays, flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device's software. Significant research efforts have been devoted to improving materials, sensing mechanism, and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology. Meanwhile, advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing data. In this review, the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented. Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated, which includes health monitoring, human-machine interfaces, object/surface recognition, pressure prediction, and human posture/motion identification. Finally, the advantages, challenges, and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed. These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.

Ultra-sensitive, Multi-directional Flexible Strain Sensors Based on an MXene Film with Periodic Wrinkles

The fast-growing motion capturing/monitoring technique has raised a great demand for flexible strain sensors. For capturing complex motions (e.g., facial motion), both the strain amplitude and direction should be accurately detected. Although some reported sensors based on anisotropic conductive networks are proved to show accurate localization of strain directions, it is still a great challenge to achieve both high sensitivity and a high sensing range in these designs. Here, a self-assembled Ti₃C₂T_x MXene film with parallel and periodic wrinkles is fabricated on a stretchable poly(dimethylsiloxane) substrate for constructing multi-directional strain sensors. During stretching, relative slip and crack will occur between the stacked MXene nanosheets, which contribute to high structural sensitivity in the MXene film. Meanwhile, the wrinkled structure contributes to high stretchability. As a result, the sensor based on the film with one-dimensional periodic wrinkles shows a large sensing range (>50%) and a gauge factor of 45. Furthermore, the sensor can accurately detect both the strain amplitude and direction by using the MXene film with two-dimensional wrinkles. It shows distinguishable electrical responses when detecting different-amplitude human/robot motions such as joint bending and walking. Additionally, the directions in complex human motions (e.g., facial motion) can also be well-tracked. This work provides an effective strategy to detect multi-directional motions.

Janus and Heteromodulus Elastomeric Fiber Mats Feature Regulable Stress Redistribution for Boosted Strain Sensing Performance

Wearable strain sensors have huge potential for applications in healthcare, human-machine interfacing, and augmented reality systems. However, the nonlinear response of the resistance signal to strain has caused considerable difficulty and complexity in data processing and signal transformation, thus impeding their practical applications severely. Herein, we propose a simple way to achieve linear and reproducible resistive signals responding to strain in a relatively wide strain range for flexible strain sensors, which is achieved via the fabrication of Janus and heteromodulus elastomeric fiber mats with micropatterns using microimprinting second processing technology. In detail, both isotropic and anisotropic fiber mats can turn into Janus fiber mats with periodical and heteromodulus micropatterns via controlling the fiber fusion and the diffusion of local macromolecular chains of thermoplastic elastomers. The Janus heterogeneous microstructure allows for stress redistribution upon stretching, thus leading to lower strain hysteresis and improved linearity of resistive signal. Moreover, tunable sensing performance can be achieved by tailoring the size of the micropatterns on the fiber mat surface and the fiber anisotropy. The Janus mat strain sensors with high signal linearity and good reproducibility have a very low strain detection limit, enabling potential applications in human-machine interfacing and intelligent control fields if combined with a wireless communication module.

Surface Wrinkling for Flexible and Stretchable Sensors

Recent advances in nanolithography, miniaturization, and material science, along with developments in wearable electronics, are pushing the frontiers of sensor technology into the large-scale fabrication of highly sensitive, flexible, stretchable, and multimodal detection systems. Various strategies, including surface engineering, have been developed to control the electrical and mechanical characteristics of sensors. In particular, surface wrinkling provides an effective alternative for improving both the sensing performance and mechanical deformability of flexible and stretchable sensors by releasing interfacial stress, preventing electrical failure, and enlarging surface areas. In this study, recent developments in the fabrication strategies of wrinkling structures for sensor applications are discussed. The fundamental mechanics, geometry control strategies, and various fabricating methods for wrinkling patterns are summarized. Furthermore, the current state of wrinkling approaches and their impacts on the development of various types of sensors, including strain, pressure, temperature, chemical, photodetectors, and multimodal sensors, are reviewed. Finally, existing wrinkling approaches, designs, and sensing strategies are extrapolated into future applications.

Strain-ultrasensitive surface wrinkles for visual optical sensors

Wearable tactile sensors have found widespread applications in human health monitoring, motion monitoring, human-machine interactions, and artificial prostheses. Herein, we demonstrate a new and feasible strategy for wearable optical sensors based on surface wrinkles that are ultrasensitive to strain using a bilayer wrinkling system, in which the relevance between strain and the optical signal can be founded on surface wrinkles. The strain (S⃑(ε, θ_S)), the wrinkled topography (W⃑(A, θ_W)), and the reflected optical signal (O⃑(δ, θ_O)) are correlated with each other, allowing simultaneous measurement of the strain magnitude and direction due to the vector property of optical signals. In addition, interactively visualized detection of slight strain has been achieved by a conspicuous structural color change, successfully amplifying the strain signal owing to the ultra-sensitivity of wrinkles and the nonlinearity of the optical signal. The sensor also exhibits electrical safety and immunity to electromagnetic interference and thus may find potential applications in detecting various complex slight strains, such as subtle human motion or object deformation.

Crack-Based Core-Sheath Fiber Strain Sensors with an Ultralow Detection Limit and an Ultrawide Working Range

With the booming development of flexible wearable sensing devices, flexible stretchable strain sensors with crack structure and high sensitivity have been widely concerned. However, the narrow sensing range has been hindering the development of crack-based strain sensors. In addition, the existence of the crack structure may reduce the interface compatibility between the elastic matrix and the sensing material. Herein, to overcome these problems, integrated core-sheath fibers were prepared by coaxial wet spinning with partially added carbon nanotube sensing materials in thermoplastic polyurethane elastic materials. Due to the superior interface compatibility and the change in the conductive path during stretching, the fiber strain sensor exhibits excellent durability (5000 tensile cycles), high sensitivity (>10⁴), large stretchability (500%), a low detection limit (0.01%), and a fast response time of ∼60 ms. Based on these outstanding strain sensing performances, the fiber sensor is demonstrated to detect subtle strain changes (e.g., pulse wave and swallowing) and large strain changes (e.g., finger joint and wrist movement) in real time. Moreover, the fabric sensor woven with the core-sheath fibers has an excellent performance in wrist bending angle detection, and the smart gloves based on the fabric sensors also show exceptional recognition ability as a wireless sign language translation device. This integrated strategy may provide prospective opportunities to develop highly sensitive strain sensors with durable deformation and a wide detection range.

Serpentine-inspired Strain Sensor with Predictable Cracks for Remote Bio-Mechanical Signal Monitoring

The flexible strain sensors have attracted intense interests due to their application as intelligent wearable electronic devices. However, it is still a huge challenge to achieve the flexible sensor with simultaneous high sensitivity, excellent durability and wide sensing region. In this work, a crack-based strain sensor with paired-serpentine conductive network is fabricated onto flexible film by screen printing. The innovative conductive network exhibits a controlled crack morphology during stretching, which endows the prepared sensor with outstanding sensing characteristics, including the high sensitivity (gauge factor up to 2391.5), wide detection (rang up to 132%), low strain detection limit, fast response time (about 40 ms), as well as excellent durability (more than 2000 stretching/releasing cycles). Benefiting from these excellent performances, full-range human body motions including subtle physiological signals and large motions are accurately detected by the prepared sensor. Besides, wearable electronic equipment integrated with wireless transmitter and the prepared strain sensor shows great potential for remote motion monitoring and intelligent mobile diagnosis for humans. This work provides an effective strategy for the fabrication of the novel strain sensors with highly comprehensive performance. This article is protected by copyright. All rights reserved.

Breathable and Wearable Strain Sensors Based on Synergistic Conductive Carbon Nanotubes/Cotton Fabrics for Multi-directional Motion Detection

Flexible strain-sensitive sensors have been receiving intensive attention in many aspects ranging from human motion capture to health-related signal monitoring. However, the fabric strain sensor with multi-directional sensing capability, besides having a wide strain range and high response sensitivity, is still very challenging and deserves further exploration. Here, we have prepared a wearable cotton fabric strain sensor uniformly decorated with single-walled carbon nanotubes through a facile solution process. The unique hierarchical architecture of the cotton fabric woven from twisted yarns combined with the conductive carbon nanotube network endows the fabric strain sensors with attractive performance, including low detection limit, large workable strain range, fascinating stability and durability, excellent direction-dependent strain response, and good air permeability. The strain sensor without polymer encapsulation can not only monitor subtle and large multi-directional motions but also fit well to the human body with satisfactory comfort, demonstrating its potential application in wearable electronics and intelligent clothing.

High Sensitivity and a Wide Sensing Range Flexible Strain Sensor Based on the V-Groove/Wrinkles Hierarchical Array

Flexible strain sensors occupying a large part of human body detection and wearable electronics, which have a wide sensing range and high sensitivity, are crucial in fully monitoring human motion signals. This study proposed a strategy to construct flexible strain sensors based on the V-groove/wrinkles hierarchical array. The V-groove array was prepared on a polydimethylsiloxane (PDMS) substrate through mold transfer printing. The gold film was sputtered on the prestretching PDMS substrate, and the V-groove/wrinkles hierarchical array was formed after strain release. Compared with the sensors based on single-scale wrinkle structures and a V-groove array, the fabricated strain sensor with the hierarchical array showed high sensitivity (maximum gauge factor up to 2,557.71) and a wide sensing range (up to 45%). In addition, the dynamic characteristics of the sensor were investigated in detail, indicating that the sensor had a fast response (less than 130 ms), a low detection limit (0.1% strain), and good stability (almost no performance loss after 10,000 cycles). In practical applications, the sensor was used to detect sizable physical motion and weak physiological signals, demonstrating great potential application value in human motion detection. This study could provide new ideas for preparing high-performance flexible strain sensors.

Macromolecule Relaxation Directed 3D Nanofiber Architecture in Stretchable Fibrous Mats for Wearable Multifunctional Sensors

Elastomer fiber mat sensors, which are capable of perceiving mechanical stimuli, temperature, and vapor of chemicals, are highly desirable for designing wearable electronics and human-robot interfacing devices due to good wearability, skin affinity, and durability, and so on. However, it is still challenging to fabricate multiresponsive flexible wearable sensors with three-dimensional (3D) architecture using simple material and structure design. Herein, we report an all-in-one multiresponsive thermoplastic polyurethane (TPU) nanofiber mat sensors composed of crimped elastomer fibers with deposited platinum nanoparticles (PtNPs) on the fiber surface. The 1D TPU nanofibers could be transferred to nanofibers with different 3D nanofiber architectures by controllable macromolecular chain relaxation of aligned elastomer polymers upon poor solvent annealing. The conductive networks of PtNPs on wavy TPU fibers enable the sensor susceptible to multiple stimuli like strain/pressure, humidity, and organic vapors. Besides, the 3D nanofiber architectures allow the strain sensor to detect wider tensile strain and pressure with higher sensitivity due to delicate fiber morphology and structure control. Therefore, this work provides new insights into the fabrication of multifunctional flexible sensors with 3D architecture in an easy way, advancing the establishment of a multiple signal monitoring platform for the health care and human-machine interfacing.

Scientific Developments and New Technological Trajectories in Sensor Research

Scientific developments and new technological trajectories in sensors play an important role in understanding technological and social change. The goal of this study is to develop a scientometric analysis (using scientific documents and patents) to explain the evolution of sensor research and new sensor technologies that are critical to science and society. Results suggest that new directions in sensor research are driving technological trajectories of wireless sensor networks, biosensors and wearable sensors. These findings can help scholars to clarify new paths of technological change in sensors and policymakers to allocate research funds towards research fields and sensor technologies that have a high potential of growth for generating a positive societal impact.

Textile-Based Mechanical Sensors: A Review

Innovations related to textiles-based sensors have drawn great interest due to their outstanding merits of flexibility, comfort, low cost, and wearability. Textile-based sensors are often tied to certain parts of the human body to collect mechanical, physical, and chemical stimuli to identify and record human health and exercise. Until now, much research and review work has been carried out to summarize and promote the development of textile-based sensors. As a feature, we focus on textile-based mechanical sensors (TMSs), especially on their advantages and the way they achieve performance optimizations in this review. We first adopt a novel approach to introduce different kinds of TMSs by combining sensing mechanisms, textile structure, and novel fabricating strategies for implementing TMSs and focusing on critical performance criteria such as sensitivity, response range, response time, and stability. Next, we summarize their great advantages over other flexible sensors, and their potential applications in health monitoring, motion recognition, and human-machine interaction. Finally, we present the challenges and prospects to provide meaningful guidelines and directions for future research. The TMSs play an important role in promoting the development of the emerging Internet of Things, which can make health monitoring and everyday objects connect more smartly, conveniently, and comfortably efficiently in a wearable way in the coming years.

Morphology and Chemical Purity of Water Suspension of Graphene Oxide FLAKES Aged for 14 Months in Ambient Conditions. A Preliminary Study

Graphene and its derivatives have attracted scientists’ interest due to their exceptional properties, making them alluring candidates for multiple applications. However, still little is known about the properties of as-obtained graphene derivatives during long-term storage. The aim of this study was to check whether or not 14 months of storage time impacts graphene oxide flakes’ suspension purity. Complementary micro and nanoscale characterization techniques (SEM, AFM, EDS, FTIR, Raman spectroscopy, and elemental combustion analysis) were implemented for a detailed description of the topography and chemical properties of graphene oxide flakes. The final step was pH evaluation of as-obtained and aged samples. Our findings show that purified flakes sustained their purity over 14 months of storage.