Ultrasensitive and Wearable Carbon Hybrid Fiber Devices as Robust Intelligent Sensors

Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification

Sedentary behaviors, including poor postures, are significantly detrimental to health, particularly for individuals losing motion ability. This study presents a posture detection system utilizing four force-sensitive resistors (FSRs) and two triaxial accelerometers selected after rigorous assessment for consistency and linearity. We compared various machine learning algorithms based on classification accuracy and computational efficiency. The k-nearest neighbor (KNN) algorithm demonstrated superior performance over Decision Tree, Discriminant Analysis, Naive Bayes, and Support Vector Machine (SVM). Further analysis of KNN hyperparameters revealed that the city block metric with K = 3 yielded optimal classification results. Triaxial accelerometers exhibited higher accuracy in both training (99.4%) and testing (99.0%) phases compared to FSRs (96.6% and 95.4%, respectively), with slightly reduced processing times (0.83 s vs. 0.85 s for training; 0.51 s vs. 0.54 s for testing). These findings suggest that, apart from being cost-effective and compact, triaxial accelerometers are more effective than FSRs for posture detection.

Strong and Robust Core-Shell Ceramic Fibers Composed of Highly Compacted Nanoparticles for Multifunctional Electronic Skin

Functional fibers composed of textiles are considered a promising platform for constructing electronic skin (e-skin). However, developing robust electronic fibers with integrated multiple functions remains a formidable task especially when a complex service environment is concerned. In this work, a continuous and controllable strategy is demonstrated to prepare e-skin-oriented ceramic fibers via coaxial wet spinning followed by cold isostatic pressing. The resulting core-shell structured fiber with tightly compacted Al-doped ZnO nanoparticles in the core and highly ordered aramid nanofibers in the shell exhibit excellent tensile strength (316 MPa) with ultra-high elongation (33%). Benefiting from the susceptible contacts between conducting ceramic nanoparticles, the ceramic fiber shows both ultrahigh sensitivity (gauge factor = 2141) as a strain sensor and a broad working range up to 70 °C as a temperature sensor. Furthermore, the tunable core-shell structure of the fiber enables the optimization of impedance matching and attenuation of electromagnetic waves for the corresponding textile, resulting in a minimum reflection loss of -39.1 dB and an effective absorption bandwidth covering the whole X-band. Therefore, the versatile core-shell ceramic fiber-derived textile can serve as a stealth e-skin for monitoring the motion and temperature of robots under harsh conditions.

Quasi-1D Conductive Network Composites for Ultra-Sensitive Strain Sensing

Highly performance flexible strain sensor is a crucial component for wearable devices, human-machine interfaces, and e-skins. However, the sensitivity of the strain sensor is highly limited by the strain range for large destruction of the conductive network. Here the quasi-1D conductive network (QCN) is proposed for the design of an ultra-sensitive strain sensor. The orientation of the conductive particles can effectively reduce the number of redundant percolative pathways in the conductive composites. The maximum sensitivity will reach the upper limit when the whole composite remains only "one" percolation pathway. Besides, the QCN structure can also confine the tunnel electron spread through the rigid inclusions which significantly enlarges the strain-resistance effect along the tensile direction. The strain sensor exhibits state-of-art performance including large gauge factor (862227), fast response time (24 ms), good durability (cycled 1000 times), and multi-mechanical sensing ability (compression, bending, shearing, air flow vibration, etc.). Finally, the QCN sensor can be exploited to realize the human-machine interface (HMI) application of acoustic signal recognition (instrument calibration) and spectrum restoration (voice parsing).

Valorization of Food Waste: Utilizing Natural Porous Materials Derived from Pomelo-Peel Biomass to Develop Triboelectric Nanogenerators for Energy Harvesting and Self-Powered Sensing

Food waste is an enormous challenge, with implications for the environment, society, and economy. Every year around the world, 1.3 billion tons of food are wasted or lost, and food waste-associated costs are around $2.6 trillion. Waste upcycling has been shown to mitigate these negative impacts. This study's optimized pomelo-peel biomass-derived porous material-based triboelectric nanogenerator (PP-TENG) had an open circuit voltage of 58 V and a peak power density of 254.8 mW/m2. As porous structures enable such triboelectric devices to respond sensitively to external mechanical stimuli, we tested our optimized PP-TENG's ability to serve as a self-powered sensor of biomechanical motions. As well as successfully harvesting sufficient mechanical energy to power light-emitting diodes and portable electronics, our PP-TENGs successfully monitored joint motions, neck movements, and gait patterns, suggesting their strong potential for use in healthcare monitoring and physical rehabilitation, among other applications. As such, the present work opens up various new possibilities for transforming a prolific type of food waste into value-added products and thus could enhance long-term sustainability while reducing such waste.

Piezoresistive Pressure Sensor Based on a Conductive 3D Sponge Network for Motion Sensing and Human-Machine Interface

Flexible sensors have attracted increasing attention owing to their important applications in human activity monitoring, medical diagnosis, and human-machine interaction. However, the rational design of low-cost sensors with desirable properties (e.g., high sensitivity and excellent stability) and extended applications is still a great challenge. Herein, a simple and cost-effective strategy is reported by immersing polyurethane (PU) sponge in graphene oxide solution followed by in situ chemical reduction to construct a reduced graphene oxide (RGO)-wrapped PU sponge sensor. Ascribed to the excellent compressive resilience of PU sponge and an electrically conductive RGO layer, the constructed flexible sensor exhibits satisfactory sensing performance with high sensitivity (17.65 kPa^-1) in a low-load range (0-3.2 kPa), a wide compression strain range (0-80%), and reliable stability (8000 cycles). In addition, these sensors can be successfully applied to monitor human movements and identify the weight of objects. Through the use of a sensor array integrated with a signal acquisition circuit, the reasonably designed sensors can realize tactile feedback via mapping real-time spatial distribution of pressure in complicated tasks and show potential applications in flexible electronic pianos, electronic skin, and remote real-time control of home electronics.

Carbon Nanomaterials-Based Electrochemical Sensors for Heavy Metal Detection

Heavy metals are commonly found in a wide range of environmental settings metals, but the potential toxicity associated with heavy metal exposure represents a major threat to global public health. It is thus vital that approaches to efficiently, reliably, and effectively detecting heavy metals in a range of sample types be established. Carbon nanomaterials offer many advantageous properties that make them well-suited to the design of sensitive, selective, easy-to-operate electrochemical biosensors ideal for detecting heavy metal ions. The present review offers an overview of recent progress in the development of carbon nanomaterial-based electrochemical sensors used to detect heavy metals. In addition to providing a detailed discussion of certain carbon nanomaterials such as carbon nanotubes, graphene, carbon fibers, carbon quantum dots, carbon nanospheres, mesoporous carbon, and Graphdiyne, we survey the challenges and future directions for this field. Overall, the studies discussed herein suggest that the further development of carbon nanomaterial-modified electrochemical sensors will support the integration of increasingly advanced sensor platforms to aid in detecting heavy metals in foods, environmental samples, and other settings, thereby benefitting human health and society as a whole.

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.

Ultrasensitive and highly stretchable fibers with dual conductive microstructural sheaths for human motion and micro vibration sensing

Conductive and stretchable fibers are important components of the increasingly popular wearable electronic devices as they meet the design requirements of excellent electrical conductivity, stretchability, and wearability. In this work, we developed a novel dual conductive-sheath fiber (DCSF) with a conductive sheath composed of a porous elastic conductive layer and cracked metal networks, thus achieving ultrahigh sensitivity under a large strain range. The core of the DCSF is made of thermoplastic polyurethane (TPU) elastic fiber wrapped in a porous stretchable conductive layer composed of carbon nanotubes (CNTs) and TPU. Next, a layer of gold film is deposited on the surface of the porous stretchable conductive layer by ion beam sputtering. Due to the fast response time of 184 ms and ultrahigh sensitivity in the 0-100% strain range (a gauge factor of 184.50 for a strain of 0-10%, 4.12 × 10⁵ for 10%-30%, and 2.80 × 10⁵ for 30%-100%) of the DCSF strain sensor, we successfully wove the fiber strain sensor into gloves and could realize the recognition of different hand gestures. Also the DCSF strain sensor can be applied to detect microvibrations efficiently. The demonstrated DCSF has potential applications in the development of smart wearable devices and micro vibration sensors.

Lightweight, Robust, Conductive Composite Fibers Based on MXene@Aramid Nanofibers as Sensors for Smart Fabrics

Developing one-dimensional fiber-based sensors to meet the requirement of spinnability, portability, flexibility, and easeful conformability in smart wearable devices has attracted increasing interest. Here, we report highly conductive MXene@aramid nanofibers (ANFs) with a distinct skin-core structure by the wet spinning method. MXene, an emerging 2D conductive material, is applied to build internal conductive paths. ANF frameworks function as protective and skeleton structures to reduce the fiber oxidation probability and achieve superior strength. The obtained MXene@ANF fiber with superior conductivity (2515 S m^-1) and tensile strength (130 MPa) works as a promising sensor for smart fabrics to detect different human movements with abundant detection motions, fast response time (100 ms), and long service life (up to 1000 cycles). Benefiting from its high flexibility, it can be sewn into textile and gloves as a smart wearable device. Besides superior thermal stability, it shows promising electrothermal properties with wide heating temperature (25-123 °C) and fast heating temperature (10 s). Therefore, the MXene@ANF fiber with the skin-core structure shows great potential as a promising sensor to be applied in electric heating and smart wearable fabrics.