Double-Layered Conductive Network Design of Flexible Strain Sensors for High Sensitivity and Wide Working Range

A high stretchability fiber based on a synergistic three-dimensional conductive network for wide-range strain sensing

Fiber strain sensors are promising for constructing high-performance wearable electronic devices due to their light weight, high flexibility and excellent integration. However, the conductivity of most reported fiber strain sensors is severely degraded, following deformation upon stretching, and it is still a considerable challenge to achieve both high conductivity and stretchability. Herein, we have fabricated a fiber strain sensor with high conductivity and stretchability by integrating the AgNPs into the multi-walled carbon nanotube/graphene/thermoplastic polyurethane (MWCNT/GE/TPU) fiber. The tunneling-effect dominated MWCNT/GE layer bridges separated AgNP islands, endowing conductive fibers with the integrity of conductive pathways under large strain. By means of the synergistic effect of a three-dimensional conductive network, the fiber strain sensor of AgNPs/MWCNT/GE/TPU presents not only a high conductivity of 116 S m-1, but also a wide working range of up to 600% and excellent durability (8000 stretching-releasing cycles). Remarkably, benefiting from the crack propagation on the brittle AgNP layer, the fiber strain sensor exhibits a large resistance change in the strain range of 500-600%, and thus high sensitivity with a gauge factor of 545. This fiber strain sensor can monitor human physiological signals and body movement in real-time, including pulse and joint bending, which will contribute to the development of smart textiles and next-generation wearable devices.

Mechanism and Performance Evaluation of a Strain Sensor Made from a Composite Hydrogel Containing Conductive Fibers of Thermoplastic Polyurethane and Polyvinyl Alcohol

Monitoring human physiological conditions using flexible, stretchable strain sensors is an effective approach to prevent and treat critical illnesses, emergencies, and infectious diseases. However, achieving ultralow detection limits, high sensitivity, and a wide detection range in a cost-effective manner is challenging. In this study, a strain sensor was developed by embedding an adhesive hydrogel composed of polyvinyl alcohol, starch, and glutaraldehyde into conductive fibers made from thermoplastic polyurethane. By leveraging the high sensitivity of the conductive fibers and the wide detection range of the hydrogel, a robust dual-layer continuous conductive network was formed through their synergistic interaction. Tensile strength tests and other assessments indicated that the sensitivity of the sensor increased from a gauge factor of 49.32 (for fiber-based sensors) to 74.18, while the detection range expanded from 250 to 400%. Furthermore, the sensor demonstrated a low detection limit (0.6%), fast response and recovery times (80 ms/120 ms), and durability exceeding 800 cycles. Tests on pulse monitoring, joint movement, and voice recognition confirmed the significant applicability of the sensor for real-time monitoring of various physiological activities throughout a human's life. This study aims to provide technical support for the development of flexible wearable systems.

Ultrasensitive Flexible Strain Sensor Made with Carboxymethyl-Cellulose-Anchored Carbon Nanotubes/MXene for Machine-Learning-Assisted Handwriting Recognition

The combination of wearable sensors with machine learning enables intelligent perception in human-machine interaction and healthcare, but achieving high sensitivity and a wide working range in flexible strain sensors for signal acquisition and accurate recognition remains challenging. Herein, we introduced carboxymethyl cellulose (CMC) into a carbon nanotubes (CNTs)/MXene hybrid network, forming tight anchoring among the conductive materials and, thus, bringing enhanced interaction. The silicone-rubber-encapsulated CMC-anchored CNTs/MXene (CCM) strain sensor exhibits an excellent sensitivity (maximum gauge factor up to 71 294), wide working range (200%), ultralow detection limit (0.05%), and outstanding durability (over 10 000 cycles), which is superior to most of the recently reported counterparts also based on a conductive composite film. Moreover, the sensor achieves seamless integration with human skin with the help of a poly(acrylic acid) adhesive layer, successfully obtaining stable and clear waveforms with meaningful profiles from the human body. On this basis, we proposed and realized a novel in-air handwriting recognition method via extracting multiple features of high-quality strain signals assisted by deep neural networks, achieving a high classification accuracy of 98.00 and 94.85% for Arabic numerals and letters, respectively. Our work provides an effective approach for significantly improving strain sensing performance, thereby facilitating innovative applications of flexible sensors.

Flexible Strain Sensors Based on Thermoplastic Polyurethane Fabricated by Electrospinning: A Review

Over recent years, thermoplastic polyurethane (TPU) has been widely used as a substrate material for flexible strain sensors due to its remarkable mechanical flexibility and the ease of combining various conductive materials by electrospinning. Many research advances have been made in the preparation of flexible strain sensors with better ductility, higher sensitivity, and wider sensing range by using TPU in combination with various conductive materials through electrospinning. However, there is a lack of reviews that provide a systematic and comprehensive summary and outlook of recent research advances in this area. In this review paper, the working principles of strain sensors and electrospinning technology are initially described. Subsequently, recent advances in strain sensors based on electrospun TPU are tracked and discussed, with a focus on the incorporation of various conductive fillers such as carbonaceous materials, MXene, metallic materials, and conductive polymers. Moreover, the wide range of applications of electrospun TPU flexible strain sensors is thoroughly discussed. Finally, the future prospects and challenges of electrospun TPU flexible strain sensors in various fields are pointed out.

Nacre-Mimetic Structure Multifunctional Ion-Conductive Hydrogel Strain Sensors with Ultrastretchability, High Sensitivity, and Excellent Adhesive Properties

Recently, conductive hydrogels have emerged as promising materials for smart, wearable devices. However, limited mechanical properties and low sensitivity greatly restrict their lifespan. Based on the design of biomimetic-layered structure, the conductive hydrogels with nacre-mimetic structure were prepared by using layered acrylic bentonite (AABT) and phytic acid (PA) as multifunctional "brick" and "mortar" units. Among them, the unique rigid cyclic multihydroxyl structure of the "organic mortar" PA preserves both ultrastretchability (4050.02%) and high stress (563.20 kPa) of the hydrogel, which far exceeds most of the reported articles. Because of the synergistic effect of AABT and PA, the hydrogel exhibits an excellent adhesive strength (87.74 kPa). The role of AABT in the adhesive properties of hydrogels is proposed for the first time, and a general strategy for improving the adhesive properties of hydrogels by using AABT is demonstrated. Furthermore, AABT provides ion channels and PA ionizes abundant H+, conferring a high gauge factor (GF = 14.95) and excellent antimicrobial properties to the hydrogel. Also, inspired by fruit batteries, simple self-powered flexible sensors were developed. Consequently, this study provides knowledge for functional bentonite filler modified hydrogel, and the prepared multifunctional ionic conductive hydrogel shows great application potential in the field of intelligent wearable devices.

Electrospinning and electrospun polysaccharide-based nanofiber membranes: A review

The electrospinning technology has set off a tide and given rise to the attention of a widespread range of research territories, benefiting from the enhancement of nanofibers which made a spurt of progress. Nanofibers, continuously produced via electrospinning technology, have greater specific surface area and higher porosity and play a non-substitutable key role in many fields. Combined with the degradability and compatibility of the natural structure characteristics of polysaccharides, electrospun polysaccharide nanofiber membranes gradually infiltrate into the life field to help filter air contamination particles and water pollutants, treat wounds, keep food fresh, monitor electronic equipment, etc., thus improving the life quality. Compared with the evaluation of polysaccharide-based nanofiber membranes in a specific field, this paper comprehensively summarized the existing electrospinning technology and focused on the latest research progress about the application of polysaccharide-based nanofiber in different fields, represented by starch, chitosan, and cellulose. Finally, the benefits and defects of electrospun are discussed in brief, and the prospects for broadening the application of polysaccharide nanofiber membranes are presented for the glorious expectation dedicated to the progress of the eras.

A double-crack structure for bionic wearable strain sensors with ultra-high sensitivity and a wide sensing range

Flexible strain sensors are crucial in fully monitoring human motion, and they should have a wide sensing range and ultra-high sensitivity. Herein, inspired by lyriform organs, a flexible strain sensor based on the double-crack structure is designed. An MXene layer and an Au layer with cracks are constructed on both sides of the insulated polydimethylsiloxane (PDMS) film, forming an equivalent parallel circuit that guarantees the integrity of the conductive path under a large strain. The rapid disconnection of the crack junctions causes a significant change in the resistance value. Due to the effect of cracks on the conductive path, the sensitivity of the sensor is largely improved. Benefiting from the double-crack structure, the as-obtained sensor shows ultra-high sensitivity (maximum gauge factor of up to 14 373.6), a wide working range (up to 21%), a fast response time (183 ms) and excellent dynamical stability (almost no performance loss after 1000 stretching cycles and different frequency cycles). In practical applications, the sensor is applied to different parts of the human body to sense the deformation of the skin, demonstrating its great potential application value in human physiological detection and the human-machine interaction. This study can provide new ideas for preparing high-performance flexible strain sensors.

Electrospinning Nanofibers as Stretchable Sensors for Wearable Devices

Wearable devices attract great attention in intelligent medicine, electronic skin, artificial intelligence robots, and so on. However, boundedness of traditional sensors based on rigid materials unconstrained self-multilayer structure assembly and dense substrate in stretchability and permeability limits their applications. The network structure of the elastomeric nanofibers gives them excellent air permeability and stretchability. By introducing metal nanofillers, intrinsic conductive polymers, carbon materials, and other methods to construct conductive paths, stretchable conductors can be effectively prepared by elastomeric nanofibers, showing great potential in the field of flexible sensors. This perspective briefly introduces the representative preparations of conductive thermoplastic polyurethane, nylon, and hydrogel nanofibers by electrospinning and the application of integrated electronic devices in biological signal detection. The main challenge is to unify the stretchability and conductivity of the fiber structure.

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.