Self-Healing, Self-Adhesive Strain Sensors Made with Carbon Nanotubes/Polysiloxanes Based on Unsaturated Carboxyl-Amine Ionic Interactions

Highly Durable Silicone-Based Elastomers Achieved Through the Synergy of Bi-Incompatible Soft Segments and Multi-Scale Hydrogen Bonds

Developing a silicone elastomer with high strength, exceptional toughness, good crack tolerance, healability, and recyclability, poses significant challenges due to the inherent trade-offs between these properties. Herein, the design of silicone-based elastomers with a nanoscopic microphase separation structure and comprehensive mechanical properties is achieved by combining bi-incompatible soft segments and multi-scale hydrogen bonds. The formation of multi-scale hydrogen bonds involving urethane, urea, and 2-ureido-4[1H]-pyrimidinone (UPy) facilitates efficient reversible crosslinking of the synthesized polymer containing thermodynamically incompatible poly(dimethylsiloxane) (PDMS) and poly(propylene glycol) (PPG). The dynamic dissociation and recombination of hydrogen bonds, coupled with the forced compatibility and spontaneous separation of bi-incompatible soft segments, can effectively dissipate energy, particularly in the crack region during the stretching process. The obtained silicone-based elastomer exhibits a high break strength of 8.0 MPa, good elongation at break of 1910%, ultrahigh toughness of 67.8 MJ m-3, and unprecedented fracture energy of 31.8 kJ m-2 while maintaining their thermal stability, hydrophobicity, healability, and recyclability. This resilient and long-lasting silicone-based elastomer exhibits significant potential for use in flexible electronic devices.

High-Performance Multidirectional Flexible Strain Sensor for Human Motion and Health Monitoring

Multidirectional strain sensors are pivotal for wearable electronic devices and human-computer interaction. In this investigation, we translocate carbon/graphene (CB/Gr) conductive nanocomposites onto an Ecoflex flexible substrate via a facile technique encompassing reverse molding and spraying, culminating in the fabrication of a 45° strain rosette-shaped multidirectional flexible strain sensor. The sensor distinguishes itself with extraordinary performance characteristics, including high sensitivity (boasting a gauge factor of 35), an extensive strain range from 0 to 100%, exceptional linearity, a rapid response time of merely 200 ms, remarkable stability, and outstanding durability, effortlessly withstanding over 5000 stretch-release cycles. The sensor exhibits its exceptional capability to discern intricate movements, particularly in detecting human hand and neck motions. The sensor's remarkable comprehensive performance and strain direction recognition ability underscore its significant potential for diverse applications, notably in human-computer interaction, human motion monitoring, and health monitoring.

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.

Ionic Conductive Cellulose-Based Hydrogels with Superior Long-Lasting Moisture and Antifreezing Features for Flexible Strain Sensor Applications

Nowadays, wearable devices derived from flexible conductive hydrogels have attracted enormous attention. Nevertheless, the utilization of conductive hydrogels in practical applications under extreme conditions remains a significant challenge. Herein, a series of inorganic salt-ion-enhanced conductive hydrogels (HPE-LiCl) consisting of hydroxyethyl cellulose, hydroxyethyl acrylate, lithium chloride, and ethylene glycol/water binary solvent were fabricated via a facile one-pot method. Apart from outstanding self-adhesion, high stretchability, and remarkable fatigue resistance, the HPE-LiCl hydrogels possessed especially excellent antifreezing and long-lasting moisture performances, which could maintain satisfactory flexibility and electric conductivity over extended periods of time, even in challenging conditions such as extremely low temperatures (as low as -40 °C) and high temperatures (as high as 80 °C). Consequently, the HPE-LiCl-based sensor could timely and accurately monitor various human motion signals even in adverse environments and after long-term storage. Hence, this work presents a facile strategy for the design of long-term reliable hydrogels as smart strain sensors, especially used in extreme environments.

Synergistic Self-Healing Enhancement in Multifunctional Silicone Elastomers and Their Application in Smart Materials

Organosilicon polymers (silicones) are of enduring interest both as an established branch of polymer chemistry and as a segment of commercial products. Their unique properties were exploited in a wide range of everyday applications. However, current silicone trends in chemistry and materials engineering are focused on new smart applications, including stretchable electronics, wearable stress sensors, protective coatings, and soft robotics. Such applications require a fresh approach to methods for increasing the durability and mechanical strength of polysiloxanes, including crosslinked systems. The introduction of self-healing options to silicones has been recognized as a promising alternative in this field, but only carefully designed multifunctional systems operating with several different self-healing mechanisms can truly address the demands placed on such valuable materials. In this review, we summarized the progress of research efforts dedicated to the synthesis and applications of self-healing hybrid materials through multi-component systems that enable the design of functional silicon-based polymers for smart applications.

Ductile Effect of PGA/PCL Blending Plastics Using a Novel Ionic Chain Extender with Non-Covalent Bonds

Polyglycolic acid (PGA) is a promising polymer in the packaging field owing to its excellent hydrolysis, heat resistance, and gas barrier properties, but it is limited in application due to its poor toughness. For this reason, a covalently bonded chain extender is introduced to increase compatibility with flexible polymers. However, covalent bonds are unfavorable for application to degradable plastics because of the energy required for reverse reactions. Therefore, we intended to effectively control the ductility of blending plastics by using a novel ionic chain extender with a relatively weaker non-covalent bond than the existing covalent bond. Polycaprolactone (PCL), which has biodegradability and flexibility, was selected as a blending polymer. For comparison, a covalently reactive chain extender (G-CE) and a non-covalently ionic chain extender (D-CE) were synthesized and compounded with blending plastics. Each chain extender improved the compatibility between PGA and PCL, and the ductility of the PGA/PCL blending plastics was more greatly enhanced with non-covalently bonded D-CE than with covalently bonded G-CE. At this time, the ductility of the PGA/PCL(90/10) blending plastic without CE was 7.2%, the ductility of blending plastic with D-CE (10D) was 26.6%, and the ductility of blending plastic with G-CE (10G) was 18.6%. Therefore, it was confirmed that the novel ionic chain extender inducing non-covalent bonds improves the compatibility between PGA and PCL and is more advantageous in enhancing ductility through a reversible reaction.

Self-Healing Silicone Materials: Looking Back and Moving Forward

This review is dedicated to self-healing silicone materials, which can partially or entirely restore their original characteristics after mechanical or electrical damage is caused to them, such as formed (micro)cracks, scratches, and cuts. The concept of self-healing materials originated from biomaterials (living tissues) capable of self-healing and regeneration of their functions (plants, human skin and bones, etc.). Silicones are ones of the most promising polymer matrixes to create self-healing materials. Self-healing silicones allow an increase of the service life and durability of materials and devices based on them. In this review, we provide a critical analysis of the current existing types of self-healing silicone materials and their functional properties, which can be used in biomedicine, optoelectronics, nanotechnology, additive manufacturing, soft robotics, skin-inspired electronics, protection of surfaces, etc.

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.

Self-Healable Elastomeric Network with Dynamic Disulfide, Imine, and Hydrogen Bonds for Flexible Strain Sensor

Self-healable and stretchable elastomeric material is essential for the development of flexible electronics devices to ensure their stable performance. In this study, a strain sensor (PIH₂ T₁ -tri/CNT-3) composed of self-repairable crosslinked elastomer substrate (PIH₂ T₁ -tri, containing multiple reversible repairing sites such as disulfide, imine, and hydrogen bonds) and conductive layer (carbon nanotube, CNT) was prepared. The PIH₂ T₁ -tri elastomer had excellent self-healing ability (healing efficiency=91 %). It exhibited good mechanical integrity in terms of elongation at break (672 %), tensile strength (1.41 MPa). The Young's modulus (0.39 MPa) was close to that of human skin. The PIH₂ T₁ -tri/CNT-3 sensor also demonstrated an effective self-healing function for electrical conduction and sensing property. Meanwhile, it had high sensitivity (gauge factor (GF)=24.1), short response time (120 ms), and long-term durability (4000 cycles). This study offers a novel self-healable elastomer platform with carbon based conductive components to develop flexible strain sensors towards high performance soft electronics.

Ultrasensitive, Highly Stable, and Flexible Strain Sensor Inspired by Nature

For advanced flexible strain sensors, it is not difficult to achieve high sensitivity only. However, integrating high sensitivity, high stability, and high durability into one sensor still remains a great challenge. Fortunately, natural creatures with diversified excellent performances have given us a lot of ready-made solutions. Here, scorpion and spiderweb are selected as coupling bionic prototypes, which are famous for their ultrasensitive sensing capacity and excellent structural durability, respectively. Based on that, a bioinspired strain sensor is successfully fabricated. The results demonstrate that the bioinspired strain sensor has a sensitivity of 940.5 in the strain range of 0-1.5% and a sensitivity of 2742.3 between 1.5 and 2.5%. Meantime, this sensor with a spiderweb-like reticular structure has a great improvement in stability and durability. Specifically, the sensor exhibits excellent stability during bending and stretching cycles over 80,000 times. Moreover, the response time and recovery time of the sensor are 169 and 195 ms, respectively. Besides, the sensor also has functions such as vibrating frequency identification due to its low hysteresis. Based on the excellent performance, the sensor can be applied to monitor human body motions serving as wearable electronics.