Cross-Talk Signal Free Recyclable Thermoplastic Polyurethane/Graphene-Based Strain and Pressure Sensor for Monitoring Human Motions

Hysteresis-Free Temperature Sensing with Printable Electronic Skins Made of Liquid Polyisoprene/CNTs

Developing an electronic skin (e-skin) is becoming popular due to its capability to mimic human skin's ability to detect various stimuli. Mostly, such skins are tactile-based sensors. However, the exploration of nontactile-based sensing capability in the e-skin is still in a nascent stage. Herein, we report an approach toward developing electrical hysteresis- and cross-interference-free nontactile e-skin using liquid polyisoprene with an ultralow concentration of multiwalled carbon nanotubes (ϕ = 0.006 volume fraction) by leveraging the stencil printing technique. The impact of cross-linking the samples was studied. Uncross-linked samples demonstrated higher electrical conductivity than the cross-linked samples. A coarse-grained phenomenological model with molecular dynamics simulation was utilized to investigate filler network formation and percolation that dictate the conductivity of uncross-linked and cross-linked samples. Simulation studies supported the fidelity of the experimental findings. The uncross-linked e-skin demonstrated a higher temperature sensitivity (-1.103%/°C) than the cross-linked e-skin (-0.320%/°C) in the thermal conduction mode. Despite the superior sensitivity of the uncross-linked e-skin, the cross-linked systems demonstrated superior cyclic stability (35 thermal cycles), ensuring reliable sensor readings over extended usage. Judicious choice of encapsulant warranted the cross-linked e-skin sensor to nullify the impact of moisture on signal output, thereby providing cross-interference-free results. The optimized e-skin sample retained a similar thermal sensitivity even when used in the nontactile mode. From the application purview, the utility of the developed sensor was tested successfully for nontactile sensing of human body temperature. Additionally, the sensor was utilized to determine the respiratory profile by integrating the developed sensor into a wearable mask. This study advances nontactile e-skin-based sensing technology and opens new avenues for creating wearable and IoT devices for healthcare and human-machine interactions.

Polyurethane/Carbon Nanotube-Based ThermoSense Electronic Skin: Perception to Decision Making Aided by Internet of Things Brain

Human skin has several receptors collaborating with the brain to provide appropriate "decisions" when applying stimuli. Several research articles state that biomimetic electronic skin (e-skin) is reportedly used for sensor-related applications and performs similarly to natural skin. However, research reporting the capability of the e-skin to make decisions and therefore react upon exposure to adverse conditions is still in its nascent stage. Herein, we report the development of an e-skin, ThermoSense, that can thermoregulate by making appropriate decisions. Thermoplastic polyurethane and multiwalled carbon nanotubes were used as the model composite. The heating and sensing capabilities of the optimized e-skin were studied in detail. In the study window, the e-skin demonstrated excellent electrothermal conversion efficiency by generating a temperature of 192 °C, consuming a power of 2.23 W. A finite element modeling (FEM) was adopted to determine the distribution of the filler in the case of the optimized e-skin and thus was used to probe the reason for the heating across the e-skin via mapping of the internal energy across the sample. FEM results and experimental findings are in strong agreement. Additionally, the e-skin demonstrated its capability to act as a thermal sensor with a 0.947% °C-1 sensitivity. To integrate the decision-making capabilities of the e-skin, an Internet of Things (IoT) brain console was made using the e-skin and electronic chips by leveraging More than Moore's concept. The IoT brain was automated with decision-making programming that was controllable via an in-house-developed mobile application. The console worked exclusively under simulated conditions. When there was a shift from the set point temperature, it started to heat. Postusage, the e-skin matrix was recycled, and the recycled e-skin demonstrated a marginal decrement in performance attributes. This study opens new avenues for developing decision-making e-skins for next-generation human-machine interphases.

Elastomeric Ionic Hydrogel-Based Flexible Moisture-Electric Generator for Next-Generation Wearable Electronics

Rapid consumption of traditional energy resources creates utmost research interest in developing self-sufficient electrical devices to progress next-generation electronics to a level up. To address the global energy crisis, moisture-electric generators (MEGs) are proving to be an emerging technology in this field, capable of powering wearable electronics by harvesting energy from abundantly available ambient moisture without any requirement for external/additional energy. Recent advances in MEGs generally utilize an inorganic, metal, or petroleum-based polymeric material as an active material, which may produce sufficient current but lacks the flexibility and stretchability required for wearable electronics. Herein, we prepared an elastomer-based ionic hydrogel as an active material, and an MEG was fabricated by placing the ionic hydrogel on a PET sheet with two copper tapes on both sides of the hydrogel. The preparation of the hydrogel was thoroughly optimized and characterized in terms of spectroscopic analysis, swelling, water retention, and mechanical and rheological studies. The highly stretchable (350%) fabricated MEG is capable of producing a short-circuit current (JSC) of 16.1 μA/cm2, an open-circuit voltage (VOC) of 0.24 V, and a power density of 3.86 μW/cm2. The synergistic effect of the ion concentration gradient and the redox reaction on electrodes can be considered MEG's working principle. Apart from the current generation, this device is also used as a self-powered electronic sensor to monitor different physical activities by measuring breathing patterns. This prepared device is also capable of sensing the proximity of a hand. Therefore, our low-cost, easily fabricable, sustainable MEG device can be a potential aspirant for next-generation self-powered wearable electronics in healthcare applications.

A Flexible Wearable Sensor Based on Laser-Induced Graphene for High-Precision Fine Motion Capture for Pilots

There has been a significant shift in research focus in recent years toward laser-induced graphene (LIG), which is a high-performance material with immense potential for use in energy storage, ultrahydrophobic water applications, and electronic devices. In particular, LIG has demonstrated considerable potential in the field of high-precision human motion posture capture using flexible sensing materials. In this study, we investigated the surface morphology evolution and performance of LIG formed by varying the laser energy accumulation times. Further, to capture human motion posture, we evaluated the performance of highly accurate flexible wearable sensors based on LIG. The experimental results showed that the sensors prepared using LIG exhibited exceptional flexibility and mechanical performance when the laser energy accumulation was optimized three times. They exhibited remarkable attributes, such as high sensitivity (~41.4), a low detection limit (0.05%), a rapid time response (response time of ~150 ms; relaxation time of ~100 ms), and excellent response stability even after 2000 s at a strain of 1.0% or 8.0%. These findings unequivocally show that flexible wearable sensors based on LIG have significant potential for capturing human motion posture, wrist pulse rates, and eye blinking patterns. Moreover, the sensors can capture various physiological signals for pilots to provide real-time capturing.

Crosstalk-free graphene-liquid elastomer based printed sensors for unobtrusive respiratory monitoring

Flexible strain sensors have garnered attraction in the human healthcare domain. However, caveats like crosstalk and noise associated with the output signal of such a sensor often limit the accuracy. Hence, developing a strain sensor via frugal engineering is critical, thereby warranting its mass utility. A stencil printable graphene/liquid elastomeric crosstalk-free strain sensor for unobtrusive respiratory monitoring is reported herein. Printing supports the frugality of the process and avoids complex fabrication. The sensor was mounted on a wearable mask, and the sensor console was fabricated. The console demonstrated the capability to detect the respiratory profile at room and low temperature (-26 °C) with an SNR of -12.85 dB. Developed sensors could nullify the impact of temperature and humidity and generate respiratory signals due to strain induced by breathing. A model experiment was conducted to support the fidelity of the strain mechanism. The console demonstrated excellent stability (over 500 cycles) with a sensitivity of -196.56 (0-0.17% strain) and 117.49 (0.17-0.34% strain). The console could accurately determine conditions like eupnea, tachypnoea, etc., and transmit the data wirelessly via Bluetooth. These findings solve major caveats in flexible sensor development by focusing on selectivity, sensitivity, and stability.

Synthesis of gallic acid-grafted epoxidized natural rubber and its role in self-healable flexible temperature sensors

Developing a flexible temperature sensor with appreciable sensitivity is critical for advancing research related to flexible electronics. Although various flexible sensors are available commercially, most such temperature sensors are made from polymeric materials obtained from petrochemical resources. Such sensors will contribute to electronic waste and increase the carbon footprint after usage. While there are reports on various sensors made from sustainable polymers, research related to developing self-healable flexible temperature sensors made from sustainable polymers is significantly less. Herein, we report on developing a flexible temperature sensor made of gallic acid-grafted epoxidized natural rubber and multi-walled carbon nanotubes. Various spectroscopic and thermal techniques vetted the modification of the epoxidized natural rubber. The highest grafting of 20.9% was achieved in the selected window of stoichiometry. A self-healing behavior was achieved by leveraging the FeCl3 based metal-ligand crosslinking of the composite. The healing efficiency was noted to be 31.2% for the composite material. The fabricated sensor demonstrated an electrical resistance of 4.46 × 103 Ω, thereby warranting the composite to demonstrate an Ohmic behavior in the I-V plot. Appropriate data fitting suggested a variable range hopping mechanism as causation towards excellent electrical conduction. The temperature sensitivity and the thermal index of the developed sensor were noted to be -0.17% °C-1 and 781.2 K, respectively, in the temperature range of 30 °C to 50 °C. The proposed method of fabricating sustainable, high-strength, self-healable, and robust temperature sensors and conductors is a unique and value-added approach for next-generation flexible electronics.

Bioinspired Fast Room-Temperature Self-Healing, Robust, Adhesive, and AIE Fluorescent Waterborne Polyurethane via Hierarchical Hydrogen Bonds and Use as a Strain Sensor

Developing a new generation of ecofriendly water-based polymeric materials that integrate mechanical robustness, fast room-temperature self-healing, adhesive, and fluorescence remains a formidable challenge. Herein, inspired by titin protein, a series of novel waterborne polyurethanes (WPU-CHZ-NAGA) containing irregular 6-fold and diamide hydrogen bonds are synthesized by introducing carbohydrazide (CHZ) and N,N-bis(2-hydroxyethyl)-3-amino propionyl glycinamide (HO-NAGA-OH) groups. The representative WPU-CHZ₂-NAGA₃ exhibits outstanding mechanical properties (tensile strength of 36.58 MPa, tearing energy of 81.2 kJ m^-2, and toughness of 125.82 MJ m^-3) and fast room-temperature self-healing ability with the aid of ethanol (≥90% within 8 h) originated from hierarchical hydrogen bonds. These properties are superior to those of most of the reported room-temperature self-healing polymer materials. Benefiting from plentiful hydrogen bonds, the WPU matrix achieves excellent adhesive properties without heating or adding curing agents. Interestingly, WPU-CHZ₂-NAGA₃ film emits inherent blue fluorescence due to the aggregation-induced emission effect of tertiary amine groups, and its potential applications in information encryption and anticounterfeiting are further demonstrated. Specially, a eutectic gel strain sensor is also fabricated with WPU-CHZ₂-NAGA₃ and deep eutectic solvent by a simple physical blending method, which can be used to monitor the movement of human fingers and wrists as well as the change in body temperature. In summary, this work provides new insight into the design and synthesis of multifunctional WPU with fast room-temperature self-healing and high mechanical properties.

Multiscale Analysis of the Highly Stretchable Carbon−Based Polymer Strain Sensor

In this paper, a multiscale analysis method was proposed to simulate carbon nanoparticles (CNPs)−filled polymers which can be strain sensors applied in wearable electronic devices, flexible skin, and health monitoring fields. On the basis of the microstructure characteristics of the composite, a microscale representative volume element model of the CNPs−filled polymer was established using the improved nearest−neighbor algorithm. By finite element analysis, the variation of the junction widths of adjacent aggregates can be extracted from the simulation results. Then, according to the conductive mechanism of CNP−filled polymers, the composite was simplified as a circuit network composed of vast random resistors which were determined by the junction widths between adjacent aggregates. Hence, by taking junction widths as the link, the resistance variation of the CNPs−filled polymer with the strain can be obtained. To verify the proposed method, the electromechanical responses of silicone elastomer filled with different CNPs under different filling amounts were investigated numerically and experimentally, respectively, and the results were in good agreement. Therefore, the multiscale analysis method can not only reveal the strain−sensing mechanism of the composite from the microscale, but also effectively predict the electromechanical behavior of the CNPs−filled polymer with different material parameters.