High-Performance Strain Sensors Based on Au/Graphene Composite Films with Hierarchical Cracks for Wide Linear-Range Motion Monitoring

Matrix Swelling-Induced Precracking in Graphene Woven Fabric for Ultrasensitive Strain Sensors

The growing demand for highly sensitive flexible strain sensors in applications such as wearable electronics, healthcare monitoring, and environmental sensing has driven the development of materials capable of detecting subtle deformations with high precision. Herein, we introduce a precracked strain sensor based on solvent-swollen graphene woven fabric/polydimethylsiloxane (sGWF/PDMS) composites, designed to achieve ultrahigh gauge factors (GFs) and enhanced responsiveness to minor deformations. By utilizing PDMS swelling to induce network microcracks within the graphene structure, the sGWF/PDMS composites exhibit substantially improved sensitivity compared to traditional graphene-based strain sensors. Systematic in situ SEM analyses reveal that these preexisting microcracks expand readily under minor strain, resulting in rapid resistance changes that underpin the high sensitivity achieved. With GFs reaching up to 82,378 at only 2.8% stretching strain, the sGWF/PDMS composites demonstrate excellent performance across various applications, including human motion detection such as monitoring pulses, eye blinks, and speech-related movements, as well as detecting environmental disturbances such as water surface ripples. These findings highlight matrix-swollen composites as a promising platform for high-sensitivity, low-strain detection, offering great potential for advancements in wearable electronics, environmental monitoring, and other precision sensing applications.

Preliminary Characterization of a Novel Aerosol Jet-Printed Strain Sensor for Feasibility Assessment in a Variable Stiffness Arterial Simulator Application

Wearable strain sensors are widespread in many fields, including the biomedical field where they are used for their stretchability and ability to be applied to non-regular surfaces. The study of the propagation speed of the pressure wave generated by the heartbeat within vessels, i.e., the Pulse Wave Velocity (PWV), is of significant relevance in this field to assess arterial stiffness, a parameter commonly used for the early diagnosis of cardiovascular diseases. In this context, arterial simulators are useful tools to study the relationship between the PWV and other hemodynamic quantities in vitro. This study aims to characterize novel strain sensors to assess their suitability within an arterial simulator capable of varying the stiffness of an arterial surrogate by varying the transmural pressure. Six sensors deposited on arterial surrogates by Aerosol Jet Printing technology were subjected to deformation through a load frame. The results show that the sensors were able to distinguish strains of 0.1%, the maximum strain was around 6-8%, and the fatigue strength depended strongly on the strain rate.

Bioinspired Ultrasensitive Flexible Strain Sensors for Real-Time Wireless Detection of Liquid Leakage

Liquid leakage of pipeline networks not only results in considerable resource wastage but also leads to environmental pollution and ecological imbalance. In response to this global issue, a bioinspired superhydrophobic thermoplastic polyurethane/carbon nanotubes/graphene nanosheets flexible strain sensor (TCGS) has been developed using a combination of micro-extrusion compression molding and surface modification for real-time wireless detection of liquid leakage. The TCGS utilizes the synergistic effects of Archimedean spiral crack arrays and micropores, which are inspired by the remarkable sensory capabilities of scorpions. This design achieves a sensitivity of 218.13 at a strain of 2%, which is an increase of 4300%. Additionally, it demonstrates exceptional durability by withstanding over 5000 usage cycles. The robust superhydrophobicity of the TCGS significantly enhances sensitivity and stability in detecting small-scale liquid leakage, enabling precise monitoring of liquid leakage across a wide range of sizes, velocities, and compositions while issuing prompt alerts. This provides critical early warnings for both industrial pipelines and potential liquid leakage scenarios in everyday life. The development and utilization of bioinspired ultrasensitive flexible strain sensors offer an innovative and effective solution for the early wireless detection of liquid leakage.

Silver-decorated laser-induced graphene for a linear, sensitive, and almost hysteresis-free piezoresistive strain sensor

A new approach has recently emerged in graphene synthesis by direct laser writing (LIG), which is highly economical and scalable, unlike previous methods. Here, the sputtering method has been used to coat silver onto the laser-induced graphene-based sensor. The results demonstrate that the chosen approach substantially impacts the expected outcomes. The initial resistance values were consistent across the different sensor samples. The average resistance was slightly lower in the silver-coated samples compared to the uncoated samples, demonstrating the effectiveness of the Ag coating in enhancing the electrical conductivity of the LIG material. However, the difference in resistance was not statistically significant. The electromechanical behavior of the Ag-coated LIG strain sensor was tested under cyclic tensile strain. The gauge factor increased from 12.9-14.7 for the uncoated LIG sensor to 17.2-26.7 for the Ag-coated sensor, with the difference growing at higher strains. At 5%, 30%, and 70% strain, the gauge factor increased by 30%, 80%, and 82%, respectively. Sensors measuring 1-70% strain were developed, enabling use in various applications. Blood pulse measurements showed the silver-coated sample produced more uniform and reliable results than the uncoated sample. The number of beats matched a commercial pulse oximeter. This sensitivity, linearity, and reliability demonstrate the potential for commercializing these sensors.

Inductive Frequency-Coded Sensor for Non-Destructive Structural Strain Monitoring of Composite Materials

Structural composite materials have gained significant appeal because of their ability to be customized for specific mechanical qualities for various applications, including avionics, wind turbines, transportation, and medical equipment. Therefore, there is a growing demand for effective and non-invasive structural health monitoring (SHM) devices to supervise the integrity of materials. This work introduces a novel sensor design, consisting of three spiral resonators optimized to operate at distinct frequencies and excited by a feeding strip line, capable of performing non-destructive structural strain monitoring via frequency coding. The initial discussion focuses on the analytical modeling of the sensor, which is based on a circuital approach. A numerical test case is developed to operate across the frequency range of 100 to 400 MHz, selected to achieve a balance between penetration depth and the sensitivity of the system. The encouraging findings from electromagnetic full-wave simulations have been confirmed by experimental measurements conducted on printed circuit board (PCB) prototypes embedded in a fiberglass-based composite sample. The sensor shows exceptional sensitivity and cost-effectiveness, and may be easily integrated into composite layers due to its minimal cabling requirements and extremely small profile. The particular frequency-coded configuration enables the suggested sensor to accurately detect and distinguish various structural deformations based on their severity and location.

A Flexible Wearable Strain Sensor Based on Nano-Silver-Modified Laser-Induced Graphene for Monitoring Hand Movements

The advancement in performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting the laser parameters to enhance the LIG's performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

Highly Sensitive Biomimetic Crack Pressure Sensor with Selective Frequency Response

High-sensitivity sensors in practical applications face the issue of environmental noise interference, requiring additional noise reduction circuits or filtering algorithms to improve the signal-to-noise ratio (SNR). To address this issue, this study proposes a biomimetic crack pressure sensor with selective frequency response based on hydrogel dampers. The core of this research is to construct a biomimetic crack pressure sensor with selective frequency response using the high-pass filtering characteristics of gelatin-chitosan hydrogels. This design, inspired by the slit sensilla and stratum corneum structure of spider legs, delves into the material properties and principles of hydrogel dampers, exploring their application in biomimetic crack pressure sensors, including parameter selection, structural design, and performance optimization. By delving into the nuanced characteristics and working principles of hydrogel dampers, their integration in biomimetic crack pressure sensors is examined, focusing on aspects like parameter selection, structural engineering, and performance enhancement to selectively sieve out low-frequency noise and transmit target vibrational signals. Experimental results demonstrate that this innovative sensor, while suppressing low-frequency vibration signals, can selectively detect high-frequency signals with high sensitivity. At different vibration frequencies, the relative change in resistance exceeds 200%, and the sensor sensitivity is 7 × 104 kPa-1. Furthermore, this sensor was applied to human voice detection, and the corresponding results verified its frequency-selective performance evidently. This study not only proposes a new design for pressure sensors but also offers fresh insights into the application of biomimetic crack pressure sensors in intricate environments.

High-Performance Airflow Sensors Based on Suspended Ultralong Carbon Nanotube Crossed Networks

Airflow sensors are in huge demand in many fields such as the aerospace industry, weather forecasting, environmental monitoring, chemical and biological engineering, health monitoring, wearable smart devices, etc. However, traditional airflow sensors can hardly meet the requirements of these applications in the aspects of sensitivity, response speed, detection threshold, detection range, and power consumption. Herein, this work reports high-performance airflow sensors based on suspended ultralong carbon nanotube (CNT) crossed networks (SCNT-CNs). The unique topologies of SCNT-CNs with abundant X junctions can fully exhibit the extraordinary intrinsic properties of ultralong CNTs and significantly improve the sensing performance and robustness of SCNT-CNs-based airflow sensors, which simultaneously achieved high sensitivity, fast response speed, low detection threshold, and wide detection range. Moreover, the capability for encapsulation also guaranteed the practicality of SCNT-CNs, enabling their applications in respiratory monitoring, flow rate display and transient response analysis. Simulations were used to unveil the sensing mechanisms of SCNT-CNs, showing that the piezoresistive responses were mainly attributed to the variation of junction resistances. This work shows that SCNT-CNs have many superiorities in the fabrication of advanced airflow sensors as well as other related applications.

A visualization method for quickly detecting nitrite ions in breath condensate using a portable closed bipolar electrochemical sensor

A portable and non-invasive sensor presents an innovative way to measure inflammation biomarkers in exhaled breath condensate (EBC). This research is focused on developing a miniaturized bipolar electrochemical sensor that can be connected to a smartphone app. This device will be able to detect adding known amounts of nitrite (spikes) to a salt solution and small amounts of nitrite ions in collected real samples in EBC. The sensor was fabricated and tested for its rapid electron transfer capability and ability to detect nitrite ions even at very low concentrations and low real sample levels. In the proposed setup, when the required potential was applied by using a direct power supply, the nitrite ions were oxidized electrocatalytically at amine-functionalized graphene oxide (AGO) decorated with gold nanoparticles on a carbon paper anodic pole. On the other hand, the reduction reaction of Prussian blue occurred at the cathodic pole of the bipolar electrode simultaneously. This strategy led to a change in color from blue to white as a result of the reduction process and the color change is proportional to the concentration of nitrite ions in the analytical solution. The combination of smartphones with the colorimetric method has resulted in a platform for the detection of test strips that is more visual and convenient. The amperometry and voltammetric methods of nitrite detection showed a linear range of up to 1230 μM. The bipolar electrochemical sensor was able to detect the clinically relevant range of nitrite from 0.5 to 85 μM in a buffer with an ultralow detection limit (LOD) of 250 nM (S/N = 3), fast response and excellent selectivity. It was benchmarked by utilizing pre-characterized real EBC samples to differentiate patients with respiratory diseases from healthy volunteers. By tracking the results of nitrite measurements over time, it has become possible to detect trends and changes in an individual's nitrite ion concentration and to potentially identify lung inflammation earlier.

2D Materials in Flexible Electronics: Recent Advances and Future Prospectives

Flexible electronics have recently gained considerable attention due to their potential to provide new and innovative solutions to a wide range of challenges in various electronic fields. These electronics require specific material properties and performance because they need to be integrated into a variety of surfaces or folded and rolled for newly formatted electronics. Two-dimensional (2D) materials have emerged as promising candidates for flexible electronics due to their unique mechanical, electrical, and optical properties, as well as their compatibility with other materials, enabling the creation of various flexible electronic devices. This article provides a comprehensive review of the progress made in developing flexible electronic devices using 2D materials. In addition, it highlights the key aspects of materials, scalable material production, and device fabrication processes for flexible applications, along with important examples of demonstrations that achieved breakthroughs in various flexible and wearable electronic applications. Finally, we discuss the opportunities, current challenges, potential solutions, and future investigative directions about this field.

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.

Multifunctional Flexible MXene/AgNW Composite Thin Film with Ultrahigh Conductivity Enabled by a Sandwich-Structured Assembly Strategy

Flexible composite films have attracted considerable attention due to great potential for healthcare, telecommunication, and aerospace. However, it is still challenging to achieve high conductivity and multifunctional integration, mainly due to poorly designed composite structures of these films. Herein, a novel sandwich-structured assembly strategy is proposed to fabricate flexible composite thin films made of Ag nanowire (AgNW) core and MXene layers by combination of spray coating and vacuum filtration process. In this case, ultrathin MXene layers play crucial roles in constructing compact composite structures strongly anchored to substrate with extensive hydrogen-bonding interactions. The resultant sandwich-structured MXene/AgNW composite thin films (SMAFs) exhibit ultrahigh electrical conductivity (up to 27193 S cm-1 ), resulting in exceptional electromagnetic interference shielding effectiveness of 16 223.3 dB cm2 g-1 and impressive Joule heating performance with rapid heating rate of 10.4 °C s-1 . Moreover, the uniform SMAFs can also be facilely cut into kirigami-patterned interconnects, which indicate superior strain-insensitive conductance even after long-term exposure to extreme temperatures. The demonstrated strategy offers a significant paradigm to construct multifunctional composite thin films for next-generation integrated flexible electronics with practical applications.

The 3D Printing of Nanocomposites for Wearable Biosensors: Recent Advances, Challenges, and Prospects

Notably, 3D-printed flexible and wearable biosensors have immense potential to interact with the human body noninvasively for the real-time and continuous health monitoring of physiological parameters. This paper comprehensively reviews the progress in 3D-printed wearable biosensors. The review also explores the incorporation of nanocomposites in 3D printing for biosensors. A detailed analysis of various 3D printing processes for fabricating wearable biosensors is reported. Besides this, recent advances in various 3D-printed wearable biosensors platforms such as sweat sensors, glucose sensors, electrocardiography sensors, electroencephalography sensors, tactile sensors, wearable oximeters, tattoo sensors, and respiratory sensors are discussed. Furthermore, the challenges and prospects associated with 3D-printed wearable biosensors are presented. This review is an invaluable resource for engineers, researchers, and healthcare clinicians, providing insights into the advancements and capabilities of 3D printing in the wearable biosensor domain.

Metal-Oxide Heterojunction: From Material Process to Neuromorphic Applications

As technologies like the Internet, artificial intelligence, and big data evolve at a rapid pace, computer architecture is transitioning from compute-intensive to memory-intensive. However, traditional von Neumann architectures encounter bottlenecks in addressing modern computational challenges. The emulation of the behaviors of a synapse at the device level by ionic/electronic devices has shown promising potential in future neural-inspired and compact artificial intelligence systems. To address these issues, this review thoroughly investigates the recent progress in metal-oxide heterostructures for neuromorphic applications. These heterostructures not only offer low power consumption and high stability but also possess optimized electrical characteristics via interface engineering. The paper first outlines various synthesis methods for metal oxides and then summarizes the neuromorphic devices using these materials and their heterostructures. More importantly, we review the emerging multifunctional applications, including neuromorphic vision, touch, and pain systems. Finally, we summarize the future prospects of neuromorphic devices with metal-oxide heterostructures and list the current challenges while offering potential solutions. This review provides insights into the design and construction of metal-oxide devices and their applications for neuromorphic systems.

A Privacy and Energy-Aware Federated Framework for Human Activity Recognition

Human activity recognition (HAR) using wearable sensors enables continuous monitoring for healthcare applications. However, the conventional centralised training of deep learning models on sensor data poses challenges related to privacy, communication costs, and on-device efficiency. This paper proposes a federated learning framework integrating spiking neural networks (SNNs) with long short-term memory (LSTM) networks for energy-efficient and privacy-preserving HAR. The hybrid spiking-LSTM (S-LSTM) model synergistically combines the event-driven efficiency of SNNs and the sequence modelling capability of LSTMs. The model is trained using surrogate gradient learning and backpropagation through time, enabling fully supervised end-to-end learning. Extensive evaluations of two public datasets demonstrate that the proposed approach outperforms LSTM, CNN, and S-CNN models in accuracy and energy efficiency. For instance, the proposed S-LSTM achieved an accuracy of 97.36% and 89.69% for indoor and outdoor scenarios, respectively. Furthermore, the results also showed a significant improvement in energy efficiency of 32.30%, compared to simple LSTM. Additionally, we highlight the significance of personalisation in HAR, where fine-tuning with local data enhances model accuracy by up to 9% for individual users.

Skin-Inspired Patterned Hydrogel with Strain-Stiffening Capability for Strain Sensors

Flexible materials with ionic conductivity and stretchability are indispensable in emerging fields of flexible electronic devices as sensing and protecting layers. However, designing robust sensing materials with skin-like compliance remains challenging because of the contradiction between softness and strength. Herein, inspired by the modulus-contrast hierarchical structure of biological skin, we fabricated a biomimetic hydrogel with strain-stiffening capability by embedding the stiff array of poly(acrylic acid) (PAAc) in the soft polyacrylamide (PAAm) hydrogel. The stress distribution in both stiff and soft domains can be regulated by changing the arrangement of patterns, thus improving the mechanical properties of the patterned hydrogel. As expected, the resulting patterned hydrogel showed its nonlinear mechanical properties, which afforded a high strength of 1.20 MPa while maintaining a low initial Young's modulus of 31.0 kPa. Moreover, the array of PAAc enables the patterned hydrogel to possess protonic conductivity in the absence of additional ionic salts, thus endowing the patterned hydrogel with the ability to serve as a strain sensor for monitoring human motion.

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.