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In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by the need for more accurate and efficient ice detection methods, which are crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors tested under varied and controlled atmospheric conditions exhibit a remarkable potential to enhance ice detection systems for aircraft. Their lightweight, efficient, and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

Polyaniline (PANI) is an important conductive-polymer gas-sensing material with working temperature and mechanical flexibilities superior to those of conventional metal oxide sensing materials. However, its applicability is limited by its low sensitivity, high detection limits, and long response/recovery times. In this study, we prepared PANI/WS2 composites via chemical oxidative polymerization and mechanical blending. A multilayer sensor structure—sequentially printed silver-paste heating electrodes, fluorene polyester insulating layer, silver interdigitated electrodes, and sensing material layer—was fabricated on a polyimide substrate via flexible microelectronic printing and systematically characterized using scanning electron microscopy, X-ray diffraction, and Fourier-transform infrared spectroscopy. The optimized 5 wt% WS2 composite showed enhanced gas-sensing performance, with 219.1% sensitivity to 100 ppm ammonia (2.4-fold higher than that of pure PANI) and reduced response and recovery times of 24 and 91 s, respectively (compared to 81 and 436 s for pure PANI, respectively). Notably, the PANI/WS2 sensor detected an ultralow ammonia concentration (100 ppb) with 0.104% sensitivity. The structural characterization and performance analysis results were used to deduce a mechanism for the enhanced sensing capability. These findings highlight the application potential of PANI/WS2 composites in flexible gas sensors and provide fundamental insights for PANI-based sensing materials research.

Conductive cotton fabric was prepared by coating single-wall carbon nanotubes (CNTs) on a knitted cotton fabric surface through a “dip-and-dry” method. The combination of CNTs and cotton fabric was analyzed using scanning electron microscopy (SEM) and Raman scattering spectroscopy. The CNTs coating improved the mechanical properties of the fabric and imparted conductivity to the fabric. The electromechanical performance of the CNT-cotton fabric (CCF) was evaluated. Strain sensors made from the CCF exhibited a large workable strain range (0~100%), fast response and great stability. Furthermore, CCF-based strain sensors was used to monitor the real-time human motions, such as standing, walking, running, squatting and bending of finger and elbow. The CCF also exhibited strong electric heating effect. The flexible strain sensors and electric heaters made from CCF have potential applications in wearable electronic devices and cold weather conditions.

The use of graphene and its derivatives with excellent characteristics such as good electrical and mechanical properties and large specific surface area has gained the attention of researchers. Recently, novel nanocomposite materials based on graphene and conducting polymers including polyaniline (PANi), polypyrrole (PPy), poly (3,4 ethyldioxythiophene) (PEDOT), polythiophene (PTh), and their derivatives have been widely used as active materials in gas sensing due to their unique electrical conductivity, redox property, and good operation at room temperature. Mixing these two materials exhibited better sensing performance compared to pure graphene and conductive polymers. This may be attributed to the large specific surface area of the nanocomposites, and also the synergistic effect between graphene and conducting polymers. A variety of graphene and conducting polymer nanocomposite preparation methods such as in situ polymerization, electropolymerization, solution mixing, self-assembly approach, etc. have been reported and utilization of these nanocomposites as sensing materials has been proven effective in improving the performance of gas sensors. Review of the recent research efforts and developments in the fabrication and application of graphene and conducting polymer nanocomposites for gas sensing is the aim of this review paper.

Recently, there has been a huge increase in the different ways to manufacture polymer-based sensors. Methods like additive manufacturing, microfluidic preparation, and brush painting are just a few examples of new approaches designed to improve sensor features like self-healing, higher sensitivity, reduced drift over time, and lower hysteresis. That being said, we believe there is still a lot of potential to boost the performance of current sensors by applying modeling, classification, and machine learning techniques. With this approach, final sensor users may benefit from inexpensive computational methods instead of dealing with the already mentioned manufacturing routes. In this study, a total of 96 specimens of two commercial brands of Force Sensing Resistors (FSRs) were characterized under the error metrics of drift and hysteresis; the characterization was performed at multiple input voltages in a tailored test bench. It was found that the output voltage at null force (Vo_null) of a given specimen is inversely correlated with its drift error, and, consequently, it is possible to predict the sensor’s performance by performing inexpensive electrical measurements on the sensor before deploying it to the final application. Hysteresis error was also studied in regard to Vo_null readings; nonetheless, a relationship between Vo_null and hysteresis was not found. However, a classification rule base on k-means clustering method was implemented; the clustering allowed us to distinguish in advance between sensors with high and low hysteresis by relying solely on Vo_null readings; the method was successfully implemented on Peratech SP200 sensors, but it could be applied to Interlink FSR402 sensors. With the aim of providing a comprehensive insight of the experimental data, the theoretical foundations of FSRs are also presented and correlated with the introduced modeling/classification techniques.

Flexible strain sensors have attracted much attention due to their wide applications in human health monitoring, motion detection, human–computer interaction, and smart robots in recent years. Cellulose-based materials include cellulose fibers, cellulose nanofibers, cellulose nanocrystals, and cellulose derivatives such as methylcellulose, carboxymethyl cellulose, and cellulose acetate. They exhibit excellent properties and diverse functions that play key roles in the preparation of flexible strain sensors. The conductive networks of the cellulose-based composite materials are established by mixing or coating conductive materials or directly carbonizing the cellulose materials. This paper was divided into five parts according to the macroscopic forms of sensors, including fibers and yarns, films, papers, fabrics and gels. The materials, preparation methods, and structures of the flexible strain sensors are detailly compared and discussed. The solutions to the difficulties met in the preparation process are proposed. The sensing performance of the flexible strain sensors based on cellulose composite and their applications in physiological signals and human motion detection are summarized. The potential applications and challenges during future development are analyzed. This review provides some suggestions and strategies for further development of flexible strain sensors based on cellulose composite for physiological signals and human motion detection.

In recent years, polymer-mediated signal amplification has drawn wide attention in bioelectronic sensing. With the rapid progress of biosensing and flexible electronics, polymers with excellent electron-ion transport properties, tunable molecular structures, and good biocompatibility have become essential materials for enhancing detection sensitivity and interfacial stability. However, current sensing systems still face challenges such as signal attenuation, surface fouling, and multi-component interference in complex biological environments, limiting their use in medical diagnosis and environmental monitoring. This review summarizes the progress of conductive polymers, molecularly imprinted polymers, hydrogels, and composite polymers in medical diagnosis, food safety, and environmental monitoring, focusing on their signal amplification mechanisms and structural optimization strategies in electronic transport regulation, molecular recognition enhancement, and antifouling interface design. Overall, polymers improve detection performance through interfacial electronic reconstruction and multidimensional synergistic amplification, offering new ideas for developing highly sensitive, stable, and intelligent biosensors. In the future, polymer-based amplification systems are expected to expand in multi-parameter integrated detection, long-term wearable monitoring, and in situ analysis of complex samples, providing new approaches to precision medicine and sustainable environmental health monitoring.

Embedded and real-time monitoring of pavement mechanical state changes based on the strain detected by self-sensing sensors of polymer/conductive composites is a new way for pavement health monitoring. Strain monitoring, using polymer-based composite mechanosensitive materials, requires the formation of effective conductive networks and conductive channels within the composite material so that the mechanosensitive material is electrically conductive at the macroscopic level. However, the deformation of the pavement structure is much smaller in magnitude, which is about hundreds or even tens of microstrains (10−6). Therefore, it is especially important to study the strain self-sensing mechanism of conductive composites at the με level. Micro- and nanostructured polymer composites have a complex structure with multiple layers, scales, and interactions, and thus present many difficulties when studying their microscopic conductive mechanisms. In this paper, the all-atom system of the micro-nanostructured composite mechanosensitive materials model was proposed with the help of molecular dynamics simulations. This achieved a breakthrough and realized the systematic study of the microscopic level of the relevant parameters of the composite’s conductivity from the molecular point of view to construct a relationship between the microscopic parameters, conductive network, and conductivity. The kinetic models of the micro-nanostructure and resin interface based on the molecular dynamics simulation technology were constructed to explore the dispersion state of the conductive filler, the interfacial interactions between the conductive filler and epoxy resin matrix, and the structural changes in the conductive network within the system under the tension state.

Conductive polymer composites (CPCs) combining with specific microstructures (micropores, microcracks, etc.) can exhibit unique resistance response changes, which can be widely regarded as an effective way to improve sensing performance. This study takes advantage of the characteristics of the formation of tiny pores between crystal grains during selective laser sintering (SLS) processing to introduce a microporous structure into the thermoplastic polyurethane (TPU)/carbon nanotube (CNT) sensing element to prepare a three-dimensional porous conductive structure. The effect of the SLS process on sensing sensitivity, accuracy, and density was studied, and its sensing and forming mechanism were discussed. By adjusting SLS process parameters to control the performance of porous structure sensor elements, a final TPU/CNT sensor element with a wide pressure detection range, high sensitivity, a fast response time, and good stability and durability was developed. Finally, the optimal performance of the developed flexible pressure sensor was successfully used to detect the pressure distribution of the human foot. This study provided a simple and effective research method to develop high-performance flexible pressure sensors.

Hybrid composites based on tin chloride and the conductive polymers, polyaniline (PAni) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), were integrated into high-performance hydrogen sulphide (H2S) gas sensors working at room temperature. The morphology and chemical properties were studied by scanning and transmission electron microscopy (SEM, TEM), energy dispersive spectroscopy (EDS) and Fourier-transform infrared (FTIR). The composites demonstrated a slightly porous nanostructure and strong interactions between the polymers and the metal salt, which slightly dopes PAni. The hybrid sensors exhibited a very low detection limit (<85 ppb), fast response, repeatability, reproducibility and stability over one month. Moreover, this work presents how calibration based on the derivative of the signal can give hybrid sensors the ability to quantify the concentration of targeted gas, even during continuous variation of the analyte concentration. Finally, the effect of interfering species, such as water and ammonia, is discussed.