The main drawback of energy harvesting using the piezoelectric direct effect is that the maximum electric power is generated at the fundamental resonance frequency. This can clearly be observed in the size and dimensions of the components of any particular energy harvester. In this paper, we are investigating a new proposed energy harvesting device that employs the Automatic Resonance Tuning (ART) technique to enhance the energy harvesting mechanism. The proposed harvester is composed of a cantilever beam and sliding masse with varying locations. ART automatically adjusts the energy harvester’s natural frequency according to the ambient vibration natural frequency. The ART energy harvester modifies the natural frequency of the harvester using the motion of the mobile (sliding) mass. An analytical model of the proposed model is presented. The investigation is conducted using the Finite Element Method (FEM). THE FEM COMSOL model is successfully validated using previously published experimental results. The results of the FEM were compared with the experimental and analytical results. The validated model is then used to demonstrate the displacement profile, the output voltage response, and the natural frequency for the harvester at different mass positions. The bandwidth of the ART harvester (17 Hz) is found to be 1130% larger compared to the fixed resonance energy harvester. It is observed that the proposed broadband design provides a high-power density of 0.05 mW mm⁻³. The piezoelectric dimensions and load resistance are also optimized to maximize the output voltage output power.

Earthquake-induced structural vibration is converted into an instant voltage signal via piezoelectric material for sensing purposes where it can be detected and read by a self-powered/self-sensing capabilities sensor located in remote and inaccessible areas. The motivating sensor is expected to wirelessly transmit vital information for monitoring purposes. A typical earthquake’s acceleration frequency components range as low from 1Hz to 17 Hz. Therefore, the motivating sensor is designed to resonate at its fundamental mode shapes to generate a readable voltage signal and power enough to meet the minimum power consumption needs of a typical acceleration sensor. The proposed sensor consists of a stack of 17 individual uniform simply supported composite-piezoelectric beams with a proof mass in the mid-span of each beam. The proof mass is utilized to enhance the voltage signal and to lower the device natural frequencies. Genetic Algorithm (GA) based optimization method is employed to optimize the 1 ^st natural frequency of the nth beam of the proposed sensing device to match it with one of a typical earthquake ground excitation frequencies at an increment of 1Hz. The fundamental mode is the most sensitive mode to the proof mass. Furthermore, the difference between the higher natural frequencies decreases when increasing the size of the proof mass. The analytical and the decoupled electro-mechanical equations are presented by employing the assumptions of Euler–Bernoulli’s thin beam hypothesis. The analytical results are then numerically verified by FEM by employing COMSOL multi-physics software to model and numerically simulate the proposed device/sensor.

In this paper, rainfall droplet impact force is transformed into a measurable voltage signal output via the piezoelectric material direct effect utilized for sensing purposes. The motivating sensor is utilized to measure the peak impact forces of rainfall droplets for further analysis and processing. Constructing a sense for the impact force of rainfall droplets has great implications in many real-life applications that can provide vital information regarding the amplifications of the impact force of rainfall on soil erosion, and the impact on small creatures and plants, etc. The rainfall droplet is set to collide on a very thin aluminum plate with negligible mass that can be presented geometrically as an extended segment of the proposed sensing device. The proposed sensing device is composed of a bimorph simply supported composite-piezoelectric beam that buckles due to the effect of the rain droplets’ vertical impact force. The proposed device is designed for optimal performance in terms of the amount of voltage that can be measured. This is accomplished by having the first critical buckling load of the device as less than the impact force of the rainfall droplet. Accordingly, the well-known genetic algorithm (GA) automated optimization technique is utilized in this paper to enhance the measured voltage signal. A proof mass is added to the middle of the beam to amplify the magnitude of the measured voltage signal. The voltage signal is intended to be transferred to the PC via a data acquisition system. The rainfall droplets’ peak impact forces are obtained analytically due to the nonlinear behavior of the beam using the Euler–Bernoulli thin beams assumptions. The FE model using COMSOL 6.0 Multiphysics commercial software is used to verify the analytical results.

Icing poses significant operational and safety risks in aviation, especially for engine components such as cowls and baffles. This study explores the potential of a chemically exfoliated graphene-rich carbon platelet epoxy coating to improve the anti-icing and de-icing performance of 3003-H14 aluminum alloy, which is widely used in such applications. Chemically exfoliated graphite was incorporated into an epoxy resin, then applied to aluminum substrates. Characterization of the coated samples revealed ~30% improvement in surface Vickers hardness (HV) (HV 75.6 ± 1.15 vs. HV average of 98.3 ± 1.5) and enhanced thermal dissipation, with coated surfaces cooling from 104 °C to 22 °C in 530 s compared to 870 s for uncoated samples. While anti-icing performance was not directly evaluated, the observed improvements in thermal dissipation and surface hardness suggest that chemically exfoliated graphene-rich carbon platelet coatings could be promising for passive anti-icing applications. The literature suggests that graphene coating improves hydrophobicity, reducing ice adhesion and delaying nucleation due to its low surface energy and nanoscale roughness, thereby supporting potential passive anti-icing functionality for aircraft engine components. SEM analysis confirmed a uniform, compact coating layer. These preliminary findings indicate that chemically exfoliated graphene-rich carbon platelet coatings can deliver multifunctional performance—mechanical, thermal, and surface—making them promising candidates for passive anti-icing/de-icing solutions in engine components where conventional systems are ineffective.

Electric aviation and unmanned aerial vehicles (UAVs) depend on lightweight composites to preserve payload and range, yet mass reduction, recycled content, or bio-based content alone does not establish component suitability. Candidate systems must also satisfy coupled structural, thermal, fire, electrical, manufacturing, durability, repair, and circularity requirements. This structured critical narrative review evaluates thermoplastic carbon-fibre-reinforced polymer (CFRP) systems, recycled-carbon-fibre composites, natural-fibre systems, bio-based and recyclable matrices, hybrid architectures, and multifunctional composites using a component-specific framework based on source role, evidence maturity, test comparability, and failure consequence. The framework links processing and chemistry to defects, retained performance, repair and recovery, and the evidence required for defined aircraft and UAV components. Thermoplastic CFRP provides the strongest near-term pathway for secondary and semi-structural components, although weld durability, impact tolerance, fire response, and process conformity remain system specific. Recycled-carbon-fibre and natural-fibre systems are most defensible for lower-consequence covers, fairings, housings, interiors, and UAV parts when feedstock variability, moisture, porosity, and fire performance are controlled. Battery enclosures, primary structures, rotor-support members, and structural-battery systems require representative coupled-hazard and component-scale evidence. The resulting adoption pathways are bounded by component and operating conditions, with manufacturing, durability, repair, recovery, and qualification evidence specified for each application.

Lightweight unmanned aerial vehicle (UAV) panels require electromagnetic interference (EMI) shielding with limited added mass and manageable manufacturing demands. This study compares seven experimentally reported thermoset carbon-fiber-reinforced polymer (CFRP) shielding configurations on a common X-band basis. The decision matrix combines paired mean shielding gain relative to each study’s matched pristine laminate, dry functional-modifier areal mass, and manufacturing and integration burden. TOPSIS and VIKOR were applied using reference weights of 0.40, 0.40, and 0.20. The polyaniline (PANI)-coated carbon-fabric CFRP containing 1 wt.% reduced graphene oxide/Fe₃O₄ hybrid (C4) ranked first by both methods, providing a 35.90 dB shielding gain at 13.26 g m⁻² dry modifier mass. PANI-decorated ACF-7/CFRP (C3) ranked second under TOPSIS, while the two-veil MXene/PEDOT:PSS/APP-modified reclaimed-carbon-fiber CFRP (C6) ranked second under VIKOR. C4 ranked first in 18 of the 19 TOPSIS weight-sensitivity cases and in all 19 VIKOR cases. Across the 243 bounded-input cases, both methods also kept C4 at first place. Under the stated UAV panel priorities, C4 is the preferred balanced configuration, while C3 is the low-mass alternative and C6 the shielding-prioritized alternative. The framework provides a traceable screening route while retaining source-specific mechanical evidence outside the weighted score.