The surge in electronic devices and wireless communication technologies has increased the demand for effective electromagnetic interference shielding and microwave-absorbing materials. Traditional electromagnetic interference (EMI) shielding materials, which predominantly utilize metals and polymer composites, pose significant environmental challenges due to their non-biodegradable nature. Recently, a range of novel electromagnetic shielding materials has been developed, with composite materials derived from waste sources emerging as promising alternatives for next-generation shielding solutions. This comprehensive review explores sustainable materials derived from various recycled waste sources for EMI shielding applications. It begins by examining the fundamental principles and mechanisms of EMI shielding and absorption techniques necessary for cost-effective performance. The review further investigates a variety of sustainable materials, including agricultural residues, industrial by-products, animal waste, and electronic waste, evaluating their potential for EMI shielding. Additionally, it explores the structural characteristics, electromagnetic properties, and synthesis methods of composite materials created from different raw material combinations. The review highlights the processing techniques and integration strategies used to develop effective shielding materials, as well as the potential applications of these materials and the challenges associated with their synthesis. The innovative use of solid waste materials from diverse origins in creating these shielding materials not only enhances their efficiency but also contributes to effective waste management and environmental sustainability.

The growing demand for sustainable and energy-efficient construction has driven significant interest in the development of advanced insulation materials that reduce energy usage while minimizing environmental impact. Although conventional insulation materials such as polyurethane, polystyrene, and mineral wools offer excellent thermal and acoustic performance, they are derived from non-renewable sources, have high embodied carbon (EC) (up to 7.3 kg CO₂-eq/kg), and pose end-of-life disposal challenges. Thus, this review critically examines the emergence of insulation materials derived from natural and recycled sources, which align with circular economy principles by minimizing waste, promoting material reuse, and extending product life cycles. Sustainable alternatives such as sheep wool, hemp, flax, and jute not only exhibit competitive thermal conductivity (as low as 0.031–0.046 W/m·K) and very good sound absorption but also offer low EC, biodegradability, and regional availability. Despite some limitations, including variable fire resistance and thickness requirements, these bio-based insulators present a viable path toward greener building solutions. The review highlights that waste-based insulation materials are essential for sustainable construction due to their low EC, renewability, and contribution to waste reduction, making them a necessary alternative even when conventional materials demonstrate superior short-term performance.

This work presents the design and analysis of a compact single-negative (SNG) metamaterial sensor based on a meandered-line configuration for high-resolution microwave sensing of liquids. The sensor, fabricated on a low-cost FR-4 substrate with a unit cell size of 10 × 10 × 1.575 mm³, operates at frequency of 5-11 GHz. The structure demonstrates strong resonance characteristics, including a reflection coefficient (S11) dip of –32 dB and a transmission coefficient (S21) level of -28 dB, indicating excellent impedance matching and field confinement. The sensing capability was validated using five essential bio oils (peppermint, citrus, eucalyptus, lavendar, and rosmary) with known relative permittivity values ranging from 2.5 to 3.25. The presence of each material under test (MUT) induced a consistent 200 MHz shift in resonance frequency, with a calculated normalized sensitivity of 6.94%. The sensor’s design was further optimized using random forest and extra trees predictive model and quantitatively assessed using mean squared error and R² score. The meandered structure and single-negative behavior contributed to a high quality factor (70.36, 64.33, 59.23, 54.86, 54.64) and enhanced dielectric interaction with an average relative error of less than 1.1%, confirming strong reproducibility. These results confirm the sensor’s utility for compact, non-invasive, and permittivity characterization in skin care and liquid sensing applications.

Modern control systems’ dependability, safety and efficiency have all been improved by studying fault-tolerant control systems (FTCS). FTCS techniques can typically be active or passive controls. The fault detection and diagnosis (FDD) method is used in this study’s active control branch to identify probable faults that could develop in the speed Hall sensors of brushless DC motors (BLDC). FDD methodologies can be categorised into two types, depending on the available data and the process involved: model-based methods and data-based methods. The proposed approach in this study explores the implementation of the Luenberger observer methodology as part of the model-based approach. The chosen methodology was practically implemented and subjected to experimental evaluation. The proposed observer relies on the residual signal, which displays the difference between the plant’s observed and estimated speed signals and serves as a failure alert for the entire system. Given the increasing demand for BLDC motors in various industrial control applications, including medical fields, automation and robotics, this particular motor was selected as a benchmark to thoroughly evaluate and validate the proposed method. The primary contribution of this paper lies in the real-time application of model-based sensor fault detection methods to BLDC motors. The efficiency of the suggested method is showcased through extensive MATLAB simulations, where the obtained results confirm the successful detection of faults with a high level of responsiveness. As a result, the project was successfully implemented in real-time, and the experimental results exhibited a close correlation with the simulated outcomes. This consistency between simulation and practical implementation validates the accuracy and reliability of the proposed methodology for detecting faults in the BLDC motor speed sensor. The results underscore the heightened reliability and safety attained by promptly and accurately detecting sensor faults during the operation of the motor.