In this work, the main objective is to enhance the gas sensing capability through investigating the effect of Al and Mg doping on ZnO based sensors. ZnO, Mg_1% doped ZnO, Al_5% doped ZnO and (Al_5%, Mg_1%) co-doped ZnO nanoparticles (NPs) were synthesized by a modified sol-gel method. The structural characterization showed the hexagonal crystalline structure of the prepared samples. Morphological characterizations confirmed the nanometric sizes of the NPs (27–57 nm) and elemental composition investigation proved the existence of Al and Mg with low concentrations. The optical characterization showed the high absorbance of the synthesized samples in the UV range. The gas sensing performances of the synthesized samples, prepared in the form of thick films, were investigated. Sensing tests demonstrated the high influence of the Al and Mg on the sensing performances towards H₂ and CO gas, respectively. The 5A1MZO-based sensor exhibits high sensitivity and low detection limits to H₂ (<2 ppm) and CO (<1 ppm). It showed a response around 70 (at 250 °C) towards 2000 ppm H₂ and 2 (at 250 °C) towards CO.

The Internet of Things (IoT) is a network of interconnected physical devices, vehicles, and buildings that are embedded with sensors, software, and network connectivity, enabling them to collect and exchange data. This exchange of data between the physical and digital worlds allows for a wide range of applications, from smart homes and cities to industrial automation and healthcare. However, a key challenge faced by IoT nodes is the limited availability of energy to support their operations. Typically, these nodes can only function for a few days based on their duty cycle. This paper introduces a solution that aims to ensure the sustainability of IoT applications by addressing this energy challenge. Thus, we develop a design of a hybrid sustainable energy system designed specifically for IoT nodes, using solar photovoltaic (PV) and wind turbines (WT) chosen for their multiple benefits and complementarity. The system uses the single-ended primary-inductance converter (SEPIC) and is controlled using a hybrid approach, combining Harris Hawks Optimization and Particle Swarm Optimization (HHHOPSO). Each SEPIC converter boost the electrical energy generated to attain the required voltage level when charging the battery. The proposed methodology is implemented in MATLAB/Simulink and its performance is measured using appropriate metrics. In terms of efficiency and average power, the results show that the suggested method outperforms previous strategies. Our system powers also many sensor nodes, leading to a high level of sustainability and lowering the carbon footprint associated with traditional energy sources.

In this paper is reported a simple and low cost conductometric sensor based on a ternary Al-Mg-ZnO thick film for the detection of carbon oxides (CO and CO2). The optimized ternary Al-Mg-ZnO sensing material, containing 5at(%) of Al and 1at(%) of Mg (sample code 5Al1MgZnO) was synthesized by a simple sol-gel method and extensively characterized by transmission electron microscopy (TEM), x-ray diffraction (XRD), UV-Vis-Nir diffuse reflectance spectroscopy (UV-Vis-Nir-DRS) and photoluminescence (PL). The developed Al-Mg-ZnO sensor showed good characteristics in terms of good sensitivity and lower limit of detection, short response and recovery time values for detecting simultaneously CO and CO2, which could be of practical application in the biomedical field.