Search

The demand for clean and sustainable alternative energy resources is linearly increasing day by day due to the prevailing electricity crisis. Small-scale energy harvesting is considered a sustainable way to generate clean energy. Advanced energy solar cells, mainly dye-sensitized solar cells use solar energy and convert it into electrical energy. Similarly, MEMS-based piezoelectric materials are used to convert mechanical energy into electrical energy. For these applications, zinc oxide is considered one of the most suitable materials with high conductive, tunable band gap, and piezoelectric properties. However, altering these properties can be carried out by the addition of metal and other materials. Various research work has been carried out to study the addition of conductive metal as a dopant to alter the properties of zinc oxide. In this study, Strontium has been doped in ZnO to form a nanostructure for application in DSSC and microelectromechanical systems (MEMS) energy harvesters. Analysis has been conducted using the simulation and fabrication method. The results show that the doping and the pore size of the substrate (Anodic Aluminum oxide membrane) largely affect the output voltage and current. The difference between the simulated and experimental results was less than 1%, which shows the accuracy of the simulation. Tuning of the band gap can be observed by the addition of Sr in the ZnO nanostructure. For microelectromechanical systems energy harvesters, Sr-doped ZnO nanostructures deposited on anodic aluminum oxide show 7.10 mV of voltage and 1.11 uA of current output. The addition of Sr doping in ZnO shows the improvement in the generated current and voltage for the energy harvester and the improvement in overall power conversion efficiency for dyesensitized solar cells. MEMS-based energy harvesting devices and low-cost advanced solar cells are promising to improve the efficiency of energy generation at a small scale. [ABSTRACT FROM AUTHOR]

The internet of medical things (IoMT) is used for the acquisition, processing, transmission, and storage of medical data of patients. The medical information of each patient can be monitored by hospitals, family members, or medical centers, providing real-time data on the health condition of patients. However, the IoMT requires monitoring healthcare devices with features such as being lightweight, having a long lifetime, wearability, flexibility, safe behavior, and a stable electrical performance. For the continuous monitoring of the medical signals of patients, these devices need energy sources with a long lifetime and stable response. For this challenge, conventional batteries have disadvantages due to their limited-service time, considerable weight, and toxic materials. A replacement alternative to conventional batteries can be achieved for piezoelectric and triboelectric nanogenerators. These nanogenerators can convert green energy from various environmental sources (e.g., biomechanical energy, wind, and mechanical vibrations) into electrical energy. Generally, these nanogenerators have simple transduction mechanisms, uncomplicated manufacturing processes, are lightweight, have a long lifetime, and provide high output electrical performance. Thus, the piezoelectric and triboelectric nanogenerators could power future medical devices that monitor and process vital signs of patients. Herein, we review the working principle, materials, fabrication processes, and signal processing components of piezoelectric and triboelectric nanogenerators with potential medical applications. In addition, we discuss the main components and output electrical performance of various nanogenerators applied to the medical sector. Finally, the challenges and perspectives of the design, materials and fabrication process, signal processing, and reliability of nanogenerators are included. [ABSTRACT FROM AUTHOR]

Fuzzy logic has been considered as a viable method for every field of study because of its large number of applications and advantages. In nano-materials, structural knowledge of material and parametric estimation can be studied using fuzzy logic. The main objective of this work is to perform fuzzy logic analyis for parametric estimation of Zinc oxide (ZnO) nano-rods based structures. The zinc oxide nano-rods when prepared with doped metal that results in change in properties of Zinc oxide nano-rods. These properties include structural, optical, mechanical and electrical properties of ZnO nano-rods. The enhancement in properties make the doped ZnO based material suitable for energy harvesting, bio-medical, energy and electronics application. Literature depicts the effect of 2nd group elements on ZnO nano-particles which directly shows the effect of change of parameters due to change in doping concentration. In this work, the analysis of effect on bandgap and rod diameter due to change in doping concentration and synthesis time is performed on ZnO nano-rods with doping 2nd group elements. The authors concluded that the synthesis time increase the rod diameter which directly decreases the bandgap. However, the doping concentration of 2nd group elements results in increase in band gap and decrease in rod diameter. However this effect is negligible for Mg and Be due to there small atomic size. The comparison between fuzzy logic simulation and mamdani model were also analysed which shows an error of less than 1% between the value. The 2nd group doped ZnO nano-rods can be used for various application due to adjustable band-gap and rod diameter with change in doping concentration. [ABSTRACT FROM AUTHOR]

Energy crisis is increasing day by day around the globe due to overconsumption, overpopulation, wastage of energy, poor infrastructure, and delay in commissioning of power plants, unexplored renewable energy resources and techniques. There is an urgent need to find out the new ways of energy production and utilization techniques. Here, authors present the new technique of energy harvesting with the movement of plant's branches and leaves. Simulation and design algorithm of energy harvesting system has been presented. Electricity can be produced due to air pressure on piezo nanogenerator that can be installed on branches and leaves of plants. The effect of variation in inputs on the range of outputs has been studied. Fuzzy Logic tool in MATLAB and Mamdani's model have been used for the simulation and calculation. Air velocity and angle have been considered as the two inputs and power has been considered as output of this energy harvesting system. Three membership functions for the inputs and output parameters have been allotted. The energy harvesting system works according to the specific defined rules. The variations of the inputs and the outputs have been displayed on the surface viewer graphs. The results obtained by fuzzy based simulation and Mamdani's model based calculations have only 0.27% error. This shows that the proposed energy harvesting system will perform well. [ABSTRACT FROM AUTHOR]

This paper presents the design and simulation of MEMS based energy harvester controller. Energy harvesting from physical motion such as finger motion, heart beating, walking and running are becoming so important now-a-days. In this study outputs voltage and current of the MEMS based energy harvester can be controlled by using fuzzy logic based control system. A new way of controlling the outputs by changing the inputs has been proposed in this study. The system has been developed in MATLAB using fuzzy logic Mamdani model.Two inputs pressure and area have been selected. The three membership functions to the input parameters have been assigned. The two outputs like voltage and current are selected for output power. Three membership functions are also assigned to the outputs. The system works according to the rules defined in the fuzzy inference system (FIS). The results according to suggested rules belonging to assigned MFs have been displayed in surface viewer.Different rules of combinations were defined in MATLAB rule editor and we used AND logic for simulation. The rsults obtained from fuzzy logic controller have been verified by using Mamdani's formula for specific values of the inputs and the outputs. As there is only 1% error for both the outputs, current and voltage, this shows that the system performs very well. [ABSTRACT FROM AUTHOR]