Dielectric investigations of pristine and modified ZnO nanoparticles for energy storage devices

Pristine ZnO, Al-doped ZnO, and TiO₂ coated ZnO nanoparticles (NPs) were synthesized by the wet chemical precipitation technique. All the synthesized NPs were characterized using X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy. XRD analysis of pristine ZnO and Al-doped ZnO NPs revealed the hexagonal wurtzite structure with P6₃mc space group with no secondary phases and impurities. FESEM micrographs also depicted hexagonal grains with well-defined grain boundaries. TEM images showed hexagonal polyhedral shape for pure ZnO NPs and spherical shape dominating polyhedral particle for Al-doped ZnO NPs, and pseudospherical particles for TiO₂ coated ZnO NPs. Energy-dispersive X-ray spectroscopy of Al-doped ZnO indicates the eminent exchange of dopant in the lattice site of Zn. Dielectric Studies reveal the highest value of the dielectric constant and lowest value of dielectric loss for Al-doped ZnO as compared to pure and TiO₂-coated ZnO NPs. Suggesting Al-doped ZnO to be used as a dielectric material that can serve as a basic building block of the energy storage devices such as dielectric capacitor. TiO₂-coated ZnO NPs demonstrated higher AC conductivity in comparison to pure ZnO and Al-doped ZnO NPs suggesting their use as a conductive nanofiller materials in a polymer-based nanocomposite to achieve higher energy density.

     

A Review on Precision Agriculture Using Wireless Sensor Networks Incorporating Energy Forecast Techniques

Wireless Personal Communications - Wireless sensor networks (WSNs) are prominently used for environment monitoring, however, energy constraints limit their applications. So, the energy consumption...     

Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

Increasing the coverage and capacity of cellular networks by deploying additional base stations is one of the fundamental objectives of fifth-generation (5G) networks. However, it leads to performance degradation and huge spectral consumption due to the massive densification of connected devices and simultaneous access demand. To meet these access conditions and improve Quality of Service, resource allocation (RA) should be carefully optimized. Traditionally, RA problems are nonconvex optimizations, which are performed using heuristic methods, such as genetic algorithm, particle swarm optimization, and simulated annealing. However, the application of these approaches remains computationally expensive and unattractive for dense cellular networks. Therefore, artificial intelligence algorithms are used to improve traditional RA mechanisms. Deep learning is a promising tool for addressing resource management problems in wireless communication. In this study, we investigate a double deep Q-network-based RA framework that maximizes energy efficiency (EE) and total network throughput in unmanned aerial vehicle (UAV)-assisted terrestrial networks. Specifically, the system is studied under the constraints of interference. However, the optimization problem is formulated as a mixed integer nonlinear program. Within this framework, we evaluated the effect of height and the number of UAVs on EE and throughput. Then, in accordance with the experimental results, we compare the proposed algorithm with several artificial intelligence methods. Simulation results indicate that the proposed approach can increase EE with a considerable throughput.     

Analysis and synthesis of speech using least <Emphasis Type="Italic">P</Emphasis>th norm filter design

In this paper we analyze the combination of speech and FIR filter design aspect to achieve good results in speech quality. A new approach in the time domain based on the least Pth norm is presented to extract maximum information that represents speech. The aim of this paper is to improve the perceived quality of speech through the introduction of least Pth norm algorithm that attenuates speech contaminated with noise. This approach relates to a filter bank structure and a method for filtering and separating an information signal into different bands, particularly for filtering and separation of speech signals. Then the desired signal is reconstructed from the independent components representing every band. This approach differs from the traditional approaches since no priori knowledge of the noise statistics is required, instead the noise signals are only assumed to have finite energy. Since the estimation criterion for the filter design is to minimize the worst possible amplification of the estimation error signal in terms of modeling errors and additive noise, this approach is highly robust and appropriate in practical speech analysis and synthesis. This paper presents a least Pth approach to the optimal design of FIR digital filter banks in the minimax sense for speech analysis and synthesis. The signal to noise ratio (SNR) of around 50–60 dB is achieved with various speech samples.     

Fruit Extract Mediated Green Synthesis of Metallic Nanoparticles: A New Avenue in Pomology Applications

Fruit extracts have natural bioactive molecules that are known to possess significant therapeutic potential. Traditionally, metallic nanoparticles were synthesized via chemical methods, in which the chemical act as the reducing agent. Later, these traditional metallic nanoparticles emerged as the biological risk, which prompted researchers to explore an eco-friendly approach. There are different eco-friendly methods employed for synthesizing these metallic nanoparticles via the usage of microbes and plants, primarily via fruit extract. These explorations have paved the way for using fruit extracts for developing nanoparticles, as they eliminate the usage of reducing and stabilizing agents. Metallic nanoparticles have gained significant attention, and are used for diverse biological applications. The present review discusses the potential activities of phytochemicals, and it intends to summarize the different metallic nanoparticles synthesized using fruit extracts and their associated pharmacological activities like anti-cancerous, antimicrobial, antioxidant and catalytic efficiency.     

Conifer-Derived Metallic Nanoparticles: Green Synthesis and Biological Applications

The use of metallic nanoparticles in engineering and biomedicine disciplines has gained considerable attention. Scientists are exploring new synthesis protocols of these substances considering their small size and lucrative antimicrobial potential. Among the most economical techniques of synthesis of metallic nanoparticles via chemical routes, which includes the use of chemicals as metal reducing agents, is considered to generate nanoparticles possessing toxicity and biological risk. This limitation of chemically synthesized nanoparticles has engendered the exploration for the ecofriendly synthesis process. Biological or green synthesis approaches have emerged as an effective solution to address the limitations of conventionally synthesized nanoparticles. Nanoparticles synthesized via biological entities obtained from plant extracts exhibit superior effect in comparison to chemical methods. Recently, conifer extracts have been found to be effective in synthesizing metallic nanoparticles through a highly regulated process. The current review highlights the importance of conifers and its extracts in synthesis of metallic nanoparticles. It also discusses the different applications of the conifer extract mediated metallic nanoparticles.     

Aegle marmelos (L.) Correa: An Underutilized Fruit with High Nutraceutical Values: A Review

Aegle marmelos (L.) Correa (Bael) fruit, a member of the Rutaceae family, is a major cultivated fruit plant in tropical and subtropical regions in countries of southeast Asia. Bael fruit has been a major topic for studies in recent years mainly due to its high nutritional (carbohydrates, proteins, minerals, and vitamins) value and presence of various phytochemicals, which attributed to its high medicinal value. These phytochemicals include various compounds, e.g., alkaloids, flavonoids, and phenolic acids (protocatechuic acid, gallic, and ellagic acid). The fruit extract of bael has been also an important study area for its pharmacological activities, including antidiarrheal, antioxidant, antidiabetic, hepatoprotective, radioprotective, anticancer, antiulcer properties. The current review mainly highlighted the nutritional and pharmacological activities of bael fruit. The nutritional profile and phytochemical profile were discussed in the review, along with their concentration in the fruit. Moreover, the experiments carried out in vivo and in vitro of bael fruit extracts with respect to their pharmacological activities were also discussed in the article. The recent literature based on nutritional and pharmacological values of bael fruit showed its high potential as a food and pharmaceutical product. Despite having high nutritional and pharmacological value, research related to molecular mechanisms of bael fruit is still limited, and clinical trials are needed to ensure its safety as a product in the food and pharma industries.