Supercapacitors (SCs) have received a great deal of attention and play an important role for future self-powered devices, mainly owing to their higher power density. Among all types of electrical energy storage devices, electrochemical supercapacitors are considered to be the most promising because of their superior performance characteristics, including short charging time, high power density, safety, easy fabrication procedures, and long operational life. An SC consists of two foremost components, namely electrode materials, and electrolyte. The selection of appropriate electrode materials with rational nanostructured designs has resulted in improved electrochemical properties for high performance and has reduced the cost of SCs. In this review, we mainly spotlight the non-metallic oxide, especially metal chalcogenides (MX; X = S, Se) based nanostructured electrode materials for electrochemical SCs. Different non-metallic oxide materials are highlighted in various categories, such as transition metal sulfides and selenides materials. Finally, the designing strategy and future improvements on metal chalcogenide materials for the application of electrochemical SCs are also discussed.

Cloud computing offers the services to access, manipulate and configure data online over the web. The cloud term refers to an internet network which is remotely available and accessible at anytime from anywhere. Cloud computing is undoubtedly an innovation as the investment in the real and physical infrastructure is much greater than the cloud technology investment. The present work addresses the issue of power consumption done by cloud infrastructure. As there is a need for algorithms and techniques that can reduce energy consumption and schedule resource for the effectiveness of servers. Load balancing is also a significant part of cloud technology that enables the balanced distribution of load among multiple servers to fulfill users’ growing demand. The present work used various optimization algorithms such as particle swarm optimization (PSO), cat swarm optimization (CSO), BAT, cuckoo search algorithm (CSA) optimization algorithm and the whale optimization algorithm (WOA) for balancing the load, energy efficiency, and better resource scheduling to make an efficient cloud environment. In the case of seven servers and eight server’s settings, the results revealed that whale optimization algorithm outperformed other algorithms in terms of response time, energy consumption, execution time and throughput.

Over the last few decades, the development of the electronic nose (E-nose) for detection and quantification of dangerous and odorless gases, such as methane (CH₄) and carbon monoxide (CO), using an array of SnO₂ gas sensors has attracted considerable attention. This paper addresses sensor cross sensitivity by developing a classifier and estimator using an artificial neural network (ANN) and least squares regression (LSR), respectively. Initially, the ANN was implemented using a feedforward pattern recognition algorithm to learn the collective behavior of an array as the signature of a particular gas. In the second phase, the classified gas was quantified by minimizing the mean square error using LSR. The combined approach produced 98.7% recognition probability, with 95.5 and 94.4% estimated gas concentration accuracies for CH₄ and CO, respectively. The classifier and estimator parameters were deployed in a remote microcontroller for the actualization of a wireless E-nose system.

We present a simplistic, ultrafast, and facile hydrothermal deposition of ternary Cu₂SnS₃ nanoparticles (CTS NPs). The fabricated CTS NPs show superior antimicrobial and photocatalytic activities. In the presence of UV-Visible illumination, methylene blue (MB) dye was studied for photocatalytic dye degradation activity of CTS NPs. Excellent efficiency is shown by incorporating CTS NPs to degrade MB dye. There is a ~95% decrease in the absorbance peak of the dye solution within 120 min. Similarly, CTS NPs tested against three bacterial strains, i.e., B. subtilis, S. aureus, P. vulgaris, and one fungal strain C. albicans, defining the lowest inhibitory concentration and zone of inhibition, revealed greater antimicrobial activity. Hence, it is concluded that the CTS NPs are photocatalytically and antimicrobially active and have potential in biomedicine.