Graphene, an innovative nanocarbon, has been discovered as a significant technological material. Increasing utilization of graphene has moved research towards the development of sustainable green techniques to synthesize graphene and related nanomaterials. This review article is basically designed to highlight the significant sustainability aspects of graphene. Consequently, the sustainability vision is presented for graphene and graphene nanocomposites. Environmentally sustainable production of graphene and ensuing nanomaterials has been studied. The formation of graphene, graphene oxide, reduced graphene oxide, and other derivatives has been synthesized using ecological carbon and green sources, green solvents, non-toxic reagents, and green routes. Furthermore, the utilization of graphene for the conversion of industrial polymers to sustainable recycled polymers has been studied. In addition, the recycled polymers have also been used to form graphene as a sustainable method. The implication of graphene in the sustainable energy systems has been investigated. Specifically, high specific capacitance and capacitance retention were observed for graphene-based supercapacitor systems. Subsequently, graphene may act as a multi-functional, high performance, green nanomaterial with low weight, low price, and environmental friendliness for sustainable engineering and green energy storage applications. However, existing challenges regarding advanced material design, processing, recyclability, and commercial scale production need to be overcome to unveil the true sustainability aspects of graphene in the environmental and energy sectors.
In recent years, the pathological diagnosis of glomerular diseases typically involves the study of glomerular his-to pathology by specialized pathologists, who analyze tissue sections stained with Periodic Acid-Schiff (PAS) to assess tissue and cellular abnormalities. In recent years, the rapid development of generative adversarial networks composed of generators and discriminators has led to further developments in image colorization tasks. In this paper, we present a generative adversarial network by Spectral Normalization colorization designed for color restoration of grayscale images depicting glomerular cell tissue elements. The network consists of two structures: the generator and the discriminator. The generator incorporates a U-shaped decoder and encoder network to extract feature information from input images, extract features from Lab color space images, and predict color distribution. The discriminator network is responsible for optimizing the generated colorized images by comparing them with real stained images. On the Human Biomolecular Atlas Program (HubMAP)—Hacking the Kidney FTU segmentation challenge dataset, we achieved a peak signal-to-noise ratio of 29.802 dB, along with high structural similarity results as other colorization methods. This colorization method offers an approach to add color to grayscale images of glomerular cell tissue units. It facilitates the observation of physiological information in pathological images by doctors and patients, enabling better pathological-assisted diagnosis of certain kidney diseases.
In engineering, a design is best described based on its alternative performance operation. In this paper, an electric power plant is analysed based on its effective operational performance even during critical situation or crisis. Data is generated and analysed using both quantitative and qualitative research approach. During maintenance operation of an electric power plant, some components are susceptible to wide range of issues or crises. These includes natural disasters, supply chain disruptions, cyberattacks, and economic downturns. These crises significantly impact power plant operations and its maintenance strategies. Also, the reliable operation of power plants is often challenged by various technical, operational, and environmental issues. In this research, an investigation is conducted on the problems associated with electric power plants by proposing a comprehensive and novel framework to maintenance the power plant during crises. Based on the achieved results discussed, the framework impact and contribution are the integration of proactive maintenance planning, resilient maintenance strategies, advanced technologies, and adaptive measures to ensure the reliability and resilience of electric power plant during power generation operations in the face of unforeseen challenges/crisis. Hypothetical inferences are used ranging from mechanical failures to environmental constraints. The research also presents a structured approach to ensure continuous operation and effective maintenance in the electric power plant, particularly during crisis (such as environmental issues and COVID-19 pandemic issues).
Nanoparticle V2O5 is prepared by the measurement of X-ray diffraction (XRD) and atomic force microscopy (AFM) analyses. The crystallite size = 19.59 nm, optical energy gap = 2.6 eV, an average particle size of 29.58 nm and, RMS roughness of ~6.8 nm. Also, Fourier transformer infrared spectrophotometer (FTIR) showed a porous free morphology with homogeneity and uniformity on the sample surface. The film surface exhibited no apparent cracking and, the grains exhibited large nicely separated conical columnar growth combined grains throughout the surface with coalescence of some columnar grains at a few places. The fabrication of a thin film of V2O5 NPs/PSi heterojunction photodetector was characterized and investigated.
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