Water is a necessity for all living and non-living organisms on this planet. It is understood that clean water sources are decreasing by the day, and the rapid rise of Industries and technology has led to an increase in the release of toxic effluents that are discharged into the environment. Wastewater released from Industries, agricultural waste, and municipalities must be treated before releasing into the environment as they contain harmful pollutants such as organic dyes, pharmaceuticals wastes, inorganic materials, and heavy metal ions. If not controlled, they can cause serious risks to human beings' health and contaminate our environment. Membrane filtration is a proven method for the filtration of various harmful chemicals and microbes from water. Carbon nanomaterials are applied in wastewater treatment due to their high surface area, making them efficient adsorbents. Carbon nanomaterials are being developed and utilized in membrane filtration for the treated wastewater before getting discharged with the rise of nanotechnology. This review studies carbon nanomaterials like fullerenes, graphenes, and CNTs incorporated in the membrane filtration to treat wastewater contaminants. We focus on these CNM based membranes and membrane technology, their properties and applications, and how they can enhance the commonly used membrane filtration performance by considering adsorption rate, selectivity, permeability, antimicrobial disinfectant properties, and compatibility with the environment.

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Chitosan has become the most known and second abundantly available recyclable, non-hazardous and eco-friendly biopolymer after cellulose with several advantageous biomedical, agriculture, and wastewater treatment applications. As nanotechnology has progressed, researchers have begun incorporating chitosan-based carbon compounds into various compounds, elements, and carbonaceous materials to increase their efficiency and biocompatibility. Chitosan carbon compounds have also been used directly in many applications due to their inherent chelating and antibacterial features and the presence of customizable functional groups. In this review, synthesis technologies and microstructure of chitosan composites and its carbon materials in biomedical, agriculture, and wastewater treatment concerning the administration of abiotic stress within plants, water accessibility for crops, scheming food bear pathogens, photothermal cancer rehabilitation, and heavy water pollutants absorption and removal methods are widely deliberated upon, with a relevant discussion of the techniques that can be used to put these into action. Chitosan is also utilized in miscellaneous applications, including the food sector and cosmetics. Overall, chitosan-based carbon compounds promise to extend agricultural practices while also addressing health concerns in an environmentally friendly manner.

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Tomorrow is a technology for Microbial fuel cells (MFC). It has attracted numerous studies for the continuous development of cell efficiency since the problem of the coming era can be resolved. Implementing artificial learning and machine learning is a change that can effectively achieve the goals. A microbial fuel cell constitutes a complex non-linear procedure that preferably needs a strategy that is not a linear control strategy for the most optimum result. Rather than making a computationally tedious and heavy non-linear control strategy, a superior single linear model or gain scheduling, or multiple models-based control techniques are the practical and feasible ways to tackle the non-linearity existing in the Microbial Fuel Cell. Machine learning and Artificial Intelligence help reduce computation and model costs. It saves time and is more efficient than previously used manual methods, which are now obsolete. In order to find the most accurate results, the study would compare all currently available research efforts and focus on implementing Artificial Intelligence and Machine learning concepts within the Microbial Fuel Cell and comparison with other fuel cells.