Carbon dots have gained tremendous interest attributable to their unique features. Two approaches are involved in the fabrication of quantum dots (Top-down and Bottom-up). Most of the synthesis methods are usually multistep, required harsh conditions, and costly carbon sources that may have a toxic effect, therefore green synthesis is more preferable. Herein, the current review presents the green synthesis of carbon quantum dots (CQDs) and graphene quantum dots (GQDs) that having a wide range of potential applications in bio-sensing, cellular imaging, and drug delivery. However, some drawbacks and limitations are still unclear. Other biomedical and biotechnological applications are also highlighted.
Graphene quantum dots (GQD) is an efficient nanomaterial composed of one or more layers of graphene with unique properties that combine both graphene and carbon dots (CDs). It can be synthesized using carbon-rich materials as precursors, such as graphite, macromolecules polysaccharides, and fullerene. This contribution emphasizes the utilization of GQD-based materials in the fields of sensing, bioimaging, energy storage, and corrosion inhibitors. Inspired by these numerous applications, various synthetic approaches have been developed to design and fabricate GQD, particularly bottom-up and top-down processes. In this context, the prime goal of this review is to emphasize possible eco-friendly and sustainable methodologies that have been successfully employed in the fabrication of GQDs. Furthermore, the fundamental and experimental aspects associated with GQDs such as possible mechanisms, the impact of size, surface alteration, and doping with other elements, together with their technological and industrial applications have been envisaged. Till now, understanding simple photo luminance (PL) operations in GQDs is very critical as well as there are various methods derived from the optical properties of manufactured GQDs can differ. Lack of determining exact size and morphology is highly required without loss of their optical features. Finally, GQDs are promising candidates in the after-mentioned application fields.
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