Studying the phosphorescent mechanisms of carbon nanostructures synthesized by the "bottom-up" approach is key to understanding the structure modulation and the interfacial properties of carbon nanostructures. In this work, the relationships among symmetry of precursors in the "bottom-up" synthesis, structures of products, and phosphorescence lifetimes of graphene quantum dots (GQDs) are studied. The symmetry matching of precursors in the formation of a D graphene-like framework is considered the key factor in controlling the separability of sp domains in GQDs. As the separability of sp domains in GQDs increases, the phosphorescence lifetimes (14.8-125.5 ms) of GQDs in the solid state can be tuned. Machine learning is used to define the degree of disorder (S) of the GQD structure, which quantitatively describes the different space groups of precursors. The negative correlation between S and the oscillator strength of GQDs is uncovered. Therefore, S can be recognized as reflective of oscillator strength in the GQD structure. Finally, based on the correlations found between the structures and phosphorescence lifetimes of GQDs, GQDs with an ultralong phosphorescence lifetime (28.5 s) are obtained. Moreover, GQDs with visible phosphorescence emission (435-618 nm) are synthesized.

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http://dx.doi.org/10.1002/adma.202313639DOI Listing

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