材料科学
石墨烯
量子点
量子产额
光致发光
荧光
量子
产量(工程)
纳米技术
化学物理
光电子学
量子力学
物理
复合材料
作者
Liangfeng Chen,Siwei Yang,Yongqiang Li,Zheng Liu,Hang Wang,Yuqing Zhang,Kai Qi,Gang Wang,Peng He,Guqiao Ding
标识
DOI:10.1002/adfm.202401246
摘要
Abstract Although various effective machine‐learning attempts have been made to investigate the photoluminescence properties of graphene quantum dots (GQDs) or carbon dots, the physical correlation behind their mathematical models has not been reasonably elucidated. In this work, the correlation mechanism between the precursor structure and quantum yield of GQDs prepared by a “bottom‐up” method is sufficiently studied. Three decisive factors affecting the quantum yield of GQDs during the two‐component reaction system preparation are revealed, namely structure factor (F1), temperature factor (F2), and concentration factor (F3). The symmetry of precursors in the formation of sp 2 – sp 3 hybrid carbon nanostructures is considered the key factor in the modulation of fluorescence quantum yield in GQDs. Notably, in contrast to previous work, it is first demonstrated that the normal modes of molecular vibration are the core mechanism by which the structural properties of the precursors act on the fluorescence quantum yield of GQDs. The conclusion further proved conducive in obtaining GQDs with a higher absolute quantum yield up to 83.33%.
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