High-efficiency synthesis of red carbon dots using machine learning
Jun Luo, Jiao Chen, Hui Liu, Cheng Zhi Huang, Jun Zhou
Abstract
Due to their excellent optical properties, red carbon dots (CDs) have been widely used in cell imaging and biomedical therapy. However, the efficiency of red CD synthesis is deficient, and the synthesis cost is high. Here, we propose an efficient synthesis method based on machine learning to assist researchers in synthesizing red fluorescent CDs. This strategy can quickly and efficiently predict the predesigned conditions of CD synthesis. It avoids invalid synthetic experiments and improves the efficiency of red CD synthesis.
Topics & Concepts
Carbon fibersNanotechnologyComputer scienceMaterials scienceChemistryAlgorithmComposite numberMachine Learning in Materials ScienceAdvanced Nanomaterials in CatalysisQuantum Dots Synthesis And Properties