Rational Design of Full-Color Fluorescent C₃N Quantum Dots

Carbon-based quantum dots (QDs) exhibit unique photoluminescence due to size-dependent quantum confinement, giving rise to fascinating full-color emission properties. Accurate emission calculations using time-dependent density functional theory are a time-costing and expensive process. Herein, we employed an artificial neural network (ANN) combined with statistical learning to establish the relationship between geometrical/electronic structures of ground states and emission wavelength for C₃N QDs. The emission energy of these QDs can be doubly modulated by size and edge effects, which are governed by the number of C₄N₂ rings and the CH group, respectively. Moreover, these two structural characteristics also determine the phonon vibration mode of C₃N QDs to harmonize the emission intensity and lifetime of hot electrons in the electron-hole recombination process, as indicated by nonadiabatic molecular dynamics simulation. These computational results provide a general approach to atomically precise design the full-color fluorescent carbon-based QDs with targeted functions and high performance.