Inverse Design of Nanoclusters for Light-Controlled CO2-HCOOH Interconversion

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.