Searching for the Optimized Luminescent Lanthanide Phosphor Using Heuristic Algorithms

In this research, four heuristic algorithms (HAs), including simulated annealing (SA), improved annealing with a harmony search algorithm (HSA), particle swarm optimization (PSO), and genetic algorithm (GA), were used to optimize the luminescent intensity of phosphor. Among the four HAs, the improved algorithm HSA got better phosphors than SA (without using the known coded concentration). The PSO algorithm got gradually better results with increased generation, and the GA could find the best local phosphors with shorter time. After further analysis of the 340 phosphors, we found that the final brightness has an optimized activator concentration (Tb: 0.21-0.26), and the results were further proved by another uniform host of NaGdF4:Ce,Tb nanoparticles. The HA was proper to find the optimal concentration of the activator of Tb. Furthermore, the optimal phosphor could be used as a bioimaging agent and improved QR code.