Heuristics-assisted combinatorial screening of oxynitride phosphors

Nitride or oxynitride phosphors have been recently acting as key phosphors in the light emitting diode (LED) application. In particular, their superiority to the conventional oxide-based phosphors in terms of efficacy, thermal stability, color rendering, and etc. made it possible to achieve rapid commercialization of several nitride or oxynitride phosphors such as CaAISiN3, alpha- and beta-Sialons, Sr2Si5N8, and etc. However, it is still necessary to discover more nitride or oxynitride phosphors, which meet specific requirements for LED applications. In this regard, heuristics-based combinatorial material search (HCMS) strategies have been applied to multi-compositional inorganic systems to search for new phosphors and to optimize the properties of phosphors in the six dimensional SrCO3-BaCO3-CaCO3-SiO2-Si3N4-Eu2O3 search space. The heuristics strategies include non-dominated sorting genetic algorithm (NSGA) and particle swarm optimization (PSO).