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).
