Simultaneous Optimization of Luminance and Color Chromaticity of Phosphors Using a Nondominated Sorting Genetic Algorithm

Acquiring materials that simultaneously meet two or more conflicting requirements is very difficult. For instance, a situation wherein the color chromaticity and photoluminescence (PL) intensity of phosphors conflict with one another is a frequent problem. Therefore, identification of a good phosphor that simultaneously exhibits both desirable PL intensity and color chromaticity is a challenge. A high-throughput synthesis and characterization strategy that was reinforced by a nondominated sorting genetic algorithm (NSGA)-based optimization process was employed to simultaneously optimize both the PL intensity and color chromaticity of a MgO–ZnO–SrO–CaO–BaO–Al2O3–Ga2O3–MnO system. NSGA operations, such as Pareto sorting and niche sharing, and the ensuing high-throughput synthesis and characterization resulted in identification of promising green phosphors, i.e., Mn2+-doped AB2O4 (A = alkali earth, B = Al and Ga) spinel solid solutions, for use in either plasma display panels or cold cathode fluorescent lamps.