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Simultaneous Optimization of Luminance and Color Chromaticity of Phosphors Using a Nondominated Sorting Genetic Algorithm
Author(s) -
Sharma Asish Kumar,
Son Kyung Hyun,
Han Bo Yong,
Sohn KeeSun
Publication year - 2010
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.200902285
Subject(s) - chromaticity , phosphor , sorting , materials science , photoluminescence , genetic algorithm , plasma display , throughput , computer science , luminance , identification (biology) , optoelectronics , optics , biological system , algorithm , artificial intelligence , physics , telecommunications , wireless , electrode , quantum mechanics , machine learning , biology , botany
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–Al 2 O 3 –Ga 2 O 3 –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., Mn 2+ ‐doped AB 2 O 4 (A = alkali earth, B = Al and Ga) spinel solid solutions, for use in either plasma display panels or cold cathode fluorescent lamps.