用于三色白光发光二极管的新型绿色荧光粉的遗传算法辅助组合搜索

Genetic algorithm-assisted combinatorial search for a new green phosphor for use in tricolor white LEDs.

作者信息

Sohn Kee-Sun, Park Duk Hyun, Cho Sang Ho, Kim Byung Il, Woo Seong Ihl

机构信息

Department of Materials Science and Metallurgical Engineering, Sunchon National University, Chonam 540-742, Korea.

出版信息

J Comb Chem. 2006 Jan-Feb;8(1):44-9. doi: 10.1021/cc050101z.

DOI:10.1021/cc050101z

PMID:16398552

Abstract

An evolutionary optimization process involving a genetic algorithm and combinatorial chemistry was employed for the development of green phosphors which are suitable for tricolor white-light-emitting diodes. To accomplish a high luminescent efficiency at 400 nm excitation, we screened a seven-cation oxide system including Tb, Gd, Ce, Mg, Si, Al, and B. The combination of a genetic algorithm and combinatorial chemistry enhanced the searching efficiency when applied for phosphor screening. As a result, the optimized composition was Tb(0.01)Gd(0.02)Ce(0.04)B(0.1)Si(0.83)O(delta), The luminance of this borosilicate glass was 67% that of ZnS:Cu,Al at 400-nm excitation.

摘要

一种涉及遗传算法和组合化学的进化优化过程被用于开发适用于三色白光发光二极管的绿色荧光粉。为了在400nm激发下实现高发光效率，我们筛选了一种包含Tb、Gd、Ce、Mg、Si、Al和B的七阳离子氧化物体系。当应用于荧光粉筛选时，遗传算法和组合化学的结合提高了搜索效率。结果，优化后的组成是Tb(0.01)Gd(0.02)Ce(0.04)B(0.1)Si(0.83)O(δ)，这种硼硅酸盐玻璃在400nm激发下的亮度是ZnS:Cu,Al的67%。