Lv Ruichan, Xiao Liyang, Wang Yanxing, Yang Fan, Tian Jie, Lin Jun
Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology , Xidian University , Xi'an , Shaanxi 710071 , China.
State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry , Chinese Academy of Sciences , Changchun 130022 , China.
Inorg Chem. 2019 May 6;58(9):6458-6466. doi: 10.1021/acs.inorgchem.9b00667. Epub 2019 Apr 24.
In this research, four heuristic algorithms (HAs), including simulated annealing (SA), improved annealing with a harmony search algorithm (HSA), particle swarm optimization (PSO), and genetic algorithm (GA), were used to optimize the luminescent intensity of phosphor. Among the four HAs, the improved algorithm HSA got better phosphors than SA (without using the known coded concentration). The PSO algorithm got gradually better results with increased generation, and the GA could find the best local phosphors with shorter time. After further analysis of the 340 phosphors, we found that the final brightness has an optimized activator concentration (Tb: 0.21-0.26), and the results were further proved by another uniform host of NaGdF:Ce,Tb nanoparticles. The HA was proper to find the optimal concentration of the activator of Tb. Furthermore, the optimal phosphor could be used as a bioimaging agent and improved QR code.
在本研究中，使用了四种启发式算法（HA），包括模拟退火算法（SA）、结合和声搜索算法的改进退火算法（HSA）、粒子群优化算法（PSO）和遗传算法（GA）来优化磷光体的发光强度。在这四种启发式算法中，改进算法HSA比SA得到了更好的磷光体（未使用已知的编码浓度）。PSO算法随着迭代次数的增加得到的结果逐渐变好，而GA能在更短时间内找到最佳的局部磷光体。在对340种磷光体进行进一步分析后，我们发现最终亮度存在一个优化的激活剂浓度（Tb：0.21 - 0.26），并且这一结果通过另一种均匀基质的NaGdF:Ce,Tb纳米粒子得到了进一步验证。启发式算法适用于找到Tb激活剂的最佳浓度。此外，最佳磷光体可作为生物成像剂和改进的二维码使用。
