Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning
Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning
复制标题
通过机器学习优化多金属敏化荧光粉以增强红色上转换发光
DOI：
10.1021/acscombsci.0c00035
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Lv Ruichan
中科院分区：
文献类型：
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作者：
Yang Fan;Wang Yanxing;Jiang Xue;Lin Bi;Lv Ruichan
在这项研究中，包括遗传算法（GA）和支持向量机（SVM）算法在内的机器学习被用来解决“低上转换发光（UCL）强度”问题，以便找到使用多元素K/Li/Mn金属调制增强红色UCL发射的最佳荧光粉。与第一代荧光粉相比，经过GA优化的第三代荧光粉的荧光强度最好，具有更强的亮度（4.91倍）、更高的相对量子产率（6.40倍）和增强的组织穿透深度（5毫米）。还研究了单一和多种掺杂剂对K+Li+Mn敏化剂上转换强度的影响：随着Yb/Er/K+Li+Mn含量的增加，强度先增大后减小，优化的K+Li+Mn浓度为6.03%。为了证实遗传算法亮度优化的稳定性，合成了一批相同元素比例的荧光粉，并通过SVM算法以分类精度指标评价两批次荧光粉荧光强度的相似度。最后，优化后的荧光粉用于生物成像和荧光粉LED。
In this research, machine learning including the genetic algorithm (GA) and support vector machine (SVM) algorithm is used to solve the “low up-conversion luminescence (UCL) intensity” problem in order to find the optimal phosphor with enhanced red UCL emission using multielement K/Li/Mn metal modulation. Compared with the first generation of phosphors, the best phosphors’ fluorescence intensity occurs in the third generation optimized by the GA, with a stronger brightness (4.91-fold), a higher relative quantum yield (6.40-fold), and an enhanced tissue penetration depth (by 5 mm). The single and multiple dopants effect on the upconversion intensity of K+Li+Mn sensitizers is also studied: the intensity increases first and then decreases with the increase of Yb/Er/K+Li+Mn content, and the optimized K+Li+Mn concentration is 6.03%. In order to confirm the stability of the brightness optimization by the GA, a batch of phosphors was synthesized with the same element proportion, and the similarity of fluorescence intensity of two batches of phosphors was evaluated by the SVM algorithm with the classification accuracy index. Finally, the optimized phosphor was used for bioimaging and phosphor-LED.