Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning.,ACS Combinatorial Science

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Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning.
ACS Combinatorial Science Pub Date : 2020-04-26 , DOI: 10.1021/acscombsci.0c00035
Fan Yang ₁ , Yanxing Wang ₁ , Xue Jiang ₁ , Bi Lin ₁ , Ruichan Lv ₁

Affiliation

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.

中文翻译：

优化的多金属敏化荧光粉，可通过机器学习增强红色上转换发光。

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用于解决“低上转换发光（UCL）强度”问题，以便找到具有增强的红色UCL发射的最佳磷光体使用多元素K / Li / Mn金属调制。与第一代荧光粉相比，GA优化的第三代荧光粉具有最佳的荧光强度，亮度更高（4.91倍），相对量子产率更高（6.40倍），并且组织穿透力更高深度（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，强度先升高后降低，而优化的K + Li + Mn浓度为6.03％。为了确认GA亮度优化的稳定性，以相同的元素比例合成了一批荧光粉，并通过SVM算法和分类精度指标对两批荧光粉的荧光强度进行了相似性评估。最后，将优化的荧光粉用于生物成像和荧光粉LED。

更新日期：2020-04-14

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