Adaptive guided stochastic optimization: A novel approach for fitting the theoretical intensity parameters for lanthanide compounds

Q2 Engineering Optical Materials: X Pub Date : 2023-10-18 DOI:10.1016/j.omx.2023.100275
Carlos V. Santos-Jr. , Eduardo C. Aguiar , Albano N. Carneiro Neto , Renaldo T. Moura Jr.
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Abstract

In this study, we introduce a state-of-the-art approach to enhance the fitting accuracy of theoretical intensity parameters in lanthanide spectroscopy. Lanthanide-based compounds play a pivotal role in a wide range of applications due to their distinctive photophysical characteristics. Theoretical understanding and computational descriptions are essential for advancing these applications. The Judd-Ofelt theory stands as a fundamental stone, offering insights into the luminescence exhibited by lanthanide compounds. Our methodology addresses the procedure of fitting charge factors (g in the Simple Overlap Model) and ligand effective polarizabilities (α in the Bond Overlap Model), quantities used for the determination of the intensity parameters (Ωλ). We propose Adaptive Guided Stochastic Optimization (AGSO), a method that employs randomized initial points within predefined bounds for each variable. By iteratively updating variable bounds based on population statistics, AGSO systematically minimizes the error function with respect to experimental data. Extensive tests were conducted comparing AGSO with the well-established simulated annealing (SA) method. Remarkably, AGSO consistently outperformed SA, demonstrating its efficacy in fitting intensity parameters for various lanthanide compounds. Through AGSO, we offer a robust and efficient tool for the accurate study of lanthanide-based compounds, with broad implications for diverse applications.

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自适应引导随机优化:拟合镧系化合物理论强度参数的新方法
在这项研究中,我们引入了一种最新的方法来提高理论强度参数在镧系光谱中的拟合精度。镧系化合物由于其独特的光物理特性在广泛的应用中发挥着关键作用。理论理解和计算描述对于推进这些应用至关重要。Judd-Ofelt理论作为基石,提供了对镧系化合物发光的见解。我们的方法解决了拟合电荷因子(简单重叠模型中的g)和配体有效极化率(键重叠模型中的α ')的过程,用于确定强度参数的数量(Ωλ)。我们提出了自适应引导随机优化(AGSO),一种在预定义范围内为每个变量使用随机初始点的方法。通过迭代更新基于总体统计的变量边界,AGSO系统地最小化了相对于实验数据的误差函数。进行了大量的试验,比较AGSO和成熟的模拟退火(SA)方法。值得注意的是,AGSO始终优于SA,证明了其在拟合各种镧系化合物强度参数方面的有效性。通过AGSO,我们为镧系化合物的精确研究提供了一个强大而高效的工具,具有广泛的应用前景。
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来源期刊
Optical Materials: X
Optical Materials: X Engineering-Electrical and Electronic Engineering
CiteScore
3.30
自引率
0.00%
发文量
73
审稿时长
91 days
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