Nonparametric design of nanoparticles with maximum scattering using evolutionary topology optimization
Nonparametric design of nanoparticles with maximum scattering using evolutionary topology optimization
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DOI：
10.1016/j.ijheatmasstransfer.2020.120738
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发表时间：
2021-02
影响因子：
5.2
通讯作者：
Mine Kaya;S. Hajimirza
中科院分区：
文献类型：
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作者：
Mine Kaya;S. Hajimirza
光和亚波长结构之间的相互作用提供了可定制的光学性质，可以在许多工程应用中使用。这些性质强烈依赖于材料的形状，这提供了获得独特的散射特性时，严格设计。然而，传统的设计方法需要对散射物体的形状进行精确的建模和表征，因此需要大量关于小尺度光辐射的直觉和知识，以及许多轮的实验试验和错误。我们提出了一个框架，发现新的纳米粒子设计，改善散射的拓扑优化的基础上。该框架允许我们最大化粒子域的散射截面。纳米级散射截面的增加导致光捕获的改善，这在许多应用中是至关重要的，例如薄膜太阳能电池和生物成像。拓扑优化提供了一个知识独立的设计过程，因此揭示了设计域中的特定区域与最大散射截面的光行为之间的关系。
The interaction between light and subwavelength structures provides tailorable optical properties that can be useful in many engineering applications. These properties strongly depend on the material shape, which provides obtaining unique scattering characteristics when rigorously designed. However, the conventional design methods require precise modeling and characterization of the shapes of the scattering objects, thus requiring a lot of intuition and knowledge about light radiation at small scales, as well as many rounds of experimental trial and error. We propose a framework to discover new nanoparticle designs for improved scattering based on topology optimization. The framework allows us to maximize the scattering cross section of the particle domain. Increased scattering cross-section at nanoscale leads to improved light trapping, which is critical in many applications such as thin film solar cells and biological imaging. Topology optimization offers a knowledge independent design procedure, therefore revealing relationships between specific regions in the design domain and the light behavior for maximum scattering cross section.