Optimal design of nanoplasmonic materials using genetic algorithms as a multiparameter optimization tool.
Optimal design of nanoplasmonic materials using genetic algorithms as a multiparameter optimization tool.
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DOI：
10.1063/1.2961011
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发表时间：
2008-02
期刊：
影响因子：
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通讯作者：
Joseph Yelk;M. Sukharev;T. Seideman
中科院分区：
文献类型：
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作者：
Joseph Yelk;M. Sukharev;T. Seideman
基于多参数遗传算法的最优控制方法被应用于具有预定光学性质和功能的等离子体纳米结构的设计。我们首先开发纳米级金属透镜，将入射平面波聚焦到预先指定的空间限制点上。我们的研究结果说明了通过线和腔的能量流的机制。接下来，我们设计了一个周期性的银粒子阵列，以修改入射的偏振，线性偏振平面波在所需的方式，同时在空间中定位的光。这些结果提供了对决定金属纳米颗粒及其阵列的双折射性质的结构特征的深入了解。各种潜在的应用，可以设想，我们注意到纳米级光源的设计与可控的相干性和偏振特性，可以用于相干控制的分子，电子，或机电动力学在纳米级。
An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with predetermined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a prespecified, spatially confined spot. Our results illustrate the mechanism of energy flow through wires and cavities. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with controllable coherence and polarization properties that could serve for coherent control of molecular, electronic, or electromechanical dynamics in the nanoscale.