Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy
Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy
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DOI：
10.1364/oe.20.011953
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发表时间：
2012-05-21
期刊：
影响因子：
3.8
通讯作者：
Altug, Hatice
中科院分区：
文献类型：
--
作者：
Liberman, Vladimir;Adato, Ronen;Altug, Hatice
我们提出了一种合理的设计和优化的等离子体阵列的超灵敏表面增强红外吸收（SEIRA）光谱的特定蛋白质分析物的方法。受我们先前的工作的启发，所述工作证明了表面结合的丝素蛋白的亚阿托摩尔检测[Proc. Natl. Acad. Sci. U.S.A. 106，19227（2009）]，我们在此介绍一种通用框架，其允许超材料传感器设计的数值优化，以便最大化吸收信号。我们的方法的一个关键特征是显式补偿分析物的折射率的微扰效应，其改变超材料响应的谐振频率和线形，从而导致SEIRA签名中的光谱失真。作为一个例子，我们利用我们的方法来优化的等离子体纳米粒子的Si和CaF2基板上的周期性阵列的几何形状。与非结构化Au层相比，最佳几何形状导致三个数量级的吸光度增强，其中CaF2衬底提供比传统Si衬底增加三倍的吸光度增强。后者的改善来自于较低折射率衬底的Au纳米棒表面上的近场强度的增加。最后，我们进行灵敏度分析，我们的优化阵列，以预测制造缺陷的影响。我们发现
We present an approach for rational design and optimization of plasmonic arrays for ultrasensitive surface enhanced infrared absorption (SEIRA) spectroscopy of specific protein analytes. Motivated by our previous work that demonstrated sub-attomole detection of surface-bound silk fibroin [Proc. Natl. Acad. Sci. U.S.A. 106, 19227 (2009)], we introduce here a general framework that allows for the numerical optimization of metamaterial sensor designs in order to maximize the absorbance signal. A critical feature of our method is the explicit compensation for the perturbative effects of the analyte's refractive index which alters the resonance frequency and line-shape of the metamaterial response, thereby leading to spectral distortion in SEIRA signatures. As an example, we leverage our method to optimize the geometry of periodic arrays of plasmonic nanoparticles on both Si and CaF2 substrates. The optimal geometries result in a three-order of magnitude absorbance enhancement compared to an unstructured Au layer, with the CaF2 substrate offering an additional factor of three enhancement in absorbance over a traditional Si substrate. The latter improvement arises from increase of near-field intensity over the Au nanobar surface for the lower index substrate. Finally, we perform sensitivity analysis for our optimized arrays to predict the effects of fabrication imperfections. We find that