Institute of Photonics and Electronics of the Czech Academy of Sciences, Chaberská 1014/57, 182 51 Prague, Czech Republic.
Lab Chip. 2019 Dec 21;19(24):4117-4127. doi: 10.1039/c9lc00699k. Epub 2019 Nov 19.
The study of optical affinity biosensors based on plasmonic nanostructures has received significant attention in recent years. The sensing surfaces of these biosensors have complex architectures, often composed of localized regions of high sensitivity (electromagnetic hot spots) dispersed along a dielectric substrate having little to no sensitivity. Under conditions such that the sensitive regions are selectively functionalized and the remaining regions passivated, the rate of analyte capture (and thus the sensing performance) will have a strong dependence on the nanoplasmonic architecture. Outside of a few recent studies, there has been little discussion on how changes to a nanoplasmonic architecture will affect the rate of analyte transport. We recently proposed an analytical model to predict transport to such complex architectures; however, those results were based on numerical simulation and to date, have only been partially verified. In this study we measure the characteristics of analyte transport across a wide range of plasmonic structures, varying both in the composition of their base plasmonic element (microwires, nanodisks, and nanorods) and the packing density of such elements. We functionalized each structure with nucleic acid-based bioreceptors, where for each structure we used analyte/receptor sequences as to maintain a Damköhler number close to unity. This method allows to extract both kinetic (in the form of association and dissociation constants) and analyte transport parameters (in the form of a mass transfer coefficient) from sensorgrams taken from each substrate. We show that, despite having large differences in optical characteristics, measured rates of analyte transport for all plasmonic structures match very well to predictions using our previously proposed model. These results highlight that, along with optical characteristics, analyte transport plays a large role in the overall sensing performance of a nanoplasmonic biosensor.
基于等离子体纳米结构的光学亲和生物传感器的研究近年来受到了广泛关注。这些生物传感器的传感表面具有复杂的结构，通常由沿介电基底分布的局部高灵敏度区域（电磁热点）组成，而这些基底几乎没有灵敏度。在敏感区域被选择性功能化而其余区域被钝化的条件下，分析物的捕获速率（从而影响传感性能）将强烈依赖于纳米等离子体结构。除了最近的少数几项研究外，对于纳米等离子体结构的变化如何影响分析物传输速率的讨论很少。我们最近提出了一种分析模型来预测这种复杂结构的传输；然而，这些结果是基于数值模拟的，并且迄今为止，仅得到了部分验证。在这项研究中，我们测量了横跨广泛的等离子体结构的分析物传输特性，这些结构在其基本等离子体元件（微丝、纳米盘和纳米棒）的组成以及这些元件的堆积密度方面都有所不同。我们用基于核酸的生物受体对每个结构进行功能化，对于每个结构，我们使用分析物/受体序列来保持达莫赫勒数接近 1。这种方法允许从每个基底的传感器图谱中提取动力学（以结合和解离常数的形式）和分析物传输参数（以质量转移系数的形式）。我们表明，尽管光学特性有很大差异，但所有等离子体结构的分析物传输测量速率与我们之前提出的模型的预测非常吻合。这些结果强调了，除了光学特性外，分析物传输在纳米等离子体生物传感器的整体传感性能中起着重要作用。
