Instituto Nacional de Telecomunicações (Inatel), Santa Rita do Sapucaí 37540-000, Brazil.
Escuela de Física, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja 150003, Colombia.
Sensors (Basel). 2022 Aug 3;22(15):5789. doi: 10.3390/s22155789.
Magnetoplasmonic permittivity-near-zero (ε-near-zero) nanostructures hold promise for novel highly integrated (bio)sensing devices. These platforms merge the high-resolution sensing from the magnetoplasmonic approach with the ε-near-zero-based light-to-plasmon coupling (instead of conventional gratings or bulky prism couplers), providing a way for sensing devices with higher miniaturization levels. However, the applications are mostly hindered by tedious and time-consuming numerical analyses, due to the lack of an analytical relation for the phase-matching condition. There is, therefore, a need to develop mechanisms that enable the exploitation of magnetoplasmonic ε-near-zero nanostructures' capabilities. In this work, we developed a genetic algorithm (GA) for the rapid design (in a few minutes) of magnetoplasmonic nanostructures with optimized TMOKE (transverse magneto-optical Kerr effect) signals and magnetoplasmonic sensing. Importantly, to illustrate the power and simplicity of our approach, we designed a magnetoplasmonic ε-near-zero sensing platform with a sensitivity higher than 56∘/RIU and a figure of merit in the order of 102. These last results, higher than any previous magnetoplasmonic ε-near-zero sensing approach, were obtained by the GA intelligent program in times ranging from 2 to 5 min (using a simple inexpensive dual-core CPU computer).
基于磁等离子体的近零介电常数（ε-near-zero）纳米结构有望应用于新型高度集成（生物）传感设备。这些平台将磁等离子体方法的高分辨率传感与基于 ε-near-zero 的光等离子耦合（而不是传统的光栅或庞大的棱镜耦合器）相结合，为具有更高小型化水平的传感设备提供了一种途径。然而，由于缺乏相位匹配条件的解析关系，这些应用主要受到繁琐和耗时的数值分析的阻碍。因此，需要开发能够利用磁等离子体 ε-near-zero 纳米结构的功能的机制。在这项工作中，我们开发了一种遗传算法（GA），用于快速设计（几分钟内）具有优化 TMOKE（横向磁光克尔效应）信号和磁等离子体传感的纳米结构。重要的是，为了说明我们方法的强大功能和简单性，我们设计了一种具有高于 56∘/RIU 的灵敏度和高于 102 的品质因数的磁等离子体 ε-near-zero 传感平台。这些最后结果高于任何以前的磁等离子体 ε-near-zero 传感方法，是通过 GA 智能程序在 2 到 5 分钟的时间范围内（使用简单廉价的双核 CPU 计算机）获得的。
