Modifying the structure of surface plasmon resonance based sensors by adding 2D materials has been proven to considerably enhance the sensor’s sensitivity in comparison to a traditional three layer configuration. Moreover, a thin semiconductor film placed on top of the metallic layer and stacked together with 2D materials enhances even more sensitivity, but at the cost of worsening the plasmonic couplic strength at resonance (minimum level of reflectivity) and broadening the response. With each supplementary layer added, the complexity of optimizing the performance increases due to the extended parameter space of the sensor. This study focused on overcoming these difficulties in the design process of sensors by employing a multi-objective genetic algorithm (NSGA II) alongside a transfer matrix method (TMM) and, at the same time, optimizing the sensitivity to full width at half maximum (FWHM), and the reflectivity level at a resonance for a four layer sensor structure. Firstly, the thin semiconductor’s refractive index was optimized to obtain the maximum achievable sensitivity with a narrow FWHM and a reflectivity level at a resonance of almost zero. Secondly, it was shown that refractive indices of barium titanate (BaTiO₃) and silicon (Si) are the closest to the optimal indices for the silver—graphene/WS₂ and MoS₂ modified structures, respectively. Sensitivities up to 302 deg/RIU were achieved by Ag–BaTIO₃–graphene/WS₂ configurations with an FWHM smaller than 8 deg and a reflectivity level less than 0.5% at resonance.

中文翻译：

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基于二维材料的基于表面等离子体共振（SPR）的传感器的多目标优化：NSGA II方法

与传统的三层配置相比，通过添加2D材料来修改基于表面等离子共振的传感器的结构已被证明可以大大提高传感器的灵敏度。此外，放置在金属层顶部并与2D材料堆叠在一起的半导体薄膜甚至可以提高灵敏度，但代价是会降低共振时的等离子体耦合强度（最小反射率）并扩大响应范围。添加每个辅助层后，由于传感器的参数空间扩展，优化性能的复杂性增加了。这项研究致力于通过采用多目标遗传算法（NSGA II）和传递矩阵方法（TMM）来克服传感器设计过程中的这些困难，同时，针对四层传感器结构优化了对半峰全宽（FWHM）的灵敏度以及谐振时的反射率水平。首先，对薄半导体的折射率进行了优化，以在窄FWHM和接近零共振的反射率水平下获得最大可实现的灵敏度。其次，显示了钛酸钡（BaTiO₃）和硅（Si）分别最接近于银-石墨烯/ WS ₂和MoS ₂改性结构的最佳折射率。Ag–BaTIO ₃ –石墨烯/ WS _2的配置实现了高达302度/ RIU的灵敏度，FWHM小于8度，共振时的反射率小于0.5％。