Design of high-performance Au-Ag-dielectric-graphene based surface plasmon resonance biosensors using genetic algorithm
Design of high-performance Au-Ag-dielectric-graphene based surface plasmon resonance biosensors using genetic algorithm
复制标题
利用遗传算法设计基于金银电介质石墨烯的高性能表面等离子体共振生物传感器
DOI：
10.1063/1.5066354
复制
发表时间：
2019-03-21
影响因子：
3.2
通讯作者：
Chen, Shujing
中科院分区：
文献类型：
--
作者：
Lin, Chengyou;Chen, Shujing
提出了一种基于遗传算法的表面等离子体共振（SPR）生物传感器的设计方法。在遗传算法的评价函数中引入了灵敏度和反射率在谐振角处的约束条件，实现了灵敏度和分辨率的同时优化。利用所提出的方法，我们首先设计了一种基于Au-Ag-TiO 2-graphene的SPR生物传感器，并将其性能与传统的基于Au-graphene的SPR生物传感器进行了比较。在相同灵敏度的前提下，所设计的传感器的分辨率是传统传感器的近3倍。此外，利用MF中不同的目标灵敏度，设计了一系列灵敏度在50 °/RIU ~ 180°/RIU之间，分辨率提高的SPR生物传感器。将所设计的生物传感器与传统的金-石墨烯SPR生物传感器进行了比较，证明了存在比传统传感器具有更高灵敏度和更高分辨率的生物传感器。最后，研究了靶在共振角处的反射率和棱镜对Au-Ag-TiO 2-graphene基SPR生物传感器设计的影响。基于遗传算法的表面等离子体共振（SPR）生物传感器的设计方法可用于任意多层结构SPR生物传感器的性能优化，本文提出了一种基于遗传算法的高性能SPR生物传感器的设计方法。在遗传算法的评价函数中引入了灵敏度和反射率在谐振角处的约束条件，实现了灵敏度和分辨率的同时优化。利用所提出的方法，我们首先设计了一种基于Au-Ag-TiO 2-graphene的SPR生物传感器，并将其性能与传统的基于Au-graphene的SPR生物传感器进行了比较。在相同灵敏度的前提下，所设计的传感器的分辨率是传统传感器的近3倍。此外，利用MF中不同的目标灵敏度，设计了一系列灵敏度在50 °/RIU ~ 180°/RIU之间，分辨率提高的SPR生物传感器。将所设计的生物传感器与传统的金-石墨烯SPR生物传感器进行了比较，结果表明，所设计的生物传感器比传统的SPR生物传感器具有更高的灵敏度和分辨率。
In this paper, we presented a design method of a surface plasmon resonance (SPR) biosensor with high performance using a genetic algorithm (GA). The constraint conditions of the sensitivity and the reflectivity at the resonance angle were used in the merit function (MF) of GA to achieve simultaneous optimization of the sensitivity and the resolution. By using the proposed method, we designed an Au-Ag-TiO2-graphene based SPR biosensor at first and compared its performance with a traditional Au-graphene based SPR biosensor. The resolution of the designed biosensor was nearly three times that of the traditional one on the premise of the same sensitivity. In addition, a series of SPR biosensors with sensitivities ranging from 50 to 180°/RIU and improved resolutions was designed by using different target sensitivities in MF. A comparison of the designed biosensors with the traditional Au-graphene SPR biosensor was also done, and the biosensors with higher sensitivity and meanwhile higher resolution than the traditional one were demonstrated to be existed. Lastly, the influences of target reflectivity at the resonance angle and the prism on the design of the Au-Ag-TiO2-graphene based SPR biosensor were investigated. It is believed that the proposed design method based on the genetic algorithm could be applied to optimize the performances of a SPR biosensor with an arbitrary multilayer structure.In this paper, we presented a design method of a surface plasmon resonance (SPR) biosensor with high performance using a genetic algorithm (GA). The constraint conditions of the sensitivity and the reflectivity at the resonance angle were used in the merit function (MF) of GA to achieve simultaneous optimization of the sensitivity and the resolution. By using the proposed method, we designed an Au-Ag-TiO2-graphene based SPR biosensor at first and compared its performance with a traditional Au-graphene based SPR biosensor. The resolution of the designed biosensor was nearly three times that of the traditional one on the premise of the same sensitivity. In addition, a series of SPR biosensors with sensitivities ranging from 50 to 180°/RIU and improved resolutions was designed by using different target sensitivities in MF. A comparison of the designed biosensors with the traditional Au-graphene SPR biosensor was also done, and the biosensors with higher sensitivity and meanwhile higher resolution than the tr...