Optimization methodology for structural multiparameter surface plasmon resonance sensors in different modulation modes based on particle swarm optimization
Optimization methodology for structural multiparameter surface plasmon resonance sensors in different modulation modes based on particle swarm optimization
复制标题
基于粒子群优化的结构多参数表面等离子体共振传感器不同调制模式的优化方法
DOI：
10.1016/j.optcom.2018.09.027
复制
发表时间：
2019
影响因子：
2.4
通讯作者：
Zhan Shuyue
中科院分区：
文献类型：
--
作者：
Sun Yi;Cai Haoyuan;Wang Xiaoping;Zhan Shuyue
设计等离子体生物传感器的主要挑战之一是最大限度地提高其传感性能。提出了基于表面等离子体共振-粒子群优化（SPR-PSO）的启发式算法，对结构多参数SPR传感器在相位、强度、波长和角度4种调制模式下的传感性能进行了优化研究。针对不同的调制模式设计了不同的适应度函数，该适应度函数包含多种评价指标（如灵敏度、品质因数、半高宽、电场强度和穿透深度）。四种类型的可用的实验结构，代表各种调制方案与相应的优化结构的算法进行了比较。实验结果表明，所提出的算法具有相当高的效率.此外，该算法在辅助负折射率材料的参数化设计方面也显示出一定的潜力。
One of the main challenges in designing plasmonic biosensors is maximizing their sensing performance. This study proposes heuristic algorithms based on surface plasmon resonance-particle swarm optimization (SPR-PSO), which were investigated for the optimization of the sensing performance of structural multiparameter SPR sensors in four modulation modes (phase, intensity, wavelength, and angle). Different fitness functions were designed for different modulation modes that comprised a variety of evaluation indicators (such as sensitivity, figure of merit, full-width-at-half-maximum, electric field intensity, and penetration depth). Four types of available experimental structures representing the various modulation schemes were compared with the corresponding optimized structure by algorithms. The results showed that the introduced algorithms have a considerable efficiency. Furthermore, the algorithms also showed some potential in aiding the parametric design of negative refractive index materials.