论文部分内容阅读
提出了多孔硅表面缺陷光子晶体结构,引入多孔硅敏感层及吸收介质层形成表面缺陷腔,利用多孔硅高效的承载机制,将其作为待测样本的传感区域;由于吸收介质Zn S对谐振波长的吸收,可在反射光谱中获得与谐振波长对应的缺陷峰。以多孔硅的厚度为被优化变量,利用反向传播神经网络进行结构参数优化获得多孔硅的厚度最优值。由Goos-H?nchen位移建立待测样本浓度与缺陷峰波长的关系模型,进而对该结构进行传感特性分析。结果表明,优化结构参数后,缺陷峰对应的反射率由31.23%下降到0.00129%,其Q值可达1537.37。在传感特性研究中,每1%质量分数的灵敏度为2.5 nm。该表面缺陷光子晶体传感结构可为样本浓度、组分等信息的监测提供一定的理论参考。
Porous silicon surface defect photonic crystal structure was proposed, the porous silicon sensitive layer and the absorption medium layer were introduced to form the surface defect cavity. The porous silicon carrier was used as the sensing area of the sample to be tested. The absorption of the wavelength can obtain the defect peak corresponding to the resonance wavelength in the reflection spectrum. Taking the thickness of porous silicon as the optimized variable, the optimum thickness of porous silicon was obtained by using backpropagation neural network to optimize the structural parameters. The relationship between the sample concentration and the peak wavelength of the defect is established by Goos-Hönchen shift, and then the sensing characteristic of the structure is analyzed. The results show that the reflectivity corresponding to the defect peak decreases from 31.23% to 0.00129% and the Q value reaches 1537.37 after optimizing the structural parameters. The sensitivities for every 1% mass fraction in the sensory study are 2.5 nm. The surface defect photonic crystal sensing structure can provide certain theoretical reference for the monitoring of sample concentration, composition and other information.