片上低阈值半导体激光器与片上光信号处理及单片异质集成数据集

目前针对生物病毒等的检测多基于实时荧光聚合酶链反应核酸检测法存在的问题，开展片上荧光系统所需的可见光波段硅基光子芯片异质集成关键技术研究。波导集成芯片可大大提高生物样品检测的灵敏度，可实现对化合物、蛋白质、核酸、细胞或其它生物组分准确、快速、大信息量的筛选或检测，且可规模化低成本生产。过研究氮化硅与有源材料波导模式匹配以及耦合物理机制、有源材料生长等关键工艺及与氮化硅波导异质集成的共性关键技术、片上激发、滤波、收集的集成系统构架、器件设计以及加工工艺，重点解决氮化硅—有源材料异质集成技术，为后续片上荧光系统在生物检测中的应用奠定基础。数据集包含可见光波段连续光低阈值激发的半导体激光器的研发、硅纳米线辅助高均匀阵列波导光栅、三维波导结构的微环谐振腔品质因子、谱分析图像数据处理软件、高折射率、低本征噪声、低传输损耗的氮化硅材料等数据。数据集容量为4.24GB。

Currently, aiming at the problems existing in the real-time fluorescence polymerase chain reaction (PCR) nucleic acid detection method which is widely used for the detection of biological viruses and others, this research focuses on the key heterogeneous integration technologies of silicon-based photonic chips in the visible light band required for on-chip fluorescence systems. Waveguide-integrated chips can greatly improve the sensitivity of biological sample detection, enabling accurate, rapid, and information-rich screening or detection of compounds, proteins, nucleic acids, cells, or other biological components, and can be produced on a large scale at low cost. By studying key processes such as waveguide mode matching and coupling physical mechanisms between silicon nitride and active materials, growth of active materials, common key technologies for heterogeneous integration with silicon nitride waveguides, integrated system architecture for on-chip excitation, filtering, and collection, device design, and fabrication processes, the research focuses on solving the silicon nitride-active material heterogeneous integration technology, laying a foundation for the subsequent application of on-chip fluorescence systems in biological detection. The dataset includes data on the development of semiconductor lasers with continuous light low-threshold excitation in the visible light band, silicon nanowire-assisted highly uniform arrayed waveguide gratings, quality factors of microring resonators with three-dimensional waveguide structures, spectral analysis image data processing software, and silicon nitride materials with high refractive index, low intrinsic noise, and low transmission loss. The dataset size is 4.24GB.