In the burgeoning field of sensing, Photonic Integrated Circuits (PICs) are essential tools for precise, high-speed detection of biological markers and particles. The performance of these biosensors is intricately linked to the losses of PICs, which is largely determined by the configuration of their core and cladding layers. Recognizing this, the present study ventures into the optimization of these layers in Silicon Nitride (Si3N4) PICs, employing an innovative approach using Classification and Regression Trees (CART). The study identifies propagation and bend losses, two critical factors affecting PIC performance, as response variables. In contrast, the physical characteristics of the core and cladding layers are considered as input variables. To ensure the robustness and completeness of the study, an appropriate Design of Experiments (DOE) is implemented, meticulously exploring possible combinations of layer configurations. Following the DOE, the CART algorithm is then applied to this design space, whereas the losses act as response variables. The algorithm functions by partitioning the design space into regions associated with specific layer configurations and iteratively refines these partitions based on their corresponding impact on propagation and bend losses. The end results of this process is the statistical information about the layer stacks which come with significantly low propagation and bend losses, thereby enhancing PIC performance. This improvement in performance directly translates to heightened sensitivity and specificity in biosensors. Further, the application of the CART methodology has demonstrated its potential to streamline the PIC design process, enhancing its robustness, an aspect critical for practical implementation in fabrication environments.
Micro-ring resonators (MRR) are basic photonic components, which serve as crucial building blocks for a variety of devices, e.g. integrated sensors, external cavity lasers, and high speed photonic data transmitters. Silicon nitride photonic platforms are particularly appealing in this field of application, since this waveguide material enables on-chip photonic circuitry with (ultra-) low losses in the NIR as well as across the whole visible spectral range. In this contribution we investigate key performance properties of MRRs in the wavelength range around 850 nm, such as free spectral range (FSR), quality factor (Q factor) and extinction ratio. We systematically investigate a large parameter space given by the MRR radii, coupling gaps between ring and bus waveguide, as well as waveguide width. Furthermore, we compare key properties such as the Q factor between low pressure chemical vapor deposition (LPCVD) and plasma enhanced chemical vapor deposition (PECVD) Si3N4 platforms and find enhanced values for LPCVD ring resonators reaching nearly a Q factor of 106.The fabrication is carried out with standard CMOS foundry equipment, utilizing photolithography and reactive ion etching on 250 nm thick silicon nitride films. As cladding material, high density PECVD silicon oxide is deposited prior to the waveguide onto bare silicon and a sputtered oxide serves as upper cladding. With this process toolbox full CMOS backend compatibility is achieved when considering only PECVD Si3N4 waveguide material. In terms of manufacturability, special focus is put on the die-to-die as well as on wafer-to-wafer variability of the performance parameters, which is crucial when considering mass production of MRR devices. Finally, the experimental findings are compared to finite difference time domain (FDTD) simulations of the MRR circuits revealing excellent agreement when considering the manufacturing variability.
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