RESUMEN
This paper presents a novel co-packaging approach through on-chip hybrid laser integration with photonic circuits using photonic wire bonding. The process involves die-bonding a low-cost semiconductor distributed-feedback (DFB) laser into a deep trench on a silicon-on-insulator (SOI) chip and coupling it to the silicon circuitry through photonic wire bonding (PWB). After characterizing the power-current-voltage (LIV) and optical spectrum of the laser, a wavelength-current relationship utilizing its tunability through self-heating a swept-frequency laser (SFL) is developed. Photonic integrated circuit (PIC) resonators are successfully characterized using the SFL method, demonstrating signal detection with a quality factor comparable to measurements conducted with an off-chip benchtop laser.
RESUMEN
Silicon photonic (SiP) evanescent-field biosensors aim to combine the information-rich readouts offered by lab-scale diagnostics, at a significantly lower cost, and with the portability and rapid time to result offered by paper-based assays. While SiP biosensors fabricated with conventional strip waveguides can offer good sensitivity for label-free detection in some applications, there is still opportunity for improvement. Efforts have been made to design higher-sensitivity SiP sensors with alternative waveguide geometries, including sub-wavelength gratings (SWGs). However, SWG-based devices are fragile and prone to damage, limiting their suitability for scalable and portable sensing. Here, we investigate SiP microring resonator sensors designed with SWG waveguides that contain a "fishbone" and highlight the improved robustness offered by this design. We present a framework for optimizing fishbone-style SWG waveguide geometries based on numerical simulations, then experimentally measure the performance of ring resonator sensors fabricated with the optimized waveguides, targeting operation in the O-band and C-band. For the O-band and C-band devices, we report bulk sensitivities up to 349 nm/RIU and 438 nm/RIU, respectively, and intrinsic limits of detection as low as 5.1 × 10-4 RIU and 7.1 × 10-4 RIU, respectively. This performance is comparable to the state of the art in SWG-based sensors, positioning fishbone SWG resonators as an attractive, more robust, alternative to conventional SWG designs.
Asunto(s)
Técnicas Biosensibles , Silicio , Óptica y Fotónica , FotonesRESUMEN
Cardiovascular diseases(CVDs) are the world's leading cause of death. Endothelial Dysfunction is an early stage of cardiovascular diseases and can effectively be used to detect the presence of the CVDs, monitor its progress and investigate the effectiveness of the treatment given. This study proposes a reliable approach for the screening of endothelial dysfunction via machine learning, using features extracted from a combination of Plethysmography, Digital Thermal Monitoring, biological features (age and gender) and anthropometry (BMI and pulse pressure). This case control study includes 55 healthy subjects and 45 subjects with clinically verified CVDs. Following the feature engineering stage, the results were subjected to dimension reduction and 5-fold cross-validation where it was observed that models Logistic Regression and Linear Discriminant provided the highest accuracies of 84% and 81% respectively. We propose that this study can be used as an efficient guide for the non-invasive screening of endothelial dysfunction.