The Integrated Photonic Devices Group, led by Professor James Wilkinson, was established in early 1990 to meet the demand for optical device functions of increasing complexity and parallelism.
Planar photonic devices are exploited in applications as diverse as telecommunications, tuneable and short-pulse miniature laser light sources, diagnostics in medicine, the environment and food processing, and early-warning sensors for biological agents.
We exploit surface science, waveguide engineering, laser physics and microstructure technology to realise robust mass-producible integrated optical circuits, to further the monolithic integration of diverse devices, and to develop novel materials processing for optoelectronic devices.
Supervisor: Senthil M Ganapathy
Cancer continues to be one of the most prevalent diseases worldwide. Cancer is associated with a very high mortality rate (50% survival at 10 years) as most cancers are diagnosed at a late stage. Recent advances have been made in early detection, though the assays employed are still experimental, highly expensive and can suffer from poor sensitivity and specificity. On the other hand, Mid-IR spectroscopy have shown to be robust in detecting cancer-specific analytes within the blood and other bodily fluids. However, conventional FTIR based measurements (including the use of ATR crystals) are insufficiently sensitive for such diagnostics at low analyte concentrations.
In this project, we will exploit highly sensitive evanescent wave Mid-IR spectroscopy using signal enhanced ATR chips and waveguide chips and will use machine learning approach for rapid early cancer diagnostics as well as therapy monitoring. In specific this project will involve the design and fabrication of highly sensitive disposable ATR and waveguide chips optimised for cancer (breast and ovarian) biomarker sensing. The fabricated chips will be utilised for Mid-IR spectroscopy of blood plasma samples obtained from our collaborators from Cancer Research UK at Cambridge University and the results will be analysed using machine learning and deep learning algorithms specifically developed for this purpose.
Supervisor: Senthil M Ganapathy
Both Mid-IR and Raman molecular fingerprint spectroscopies have been shown to be powerful biodiagnostic tools for specific biomarkers. Enhancing the sensitivity and improving the detection limit of current Mid-IR and Raman spectroscopic platforms are most important to exploit them for early diagnosis of disease biomarkers in point of care setting. Recently two-dimensional (2D) materials such as graphene and transition metal di-chalcogenides (TMDC) have shown huge potentials for spectroscopic signal enhancement.
In this project, we will develop highly sensitive ATR and Raman chips empowered with 2D material layer for super enhanced IR and Raman spectroscopies. We will develop bulk silicon and silicon on insulator (SOI) platforms coated with TMDCs in both ATR and waveguide configurations for enhanced Mid-IR and Raman spectroscopies. The diagnostic potential of these platforms will be evaluated using the detection of breast/ovarian cancer and neonatal respiratory distress syndrome biomarkers in collaboration with University of Cambridge and University College London Hospitals.