Metrology and Process Integration for defect mapping of next generation semiconductor materials and devices

Development of Metrology and Wafer Mapping Techniques for SiC, GaN, and GaO Semiconductors

This PhD project aims to develop advanced metrology and wafer mapping techniques for defect analysis in semiconductor materials such as Silicon Carbide (SiC), Gallium Nitride (GaN), and Gallium Oxide (GaO). The project will leverage machine learning to correlate these defects with electrical characterization data, ultimately developing high-throughput wafer mapping approaches to improve device yield predictions for these compound semiconductor materials.

The objectives of the project are:
Develop Advanced Metrology Tools: Enhance and innovate metrology tools for analyzing semiconductor wafers, focusing on SiC, GaN, and GaO materials, to identify defects accurately.
Machine Learning for Defect Analysis: Utilize machine learning techniques to classify and predict the impact of various defect types on semiconductor device performance.
High-Throughput Wafer Mapping: Implement and optimize high-throughput wafer mapping techniques to quickly identify areas with potential yield-impacting defects.
Correlation with Electrical Characterization: Develop models to correlate defect characteristics with electrical performance metrics across the wafers.
Collaboration and Training: Engage in multidisciplinary training and collaboration, as facilitated by the UK-SIFS program, to ensure the project aligns with industry needs and leverages expert knowledge effectively.

The project research will be conducted at the National Physical Laboratory, Teddington, UK. Some additional training may be undertaken at Swansea University, but this will only be for 2 weeks per annum.
This project plan sets the stage for advancements in semiconductor metrology and defect analysis, paving the way for improved yields and performance in the production of compound semiconductors like SiC, GaN, and GaO. The PhD project will develop new analysis tools for investigating semiconductor wafers and devices. The project...