PhD scholarships
PhD scholarship: Compound semiconductor manufacturing supply chain sustainability and resiliency
This is a fully funded PhD with tuition fees and stipend for 3.5 years at £19,237 per annum.
Project description
This PhD project will support The Compound Semiconductor (CS) Manufacturing Hub for a Sustainable Future, based at Sheffield University Management School, led by Professor Lenny Koh. The Compound Semiconductor Manufacturing Hub for a Sustainable Future is 1 of 5 new hubs aiming to address the challenge of commercialising early-stage research within key areas of manufacturing funded by EPSRC and industry and launched in May 2024. In addition to being part of the research community at University of Sheffield, the researcher will join the CS Centre for Doctoral Training (CDT) community and will work closely with the Post Doctoral Research Fellow in the CS Hub.
The CS hub aims to capitalise on the huge opportunity of compound semiconductor manufacturing, as identified in the UK’s national semiconductor strategy. Researchers will develop energy-efficient opto-electronics for use in key emerging technologies such as quantum. We will expand on the environmental benefits of compound semiconductors by creating new devices such as mercury-free ‘night vision’ mid-infrared detector arrays and devices that both communicate and illuminate based on integrated transistors and LEDs.
The CS Hub is led from Cardiff University, with spokes at the University of Cambridge, University of Manchester, University of Sheffield, and University College London. We have >30 industrial partners participating in the CS Hub by providing resources, time and expertise.
We also have strong links with colleagues in other Hubs, particularly the Future Advanced Metrology Hub and the Future Photonics Hub. These links support and complement our CS research, and facilitate larger investments for promising, cross-cutting feasibility studies.
Almost all products and devices on the planet and in space are powered by semiconductor or compound semiconductor, directly or indirectly. The AI, electronic and cyber future will further exacerbate this dependency. This PhD project aims to develop new model and novel methodology to situate the compound semiconductor manufacturing supply chain from lab to x. This will focus on the process of enabling fundamental research through wafer, device and integrated chip manufacturing into prototyping, reliability testing and system qualification. It will extend to pilot and industrial scale manufacturing and application cases e.g. aerospace, healthcare, telecommunication etc. Advanced scenario models will be developed to assess and predict their environmental sustainability, resiliency and techno-economic performance based on their integrated functionality. Combined prospective spatial hybrid life cycle assessment (LCA), manufacturing supply chain mapping, environmental sustainability and resiliency measurement, and techno-economic analysis of compound semiconductor manufacturing will be conducted. The new model will capture the transition towards future sustainable and resilient manufacturing for compound semiconductor from lab to x, whilst the novel methodology will capture the steps required to build a secured world.
Our work aims to radically boost the uptake and application of CS technology by applying the manufacturing approaches of Silicon to CS. It exploits the highly advantageous electronic, magnetic, optical and power-handling properties of CS while utilising the cost and scaling advantage of Silicon technology where suitable. And it generates novel integrated functionality, such as sensing, data processing and communication. Our researchers have a track record in innovation and impact, complementary technical capability and the individual skill sets that can combine to create new solutions to the identified major scientific challenges in manufacturing.
Learn more about the Manufacturing Hubs
Learn more about the Compound Semiconductor Hub
Learn more about the ESPRC funded project
Follow the instructions linked below to apply.
Application deadline: 15 November 2024
Lead supervisor
For informal enquiries, please contact Professor Lenny Koh.
