Sustainability Assessment on Power Semiconductor Device Manufacturing

Power semiconductor device manufacturing spans multiple material platforms, device architectures, voltage classes, wafer formats, and integration schemes. The next step is to transform these technology-specific models into a consistent generational framework that enables like-for-like comparison while preserving the process differences that define each platform. 

In this internship, the student will build and extend a process-flow model for power semiconductor manufacturing across different device generations and technologies. The student will:

• Review and map existing process flows for selected power semiconductor devices and identify the key manufacturing steps and differences between technology generations.
• Break down the process flows into reusable modules such as wafer preparation, epitaxy, isolation, implantation, thermal processing, metallization, passivation, and other relevant manufacturing steps.
• Create generation-specific process-flow tables, defining parameters such as wafer size, material consumption, layer thickness, process conditions, number of process steps, and other relevant assumptions.
• Collect and document the evidence behind process parameters and assumptions, and identify the main sources of uncertainty where data are not available.
• Implement selected process-flow variants in the imec.netzero modelling environment and run environmental impact calculations.
• Compare different technology generations to quantify how changes in device architecture and manufacturing processes affect cradle-to-gate environmental impact.
• Summarize and visualize the results, identifying which process modules and technology changes are the main contributors to environmental impact and where further data or model refinement is needed.

The outcome will be a reusable process-flow modelling framework that can be extended to additional power semiconductor generations and technologies, enabling systematic comparison of their manufacturing-related environmental footprints.