Publicaties
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YOLOv8 for defect inspection of hexagonal directed self-assembly patterns: a data-centric approach KU Leuven
SEMI-CenterNet: a machine learning facilitated approach for semiconductor defect inspection KU Leuven
Benchmarking Feature Extractors for Reinforcement Learning-Based Semiconductor Defect Localization KU Leuven
Microwave Properties of Ba-Substituted Pb(Zr0.52Ti0.48)O3 after Chemical Mechanical Polishing KU Leuven
Area-Selective Deposition of AlOx and Al-Silicate for Fully Self- Aligned Via Integration KU Leuven
The rush for better-performing electronics, and manufacturing processes that heavily rely on "top-down" patterning techniques, is making the integration of "self-aligned" fabrication methods, such as area-selective deposition (ASD), a critical objective for continued device scaling. The fully self-aligned via (FSAV) scheme is broadly proposed as a "killer application" to determine whether ASD can shift from an R&D process to high-volume ...