AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.
Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry transitions into an ordered state, it can form stable imperfections known as ...
A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), in collaboration with Dr. Jaemin Wang and Prof. Dierk Raabe of the ...
Researchers built an AI system that adapts to process changes, maintaining defect detection accuracy and lowering retraining costs in smart factories. (Nanowerk News) Artificial intelligence is ...
A recent review article published in Advanced Materials explored the potential of artificial intelligence (AI) and machine learning (ML) in transforming thermoelectric (TE) materials design. The ...
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AI-based model measures atomic defects in materials
In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during ...
BMW researchers have demonstrated that camera-based inspection systems can catch manufacturing flaws in battery electrodes before those flaws ever reach a finished cell, according to a peer-reviewed ...
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