Machine learning helps track semiconductor defects under more realistic temperature conditions

All materials contain inherent defects. These are not always harmful, since they can be used to engineer and introduce certain properties into a material. However, it is crucial to understand how they function and how they affect the material's properties.

Originally published at Phys.org