Machine learning helps track semiconductor defects under more realistic temperature conditions
Summary
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.
Description from Phys.
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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.
