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. This story matters for Science & Discovery readers tracking science. Reported by phys.org. Read the full original at the source link below.