Machine learning finds new metamaterial designs for energy harvesting
Electrical engineers have harnessed the power of machine learning to design dielectric (non-metal) metamaterials that absorb and emit specific frequencies of terahertz radiation. The technique drops the time needed to simulate possible configurations from more than 2,000 years to 23 hours, which should facilitate the design of sustainable types of thermal energy harvesters and lighting.
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