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    Machine Learning Speeds Metamaterial Design for Thermophotovoltaic Devices

    Article obtained from Photonics RSS Feed.

    A Duke University engineering team has used machine learning to design dielectric metamaterials that absorb and emit specific frequencies of terahertz (THz) radiation. Use of machine learning made it possible to calculate design requirements for the metamaterial in 23 hours — a process that without machine learning could have taken more than 2000 years, according to the team.

    The THz metamaterial is built up from a 2 × 2 grid of silicon cylinders resembling a short, square Lego. Adjusting the height, radius, and spacing of each of the four cylinders changes the frequencies with which the metamaterial interacts.

    An illustration of a dielectric metamaterial with infrared light shining on it. Courtesy of Willie…

    Sep, 26 2019 |

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