We report a neural network model for predicting the electromagnetic response of mesoscale metamaterials as well as generate design parameters for a desired spectral behavior. Our approach entails treating spectral data as time-varying sequences and the inverse problem as a single-input multiple output model, thereby compelling the network architecture to learn the geometry of the metamaterial designs from the spectral data in lieu of abstract features.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452651 | PMC |
| http://dx.doi.org/10.1038/s41598-021-97999-6 | DOI Listing |
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