Nanowerk June 15, 2018
Researchers at Northeastern University have developed a deep-learning-based model, comprising two bidirectional neural networks assembled by a partial stacking strategy, to automatically design and optimize three-dimensional chiral metamaterials with strong chiroptical responses at predesignated wavelengths. The model can help to discover the intricate, nonintuitive relationship between a metamaterial structure and its optical responses from a number of training examples. This approach realizes the forward prediction of optical performance much more accurately and efficiently and helps inversely retrieve designs from given requirements…read more. TECHNICAL ARTICLEÂ
Credit: ACS Nano, Article ASAP, Publication Date (Web): June 1, 2018