Deep Neural Networks: A Bidirectional Deep Neural Network for Accurate Silicon Color Design (Adv. Mater. 51/2019). Issue 51 (17th December 2019)

• Record Type: Journal Article
• Authors: Gao, Li; Li, Xiaozhong; Liu, Dianjing; Wang, Lianhui; Yu, Zongfu
• Is Part Of: Advanced materials. Volume 31:Issue 51(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-17
• Subjects: inverse design -- nanophotonics -- neural networks -- structural color; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.201970364
• Languages: English
• ISSNs: 0935-9648

Abstract

Abstract : In article number 1905467, to avoid time‐consuming electromagnetic simulation and an iterative optimization process, Li Gao, Zongfu Yu, and co‐workers report the training of a deep neural network that can perform both forward modeling and inverse design of one million different structural colors. The adoption of a tandem network can solve the nonuniqueness problem in the inverse design process with high efficiency and accuracy.