We proposed an optical film optimal algorithm using a three-step machine learning algorithm. which applies to design layered thin-film materials. As a verification, the absorption of the designed solar selective absorption film is 91%.

© 2020 The Author(s)

PDF Article
More Like This
OTF Gym: A Set of Reinforcement Learning Environment of Layered Optical Thin Film Inverse Design

Anqing Jiang, Liangyao Chen, and Osamu Yoshie
SM1Q.7 CLEO: Science and Innovations (CLEO_SI) 2021

Deep Reinforcement Learning Enabled Network Routing Optimization Approach with an Enhanced DDPG Algorithm

Lingyu Meng, Wen Yang, Bingli Guo, and Shanguo Huang
M4A.206 Asia Communications and Photonics Conference (ACPC) 2020

Applications of a Genetic and Simplex Algorithm based Hybrid Algorithm in Optical Film Design and Optimization

Yonggang Wu, Donggong Peng, Hongfei Jiao, Zhenhua Wang, Hong Cao, and Li Zhang
WB7 Optical Interference Coatings (OIC) 2007


You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
Login to access Optica Member Subscription

Poster Presentation

Media 1: PDF (2105 KB)