Wide-angle deep ultraviolet antireflective multilayers via discrete-to-continuous optimization.

ABSTRACT: To date, various optimization algorithms have been used to design non-intuitive photonic structures with unconventional optical performance. Good training datasets facilitate the optimization process, particularly when an objective function has a non-convex shape containing multiple local optima in a continuous parametric space. Herein, we developed a discrete-to-continuous optimization algorithm and confirmed its validity by designing and fabricating deep-ultraviolet antireflective MgF₂/LaF₃ multilayers. For discrete optimization, a multilayer was encoded into a binary vector with multiple bits; a 10 nm thick MgF₂ or LaF₃ layer was assigned a binary digit of 0 or 1, respectively. Using the binary-based training datasets, a factorization machine

SUBMITTER: Kim JH 

PROVIDER: S-EPMC11501509 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature