Data-Enhanced Deep Greedy Optimization Algorithm for the On-Demand Inverse Design of TMDC-Cavity Heterojunctions

Data-Enhanced Deep Greedy Optimization Algorithm for the On-Demand Inverse Design of TMDC-Cavity Heterojunctions

A data-enhanced deep greedy optimization (DEDGO) algorithm is proposed to achieve the efficient and on-demand inverse design of multiple transition metal dichalcogenides (TMDC)-photonic cavity-integrated heterojunctions operating in the strong coupling regime. Precisely, five types of photonic cavit...

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Bibliographic Details
Main Authors: Zeyu Zhao, Jie You, Jun Zhang, Yuhua Tang
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Nanomaterials
Subjects:
inverse design
transition metal dichalcogenides
photonic cavity
integrated heterojunction
strong coupling effect
deep learning
Online Access:https://www.mdpi.com/2079-4991/12/17/2976

Internet

https://www.mdpi.com/2079-4991/12/17/2976

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