Machine-learning-driven accelerated design-method for meta-devices-Reference-Cited by-同舟云学术

Machine-learning-driven accelerated design-method for meta-devices

Published:2023-12 Issue: Volume:37 Page:106951
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Ijaz Sumbel^ORCID,Noureen Sadia,Rehman Bacha^ORCID,Aldaghri Osamah,Cabrera Humberto^ORCID,Ibnaouf Khalid H.,Madkhali Nawal,Mehmood Muhammad Qasim^ORCID

Funder

Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University

Publisher

Elsevier BV

Subject

Materials Chemistry,Mechanics of Materials,General Materials Science

Reference61 articles.

1. Principles of electromagnetic waves in metasurfaces;Luo;Sci. China Phys., Mech. Astron.,2015

2. Exploiting zirconium nitride for an efficient heat-resistant absorber and emitter pair for solar thermophotovoltaic systems;Ijaz;Opt. Express,2021

3. Revisiting tantalum based nanostructures for efficient harvesting of solar radiation in STPV systems;Rana;Nano Energy,2021

4. Broadband chiro-optical effects for futuristic meta-holographic displays;Khaliq;Adv. Opt. Mater.,2022

5. The dawn of metadevices: from contemporary designs to exotic applications;Ijaz;Adv. Devices Instrum.,2022

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