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Published in: Optical and Quantum Electronics 1/2024

01-01-2024

AI-driven electro chromic materials and devices for nanofabrication in machine learning integrated environments

Authors: K. Mahesh Prasanna, Aasheesh Shukla, K. Tamizharasu, Amit Ganatra, Atmaram Shelke, Ahmed Sayed M. Metwally, Sikandar Aftab

Published in: Optical and Quantum Electronics | Issue 1/2024

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Abstract

This study looks into the introduction of AI-driven electrochromic materials and devices into nanofabrication methods for use in ML-integrated environments. When exposed to an electric field, electrochromic materials experience reversible changes in optical properties due to dynamic optical modulation. Because of developments in AI-assisted design, optimization, and fabrication, advanced electrochromic devices with improved performance are now conceivable. The incorporation of AI-optimized electrochromic materials into nanofabrication operations and their application in ML-integrated systems are described, as well as their synthesis and characterization. Several test datasets revealed that the AI-driven strategy improved OME, Response Times, CE, and EE. These findings validate the importance of applying AI algorithms to guide material design, optimize production, and enable real-time adaptation for greater optical modulation and energy efficiency.

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Metadata
Title
AI-driven electro chromic materials and devices for nanofabrication in machine learning integrated environments
Authors
K. Mahesh Prasanna
Aasheesh Shukla
K. Tamizharasu
Amit Ganatra
Atmaram Shelke
Ahmed Sayed M. Metwally
Sikandar Aftab
Publication date
01-01-2024
Publisher
Springer US
Published in
Optical and Quantum Electronics / Issue 1/2024
Print ISSN: 0306-8919
Electronic ISSN: 1572-817X
DOI
https://doi.org/10.1007/s11082-023-05656-1

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