Presentation + Paper
20 August 2020 Machine learning for the design of nanomaterials
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Abstract
In this article we review some machine learning methods for the design of nanomaterials. The first part will discuss how to use neural network to build a predictive model of the optical properties of a certain material or structure. The second part is dedicated to the optimization and reverse engineering of an optical material using generative networks.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
André-Pierre Blanchard-Dionne and Olivier J. F. Martin "Machine learning for the design of nanomaterials", Proc. SPIE 11462, Plasmonics: Design, Materials, Fabrication, Characterization, and Applications XVIII, 114621C (20 August 2020); https://doi.org/10.1117/12.2568471
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KEYWORDS
Oscillators

Reverse modeling

Convolution

Machine learning

Nanomaterials

Neural networks

Reverse engineering

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