Inverse Engineering of Absorption and Scattering in Nanoparticles: A Machine Learning Approach

被引：0

作者：

Vallone, Alex ^{[1
]}

Estakhri, Nooshin M. ^{[2
]}

Estakhri, Nasim Mohammadi ^{[1
]}

机构：

[1] Chapman Univ, Fowler Sch Engn, Orange, CA 92866 USA

[2] Virginia Tech, Dept Phys, Blacksburg, VA 24061 USA

来源：

2023 IEEE PHOTONICS CONFERENCE, IPC | 2023年

基金：

美国国家科学基金会;

关键词：

convolutional neural networks; scattering and absorption; nanoparticles; inverse design; machine learning;

D O I：

10.1109/IPC57732.2023.10360618

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We use a region-specified machine learning approach to inverse design highly absorptive multilayer plasmonic nanoparticles. We demonstrate the design of particles with a wide range of absorption to scattering ratios (i.e., cloaked absorbers and bright absorbers) and for different visible wavelengths.

引用

页数：2

共 6 条

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Liu, Zhaocheng
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Vallone, Alex
Estakhri, Nooshin M.
Estakhri, Nasim Mohammadi
[J]. JOURNAL OF PHYSICS-PHOTONICS, 2023, 5 (02):

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