Discovery of New Plasmonic Metals via High‐Throughput Machine Learning-Reference-Cited by-同舟云学术

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Discovery of New Plasmonic Metals via High‐Throughput Machine Learning

Published:2022-08-04 Issue:18 Volume:10 Page:2200158
ISSN:2195-1071
Container-title:Advanced Optical Materials
language:en
Short-container-title:Advanced Optical Materials

Author:

Shapera Ethan P.¹^ORCID,Schleife André²³⁴^ORCID

Affiliation:

1. Department of Physics University of Illinois at Urbana–Champaign Urbana IL 61801 USA

2. Department of Materials Science and Engineering University of Illinois at Urbana–Champaign Urbana IL 61801 USA

3. Materials Research Laboratory University of Illinois at Urbana–Champaign Urbana IL 61801 USA

4. National Center for Supercomputing Applications University of Illinois at Urbana–Champaign Urbana IL 61801 USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adom.202200158

Reference90 articles.

1. Optical properties of intermetallic compounds from first principles calculations: a search for the ideal plasmonic material

2. Optical Properties of Solids

3. Local detection of electromagnetic energy transport below the diffraction limit in metal nanoparticle plasmon waveguides

4. Plasmonics: Localization and guiding of electromagnetic energy in metal/dielectric structures

5. Gap-Dependent Optical Coupling of Single “Bowtie” Nanoantennas Resonant in the Visible

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1. Prediction of Frequency-Dependent Optical Spectrum for Solid Materials: A Multioutput and Multifidelity Machine Learning Approach;ACS Applied Materials & Interfaces;2024-07-24

2. Explainable predictions of multi-component oxides enabled by attention-based neural networks;Scripta Materialia;2024-02

3. Unraveling the relationships between heat-shielding properties and crystal structure using first-principles calculations;Computational Materials Science;2023-10

4. High-throughput screening of heat-shielding carrier-doped semiconductor materials via first principles calculations;Japanese Journal of Applied Physics;2023-06-01

5. Discovery of New Plasmonic Metals via High‐Throughput Machine Learning;Advanced Optical Materials;2022-08-04

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