Optimization of Core–Shell Nanoparticles Using a Combination of Machine Learning and Ising Machine

Machine‐learning‐based optimization techniques are widely used for designing complex materials. However, an efficient search for the complex systems, where a combinatorial explosion occurs in the materials search space, is still challenging. Core–shell nanoparticles (CSNPs) are an example of a complex system with a high degree of freedom owing to their complicated structure and multiple constituent materials. In this study, a new black box optimization technique is developed. In this method, the structure of the CSNPs is optimized using an Ising machine and their constituent materials are selected using Bayesian optimization with the optical properties of the materials as the “descriptors”. Aiming for applications to i‐line photolithography, the authors search for CSNPs that are transparent to ultraviolet light of wavelength 355–375 nm and opaque to visible light of wavelength 400–830 nm. The transmittance spectra of the nanoparticles are obtained using a Mie theory calculator. The proposed nanoparticles with the best optical properties have a multilayered structure with a radius of approximately 40 nm and an outer shell composed of either Mg or Pb. The results indicate that a combination of various optimization techniques is more efficient in discovering the better complex materials.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Optimization of Core–Shell Nanoparticles Using a Combination of Machine Learning and Ising Machine ; day:03 ; month:10 ; year:2023 ; extent:11
Advanced photonics research ; (03.10.2023) (gesamt 11)

Creator
Urushihara, Makoto
Karube, Masaya
Yamaguchi, Kenji
Tamura, Ryo

DOI
10.1002/adpr.202300226
URN
urn:nbn:de:101:1-2023100415015971600681
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 11:00 AM CEST

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Associated

  • Urushihara, Makoto
  • Karube, Masaya
  • Yamaguchi, Kenji
  • Tamura, Ryo

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