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Machine learning approach for predicting optical and photothermal properties of gold nanoparticle/polymer hybrid films:Effect of synthetic data

Yi Je Cho Harrison Chaney Kathy Lu

Nano Research2025，Vol.18Issue(3)：P.347-359,13.

Nano Research2025，Vol.18Issue(3)：P.347-359,13.DOI:10.26599/NR.2025.94907216

Machine learning approach for predicting optical and photothermal properties of gold nanoparticle/polymer hybrid films:Effect of synthetic data

Yi Je Cho ¹Harrison Chaney ²Kathy Lu³

作者信息

1. Department of Materials Science and Engineering,Virginia Polytechnic Institute and State University,Blacksburg,VA 24061,USA Department of Advanced Materials Science and Engineering,Sunchon National University,Suncheon-si,Jeollanam-do 57922,Republic of Korea
2. Department of Materials Science and Engineering,Virginia Polytechnic Institute and State University,Blacksburg,VA 24061,USA
3. Department of Materials Science and Engineering,Virginia Polytechnic Institute and State University,Blacksburg,VA 24061,USA Department of Mechanical and Materials Engineering,University of Alabama at Birmingham,Birmingham,AL 35294,USA
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摘要

关键词

machine learning/gold nanoparticle/polymer hybrid film/optical property/photothermal property/finite element modeling

分类

通用工业技术

引用本文复制引用

Yi Je Cho,Harrison Chaney,Kathy Lu..Machine learning approach for predicting optical and photothermal properties of gold nanoparticle/polymer hybrid films:Effect of synthetic data[J].Nano Research,2025,18(3):P.347-359,13.

基金项目

financial support from National Science Foundation under grant(No.CBET-2024546) （No.CBET-2024546）

the School of Engineering at University of Alabama at Birmingham. （）

Nano Research

ISSN：1998-0124

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