南京理工大学学报（自然科学版）2024，Vol.48Issue(4)：489-495,7.DOI:10.14177/j.cnki.32-1397n.2024.48.04.010
基于深度学习的纳米粒子阵列电场预测
Prediction of electric field of nanoparticle array based on deep learning method
摘要
Abstract
The calculation of the electric fields of nanoparticle arrays metasurface require a lot of time and computing power.To achieve the fast calculation of the electric field of nanoparticle arrays,with the help of the deep learning method,this study proposes a mapping deep neural network from low-precision electric field to high-precision electric field.This neural network can predict the electric field with high-precision according to the electric field with low-precision.The mean square error is 5.6×10-3 and the mean norm relative error is 1.5%.The numerical results confirm that the model can fast and accurately predict the electric field on the surface of a nanoparticle array.Compared with the existing research results,the error of this model is lower by an order of magnitude.This work helps to solve the problem of fast design of nanoparticle arrays with surface enhancement of Raman scattering.关键词
超表面/表面增强拉曼散射/深度学习/纳米粒子阵列Key words
metasurface/surface enhancement of Raman scattering/deep learning/nanoparticle array分类
信息技术与安全科学引用本文复制引用
胡燕萌,马子轩,李猛猛..基于深度学习的纳米粒子阵列电场预测[J].南京理工大学学报（自然科学版）,2024,48(4):489-495,7.基金项目
国家自然科学基金(62222108 （）
61871222) （）
中央高校基本科研业务费专项资金(30921011101) （30921011101）
