Deep learning-assisted analysis of HRTEM images of crystalline nanoparticles-Reference-Cited by-同舟云学术

Deep learning-assisted analysis of HRTEM images of crystalline nanoparticles

Published:2023 Issue:35 Volume:15 Page:14496-14504
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Zhu Xiaoyang¹,Mao Yu²,Liu Jizi³,Chen Yi¹^ORCID,Chen Chuan¹,Li Yan¹^ORCID,Huang Xiao⁴^ORCID,Gu Ning¹³^ORCID

Affiliation:

1. Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, PR China

2. Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, PR China

3. Medical School, Nanjing University, Nanjing 210093, PR China

4. Key Laboratory of Flexible Electronics & Institute of Advanced Materials, Jiangsu National Synergistic Innovation Center for Advanced Materials, Nanjing Tech University (NanjingTech), Nanjing 211816, PR China

Abstract

An advanced analysis method is proposed for extracting crystal features from HRTEM images based on a 2D fast Fourier transform and U-Net based deep learning model.

Funder

Natural Science Foundation of Jiangsu Province

The Open Research Fund of Jiangsu Key Laboratory for Biomaterials and DevicesSoutheast University

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2023/NR/D3NR03061J

Reference28 articles.

1. A Universal Scripting Engine for Transmission Electron Microscopy

2. Crystallography: Some answers but more questions

3. Strain study of gold nanomaterials as HR-TEM calibration standard

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