Acquiring structural and mechanical information of a fibrous network through deep learning-Reference-Cited by-同舟云学术

Acquiring structural and mechanical information of a fibrous network through deep learning

Published:2022 Issue:13 Volume:14 Page:5044-5053
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Yang Shuo¹,Zhao Chenxi¹,Ren Jing¹,Zheng Ke²,Shao Zhengzhong³^ORCID,Ling Shengjie¹^ORCID

Affiliation:

1. School of Physical Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai, 201210, China

2. Biomass Molecular Engineering Center and Department of Materials Science and Engineering, School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei, Anhui 230036, China

3. State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Laboratory of Advanced Materials, Fudan University, Shanghai 200433, China

Abstract

A fibrous network-deep learning system (FN-DLS) was developed to extract fibrous network structure information from noisy atomic force microscopy images. FN-DLS can accurately assess the structural and mechanical characteristics of fibrous networks.

Funder

National Natural Science Foundation of China

ShanghaiTech University

State Key Laboratory for Modification of Chemical Fibers and Polymer Materials

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2022/NR/D2NR00372D

Reference48 articles.

1. Nanofibrils in nature and materials engineering