Cargando…

Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites

Carbon nanomaterials have gradually demonstrated their superiority for in-line process monitoring of high-performance composites. To explore the advantages of structures, properties, as well as sensing mechanisms, three types of carbon nanomaterials-based fiber sensors, namely, carbon nanotube-coate...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Guantao, Wang, Yong, Luo, Yun, Luo, Sida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163923/
https://www.ncbi.nlm.nih.gov/pubmed/30208571
http://dx.doi.org/10.3390/ma11091677
_version_ 1783359477691449344
author Wang, Guantao
Wang, Yong
Luo, Yun
Luo, Sida
author_facet Wang, Guantao
Wang, Yong
Luo, Yun
Luo, Sida
author_sort Wang, Guantao
collection PubMed
description Carbon nanomaterials have gradually demonstrated their superiority for in-line process monitoring of high-performance composites. To explore the advantages of structures, properties, as well as sensing mechanisms, three types of carbon nanomaterials-based fiber sensors, namely, carbon nanotube-coated fibers, reduced graphene oxide-coated fibers, and carbon fibers, were produced and used as key sensing elements embedded in fabrics for monitoring the manufacturing process of fiber-reinforced polymeric composites. Detailed microstructural characterizations were performed through SEM and Raman analyses. The resistance change of the smart fabric was monitored in the real-time process of composite manufacturing. By systematically analyzing the piezoresistive performance, a three-stage sensing behavior has been achieved for registering resin infiltration, gelation, cross-linking, and post-curing. In the first stage, the incorporation of resin expands the packing structure of various sensing media and introduces different levels of increases in the resistance. In the second stage, the concomitant resin shrinkage dominates the resistance attenuation after reaching the maximum level. In the last stage, the diminished shrinkage effect competes with the disruption of the conducting network, resulting in continuous rising or depressing of the resistance.
format Online
Article
Text
id pubmed-6163923
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-61639232018-10-12 Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites Wang, Guantao Wang, Yong Luo, Yun Luo, Sida Materials (Basel) Article Carbon nanomaterials have gradually demonstrated their superiority for in-line process monitoring of high-performance composites. To explore the advantages of structures, properties, as well as sensing mechanisms, three types of carbon nanomaterials-based fiber sensors, namely, carbon nanotube-coated fibers, reduced graphene oxide-coated fibers, and carbon fibers, were produced and used as key sensing elements embedded in fabrics for monitoring the manufacturing process of fiber-reinforced polymeric composites. Detailed microstructural characterizations were performed through SEM and Raman analyses. The resistance change of the smart fabric was monitored in the real-time process of composite manufacturing. By systematically analyzing the piezoresistive performance, a three-stage sensing behavior has been achieved for registering resin infiltration, gelation, cross-linking, and post-curing. In the first stage, the incorporation of resin expands the packing structure of various sensing media and introduces different levels of increases in the resistance. In the second stage, the concomitant resin shrinkage dominates the resistance attenuation after reaching the maximum level. In the last stage, the diminished shrinkage effect competes with the disruption of the conducting network, resulting in continuous rising or depressing of the resistance. MDPI 2018-09-11 /pmc/articles/PMC6163923/ /pubmed/30208571 http://dx.doi.org/10.3390/ma11091677 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Guantao
Wang, Yong
Luo, Yun
Luo, Sida
Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title_full Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title_fullStr Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title_full_unstemmed Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title_short Carbon Nanomaterials Based Smart Fabrics with Selectable Characteristics for In-Line Monitoring of High-Performance Composites
title_sort carbon nanomaterials based smart fabrics with selectable characteristics for in-line monitoring of high-performance composites
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163923/
https://www.ncbi.nlm.nih.gov/pubmed/30208571
http://dx.doi.org/10.3390/ma11091677
work_keys_str_mv AT wangguantao carbonnanomaterialsbasedsmartfabricswithselectablecharacteristicsforinlinemonitoringofhighperformancecomposites
AT wangyong carbonnanomaterialsbasedsmartfabricswithselectablecharacteristicsforinlinemonitoringofhighperformancecomposites
AT luoyun carbonnanomaterialsbasedsmartfabricswithselectablecharacteristicsforinlinemonitoringofhighperformancecomposites
AT luosida carbonnanomaterialsbasedsmartfabricswithselectablecharacteristicsforinlinemonitoringofhighperformancecomposites