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Enhanced carbon fiber interface with thermoplastics via nanostructure surface modification: Failure, morphology and wettability analysis.

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Title: Enhanced carbon fiber interface with thermoplastics via nanostructure surface modification: Failure, morphology and wettability analysis.
Authors: Fang, Weiqing1 (AUTHOR), Pearson, Adam1 (AUTHOR), Huang, Yige1 (AUTHOR), Naguib, Hani E.1 (AUTHOR)
Source: Composites: Part B, Engineering. Feb2025, Vol. 291, pN.PAG-N.PAG. 1p.
Subjects: Convolutional neural networks, Thermoplastic composites, X-ray photoelectron spectroscopy, Hybrid materials, High density polyethylene, Carbon fibers
Abstract: Improving the fiber-matrix adhesion in thermoplastic composites remains a significant challenge due to the lack of chemical bonding between thermoplastics and common reinforcing fibers. This study investigates the effectiveness of carbon fibers enhanced with nanostructure surface modification for strengthening the interfacial adhesion to thermoplastic matrices. The fiber surface was modified with graphene nanoplatelets (GNP) through a facile coating method, and the apparent interfacial shear strength (IFSS) was determined by single-fiber pullout tests. GNP-coated fiber improved IFSS by 74 % with neat high-density polyethylene (HDPE-Neat) and 28 % with maleic anhydride-grafted HDPE (HDPE-8MA), while IFSS reduced by 27 % with polyamide 6 (PA6) due to different failure mechanisms. Morphology, chemical, and wettability analysis were conducted on the nano-enhanced carbon fibers to quantitatively elucidate these findings on micro/nanoscale, combining machine learning-based image segmentation, X-ray photoelectron spectroscopy (XPS), and contact-angle measurements of intermittent beading on fibers. [Display omitted] • Evaluated interfacial shear strength of nano-enhanced carbon fiber within thermoplastic using single fiber pullout test. • Revealed failure mechanisms and effects of nano-coating on carbon fiber in various thermoplastic matrices. • Applied convolutional neural network technique to quantify the nano-enhanced surface morphology. • Quantified the wettability of thermoplastic to fibers using fiber beading method. [ABSTRACT FROM AUTHOR]
Copyright of Composites: Part B, Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 182072944
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PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Enhanced carbon fiber interface with thermoplastics via nanostructure surface modification: Failure, morphology and wettability analysis.
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  Data: <searchLink fieldCode="JN" term="%22Composites%3A+Part+B%2C+Engineering%22">Composites: Part B, Engineering</searchLink>. Feb2025, Vol. 291, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Convolutional+neural+networks%22">Convolutional neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Thermoplastic+composites%22">Thermoplastic composites</searchLink><br /><searchLink fieldCode="DE" term="%22X-ray+photoelectron+spectroscopy%22">X-ray photoelectron spectroscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+materials%22">Hybrid materials</searchLink><br /><searchLink fieldCode="DE" term="%22High+density+polyethylene%22">High density polyethylene</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+fibers%22">Carbon fibers</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Improving the fiber-matrix adhesion in thermoplastic composites remains a significant challenge due to the lack of chemical bonding between thermoplastics and common reinforcing fibers. This study investigates the effectiveness of carbon fibers enhanced with nanostructure surface modification for strengthening the interfacial adhesion to thermoplastic matrices. The fiber surface was modified with graphene nanoplatelets (GNP) through a facile coating method, and the apparent interfacial shear strength (IFSS) was determined by single-fiber pullout tests. GNP-coated fiber improved IFSS by 74 % with neat high-density polyethylene (HDPE-Neat) and 28 % with maleic anhydride-grafted HDPE (HDPE-8MA), while IFSS reduced by 27 % with polyamide 6 (PA6) due to different failure mechanisms. Morphology, chemical, and wettability analysis were conducted on the nano-enhanced carbon fibers to quantitatively elucidate these findings on micro/nanoscale, combining machine learning-based image segmentation, X-ray photoelectron spectroscopy (XPS), and contact-angle measurements of intermittent beading on fibers. [Display omitted] • Evaluated interfacial shear strength of nano-enhanced carbon fiber within thermoplastic using single fiber pullout test. • Revealed failure mechanisms and effects of nano-coating on carbon fiber in various thermoplastic matrices. • Applied convolutional neural network technique to quantify the nano-enhanced surface morphology. • Quantified the wettability of thermoplastic to fibers using fiber beading method. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Composites: Part B, Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.compositesb.2024.112054
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      – Code: eng
        Text: English
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      – SubjectFull: Convolutional neural networks
        Type: general
      – SubjectFull: Thermoplastic composites
        Type: general
      – SubjectFull: X-ray photoelectron spectroscopy
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      – SubjectFull: Hybrid materials
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      – SubjectFull: High density polyethylene
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      – SubjectFull: Carbon fibers
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      – TitleFull: Enhanced carbon fiber interface with thermoplastics via nanostructure surface modification: Failure, morphology and wettability analysis.
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            NameFull: Fang, Weiqing
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            NameFull: Pearson, Adam
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            NameFull: Huang, Yige
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              M: 02
              Text: Feb2025
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              Y: 2025
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