Synergy in bio-inspired hybrid composites with hierarchically structured fibrous reinforcements Article Swipe
Nello D. Sansone
,
Jiyoung Jung
,
Peter Serles
,
Rafaela Aguiar
,
Zahir Razzaz
,
Matthew Leroux
,
Tobin Filleter
,
Seunghwa Ryu
,
Patrick Lee
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.cej.2024.150357
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.cej.2024.150357
In response to the global energy crisis, high-performance transportation sectors are rapidly embracing lightweight materials to enhance energy efficiency and sustainability, while grappling with the persistent challenges of developing structural materials that meet stringent safety standards with robust mechanical performance and ease of scalability. Thus, this work presents a combined experimental and theoretical framework to develop a profound understanding of the synergistic effect in hybrid composites with bio-inspired fibrous reinforcements, by elucidating the interfacial interactions across multiple length-scales, encompassing atomic covalent bonding to micro-morphology. A model hybrid composite system, containing a self-assembled fibrous reinforcement consisting of nano-sized Graphene Nanoplatelets (GnP) covalently bonded onto chemically-modified micro-sized Glass Fibers (GF), was utilized to showcase the synergistic effect and highlight its associated mechanisms. The interfacial interactions of the reinforcement were optimized by obtaining the maximum density of covalent bonds, which was achieved with 0.5 wt% GnP for the hybrid composites containing 10 wt% GF, increasing the work of adhesion by 33 %, compared to the biphasic GF composites. The composite's morphology contains minimal agglomeration with ∼68 % of GnPs oriented with the melt flow, supressing high-stress concentration areas, while the formed crystalline microstructure, with ∼18 % β-crystals, allows the matrix to absorb substantial energy. Furthermore, the increased trans-crystallization encapsulating the hierarchical reinforcement induced nanoscale stiffness variations, increasing rigidity, and forming an ∼16 µm gradient interphase that facilitates load transfer. The greatest synergistic effect observed was ∼54 %, ∼37 %, and ∼75 % for the tensile modulus, tensile strength, and impact strength, respectively. Additionally, a theoretical framework accounting for the synergistic effect was formulated, using a two-step core/shell homogenization model, which shows great potential in expediting the design and optimization of innovative hybrid composite materials.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.cej.2024.150357
- OA Status
- hybrid
- Cited By
- 14
- References
- 83
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393349107
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393349107Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.cej.2024.150357Digital Object Identifier
- Title
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Synergy in bio-inspired hybrid composites with hierarchically structured fibrous reinforcementsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-03-23Full publication date if available
- Authors
-
Nello D. Sansone, Jiyoung Jung, Peter Serles, Rafaela Aguiar, Zahir Razzaz, Matthew Leroux, Tobin Filleter, Seunghwa Ryu, Patrick LeeList of authors in order
- Landing page
-
https://doi.org/10.1016/j.cej.2024.150357Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.cej.2024.150357Direct OA link when available
- Concepts
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Materials science, Composite material, Ultimate tensile strength, Composite number, Interphase, Microstructure, Stiffness, Reinforcement, Nanoscopic scale, Covalent bond, Graphene, Nanotechnology, Chemistry, Organic chemistry, Genetics, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 9, 2024: 5Per-year citation counts (last 5 years)
- References (count)
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83Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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