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Polymers
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Innovations in Polymer Composites for Sustainability and Multifunctionality
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Innovations in Polymer Composites for Sustainability and Multifunctionality

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Composites and Nanocomposites".

Deadline for manuscript submissions: 25 August 2025 | Viewed by 2033

Special Issue Editor

Dr. Yeqing Wang

E-Mail Website
Guest Editor
Department of Mechanical & Aerospace Engineering, Syracuse University, Syracuse, NY 13244, USA
Interests: mechanics of composite materials and structures; advanced manufacturing of composites; multifunctional composites

Special Issue Information

Dear Colleagues,

Polymer composites convey substantial advantages to a variety of applications due to their significant weight-saving benefits and ability to be tailored to achieve structural and multifunctional performance. These materials are increasingly employed in the aerospace, automotive, biomedical, marine, and many other industries. Two of the current challenges in polymer composites are sustainability and multifunctionality.

This Special Issue aims to present recent advances in polymer composites for sustainability and multifunctionality. The scope of this Special Issue includes the following:

  • Recyclability of polymer composites;
  • Using recycled components for polymer composites;
  • Decarbonization in the manufacturing process of polymer composites;
  • Innovations in the structure and properties of polymer composites towards multifunctionality (e.g., structural, heat dissipation, thermal protection, biomedical applications).

We welcome research contributions related to the above topics, including experimental studies, analysis, simulations, and reviews.

Dr. Yeqing Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • polymer composites
  • recyclability
  • biodegradable
  • decarbonization
  • multifunctionality

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

15 pages, 945 KiB  
Article
Incorporating Non-Linear Epoxy Resin Development in Infusion Simulations: A Dual-Exponent Viscosity Model Approach
by Mohammad W. Tahir, Umar Khan and Jan-Peter Schümann
Polymers 2025, 17(5), 657; https://doi.org/10.3390/polym17050657 - 28 Feb 2025
Viewed by 522
Abstract
In the field of liquid composite moulding (LCM) simulations, a long-standing assumption has dominated–the belief in constant resin viscosity. While effective in many cases, this assumption may not hold for the infusion process, which lasts for an extended period. This impacts the mechanical [...] Read more.
In the field of liquid composite moulding (LCM) simulations, a long-standing assumption has dominated–the belief in constant resin viscosity. While effective in many cases, this assumption may not hold for the infusion process, which lasts for an extended period. This impacts the mechanical properties of the cured epoxy, which are crucial for load transfer in polymer structures. The majority of epoxy resins operate on a bipartite foundation, wherein their viscosity undergoes dynamic alterations during the process of cross-linking. Temperature and cross-linking intricately interact, with elevated temperatures initially reducing viscosity due to kinetic energy but later increasing it as cross-linking accelerates. This interplay significantly influences the efficiency of the infusion process, especially in large and intricate moulds. This article explores the significant temperature dependence of epoxy resin viscosity, proposing an accurate model rooted in its non-linear evolution. This model aligns with empirical evidence, offering insights into determining the optimal starting temperature for efficient mould filling. This study presents an advanced infusion model that extends existing non-linear dual-split viscosity approaches by incorporating the experimental validation of viscosity variations. Unlike previous models that primarily focus on theoretical or numerical frameworks, this work integrates experimental insights to optimize infusion temperature for efficient resin infusion in large and complex parts. Building on these findings, a novel mould-filling technique is proposed to enhance efficiency and reduce material waste. Full article
(This article belongs to the Special Issue Innovations in Polymer Composites for Sustainability and Multifunctionality)
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27 pages, 13997 KiB  
Article
Identification of Lighting Strike Damage and Prediction of Residual Strength of Carbon Fiber-Reinforced Polymer Laminates Using a Machine Learning Approach
by Rui-Zi Dong, Yin Fan, Jiapeng Bian and Zhili Chen
Polymers 2025, 17(2), 180; https://doi.org/10.3390/polym17020180 - 13 Jan 2025
Cited by 1 | Viewed by 1070
Abstract
Due to the complex and uncertain physics of lightning strike on carbon fiber-reinforced polymer (CFRP) laminates, conventional numerical simulation methods for assessing the residual strength of lightning-damaged CFRP laminates are highly time-consuming and far from pretty. To overcome these challenges, this study proposes [...] Read more.
Due to the complex and uncertain physics of lightning strike on carbon fiber-reinforced polymer (CFRP) laminates, conventional numerical simulation methods for assessing the residual strength of lightning-damaged CFRP laminates are highly time-consuming and far from pretty. To overcome these challenges, this study proposes a new prediction method for the residual strength of CFRP laminates based on machine learning. A diverse dataset is acquired and augmented from photographs of lightning strike damage areas, C-scan images, mechanical performance data, layup details, and lightning current parameters. Original lightning strike images, preprocessed with the Sobel operator for edge enhancement, are fed into a UNet neural network using four channels to detect damaged areas. These identified areas, along with lightning parameters and layup details, are inputs for a neural network predicting the damage depth in CFRP laminates. Due to its close relation to residual strength, damage depth is then used to estimate the residual strength of lightning-damaged CFRP laminates. The effectiveness of the current method is confirmed, with the mean Intersection over Union (mIoU) achieving over 93% for damage identification, the Mean Absolute Error (MAE) reducing to 5.4% for damage depth prediction, and the Mean Relative Error (MRE) reducing to 7.6% for residual strength prediction, respectively. Full article
(This article belongs to the Special Issue Innovations in Polymer Composites for Sustainability and Multifunctionality)
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