journal article·2024-02

Advanced Aramid Fibrous Materials: Fundamentals, Advances, and Beyond

Annan He, Tonghe Xing, Zihui Liang, Yuxin Luo, Yu Zhang, Mengqi Wang, Zhiyu Huang, Jie Bai, Liuyan Wu, Zhicheng Shi, Hongmei Zuo, Wenshuo Zhang, Fengxiang Chen, Weilin Xu

Advanced Fiber Materials· Volume 6· Issue 1
Publisher page

Abstract

Aramid fibers (AFs) are widely applied in many cutting-edge fields, due to their excellent comprehensive performance. Ongoing research efforts are therefore underway to expand the applicability by designing more environmentally friendly and low-cost synthesis methods, incorporating new chemical components in the skeletons or internal structures of polyamide to enhance their processability and functionality. Despite being at the forefront of scientific research, there are fewer reviews that comprehensively summarize the latest progress of AFs. This review focuses on the fundamental research of AFs since their inception and summarizes the advanced progress and applications of AFs. Firstly, the synthesis mechanism and methods of AFs and their structure–property relationship are comprehensively discussed. Subsequently, we review the recent progress in surface functionalization of AFs by using advanced micro-nanoscale modification strategies to enhance the interface properties and ultraviolet (UV)-resistance properties, and summarize the advantages and disadvantages of various modified methods. Then, applications of AF and aramid nanofiber (ANF) in various fields are discussed. Finally, the possible challenges and outlooks toward the future development of AFs are highlighted, which is expected to provide new insights for the next-generation advanced functional AF materials and facilitate the industrialization development level for high-performance AFs and their composites.
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Research context

OpenAlex topics: Fiber-reinforced polymer composites · Advanced Sensor and Energy Harvesting Materials · Supercapacitor Materials and Fabrication

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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