Advances in developing cost-effective carbon fibers by coupling multiscale modeling and experiments: A critical review

Jiadeng Zhu, Zan Gao, Qian Mao, Yawei Gao, Ya Li, Xin Zhang, Qiang Gao, Mengjin Jiang, Sungho Lee, Adri C.T. van Duin

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Carbon fibers (CFs) have received remarkable attention in recent decades because of their excellent mechanical properties, low density, and outstanding chemical/thermal stability. However, due to their high cost, the usage of CFs is still limited to high-end applications. Tremendous efforts have been made to fabricate cost-effective CFs by exploring alternative precursors, developing spinning methods, and optimizing processing conditions. Nevertheless, selecting a successful precursor with a matching experimental procedure is still challenging. As an alternative to the experiment, we can utilize predictive modeling at multiscale levels to understand and predict CFs’ behaviors and properties with desired accuracy yet at a significantly reduced cost. The modeling efforts can subsequently be integrated with experimental studies. This review aims to provide a comprehensive and critical overview of efforts to reduce the overall cost of CF preparation via various precursors and by including computational prediction. First, it briefly describes the progress and challenges of CFs, followed by investigating different precursors that may affect their properties. Then, state-of-the-art developments regarding experimental and computational studies for achieving low-cost CFs are discussed in detail. In the end, a summary of the current achievements and a future vision of challenges and possible solutions to obtain cost-effective CFs are given.

Original languageEnglish
Article number101329
JournalProgress in Materials Science
Volume146
DOIs
StatePublished - Dec 2024
Externally publishedYes

Keywords

  • Carbon fibers
  • Cost-effective
  • Experiment
  • Multiscale modeling
  • Spinning methods

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