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.

中文翻译：

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通过耦合多尺度建模和实验开发具有成本效益的碳纤维的进展：批判性评论


近几十年来，碳纤维（CF）因其优异的机械性能、低密度和出色的化学/热稳定性而受到广泛关注。然而，由于成本较高，CF 的使用仍然仅限于高端应用。通过探索替代前驱体、开发纺丝方法和优化加工条件，人们付出了巨大的努力来制造具有成本效益的CF。然而，选择具有匹配实验程序的成功前体仍然具有挑战性。作为实验的替代方案，我们可以利用多尺度水平的预测模型来理解和预测 CF 的行为和属性，以所需的精度，同时显着降低成本。随后可以将建模工作与实验研究相结合。本综述旨在对通过各种前体并通过计算预测降低 CF 制备总体成本的努力提供全面和批判性的概述。首先，它简要描述了 CF 的进展和挑战，然后研究了可能影响其性能的不同前体。然后，详细讨论了实现低成本 CF 的实验和计算研究的最新进展。最后，总结了当前的成就、未来的挑战以及获得具有成本效益的 CF 的可能解决方案。