From conductivity collapse to rational design of thermally conductive fibers: a review

Thermally conductive fibers combine axial heat transport with mechanical flexibility, making them indispensable for thermal management across applications from AI hardware to hypersonic vehicles. However, macroscopic fibers assembled from high-thermal conductivity ( κ ) nanomaterials retain only a small fraction of their intrinsic conductivity, with transfer efficiencies ranging from below 2.3% to approximately 42.5% across different fiber systems. This review establishes phonon pathway continuity as a unifying principle connecting transport fundamentals, fiber structural design, and application requirements. Transfer efficiency ( η = κ macro / κ theoretical ) is introduced as a reference-dependent metric to quantify thermal-conductivity retention from high-conductivity reference structures to experimentally realized fibers, revealing system-specific bottlenecks including inter-tube junction resistance in CNT fibers, inter-sheet misorientation in graphene fibers, and chain disorder in polymer fibers. Phonon spectrum matching outperforms covalent functionalization for high- κ fillers, while application categories are mapped to optimal fiber systems through quantitative structure-performance analysis. Finally, this review outlines a research roadmap spanning AI-driven interface design, cross-scale phonon pathway construction, and bioinspired adaptive thermal management fibers. These concepts point toward a paradigm shift from empirical material selection to rational inverse design.