Interaction Mechanism of Graphene Oxide and Polyacrylonitrile During Pre‐Oxidation: Insights Into Structural Evolution and Thermal Behavior

Fecha de publicación: --
Fuente: Journal of applied polymer
Lugar: RESEARCH ARTICLE
Schematic illustration of the dual synergistic regulation mechanism of GO during PAN fiber pre-oxidation. Unmodified PAN suffers from disordered cyclization, localized overheating, and skin-core heterogeneity. Upon thermal treatment, GO undergoes deoxygenation to release ˙OH radicals that suppress random chain propagation, while its restored sp2-conjugated skeleton templates ordered PAN ladder structures via π-π interactions. The regulatory behavior of GO differs markedly between nitrogen and air atmospheres. At a low GO loading of 1.0 wt%, the most ordered carbon structure is obtained, as evidenced by an ID/IG ratio of 0.88; at 7.5 wt% GO, a maximum carbonization yield of 74.82% is achieved at 800°C.

ABSTRACT
Polyacrylonitrile (PAN)-based carbon fibers suffer from defects and skin-core heterogeneity due to thermal runaway and uneven oxygen diffusion during pre-oxidation. Graphene oxide (GO) shows promise as a modifier, yet its interaction mechanism with PAN, particularly the distinct roles of oxygen-containing groups and sp2-conjugated skeleton remains unclear. Herein, GO/PAN composite fibers (0.1–7.5 wt% GO) were prepared via wet spinning and characterized by DSC, TG, FTIR, XPS, and Raman spectroscopy. Results reveal a dual, atmosphere and content-dependent regulation. It is inferred that ˙OH radicals generated from GO deoxygenation may scavenge cyclization intermediates to suppress disorder, while the restored sp2 skeleton templates ordered structures via π–π interactions. Under nitrogen, radical scavenging and templating enhance reaction uniformity; under air, GO promotes oxidative crosslinking and moderates oxygen diffusion, mitigating skin-core formation. Notably, GO1.0-PAN exhibits the lowest ID/IG (0.88), and GO7.5-PAN achieves 74.82% carbonization yield. This work establishes quantitative structure–property correlations for optimizing high-performance CFs.