Statistical Optimization of Graphene Nanoplatelet-Reinforced Epoxy Nanocomposites via Box-Behnken Design for Superior Flexural and Dynamic Mechanical Performance

利用Box-Behnken设计对石墨烯纳米片增强环氧树脂纳米复合材料进行统计优化,以获得优异的弯曲和动态力学性能

阅读:1

Abstract

Graphene nanoplatelets (GNPs) are efficient nanofillers for improving the mechanical and thermal properties of epoxy resins due to their high stiffness, aspect ratio, and interfacial reinforcement ability. This study employs a three-factor, three-level Box-Behnken Design (BBD) to investigate the combined effect of GNP content (0.5-3.5 wt.%), hardener concentration (9-17 phr), and post-curing temperature (30-120 °C) on DGEBA/TETA epoxy nanocomposites. Mechanical, thermal, dynamic mechanical, and morphological characterizations (flexural testing, DMA, TGA, DSC, FTIR, SEM, TEM, and AFM) established structure-property correlations. The optimized formulation (2.0 wt.% GNP, 9 phr hardener, and 120 °C post-curing) exhibited superior reinforcement, with flexural strength of 322.0 ± 12.8 MPa, flexural modulus of 9.7 ± 0.5 GPa, and strain at break of 4.4 ± 0.2%, corresponding to increases of 197%, 155%, and 91% compared with neat epoxy. DMA confirmed a rise in storage modulus from 2.9 to 7.5 GPa and a Tg of 143 °C, while TGA showed a 15 °C improvement in thermal stability. Statistical analysis identified post-curing temperature as the dominant factor governing Tg, stiffness, and thermal stability, with synergistic contributions from GNP content and hardener concentration to the overall network performance. These results surpass those of GO- and CNT-based systems, demonstrating the superior efficiency of GNPs under optimized conditions. The proposed approach provides a robust pathway for developing epoxy nanocomposites with low filler content and enhanced multifunctional performance.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。