Unzipping Carbon Nanotube Bundles through NH−π Stacking for Enhanced Electrical and Thermal Transport
Shuiliang Wang, Zhequn Huang, Wenbo Shi, Dongwook Lee, Qixiang Wang, Wen Shang, Yosi Stein, Yang Shao‐Horn, Tao Deng, Brian L. Wardle, Kehang Cui
Abstract
Bundling of single-walled carbon nanotubes (SWCNTs) significantly undermines their superior thermal and electrical properties. Realizing stable, homogeneous, and surfactant-free dispersion of SWCNTs in solvents and composites has long been regarded as a key challenge. Here, we report amine-containing aromatic and cyclohexane molecules, which are common chain extenders (CEs) for epoxy curing in industry, can be used to effectively disperse CNTs. We achieve single-tube-level dispersion of SWCNTs in CE solvents, as demonstrated by the strong chirality-dependent absorption and photoluminescence emission. The SWCNT-CE dispersion remains stable under ambient conditions for months. The excellent dispersibility and stability are attributed to the formation of an n-type charge-transfer complex through the NH−π interaction between the amine group of CEs and the delocalized π bond of SWCNTs, which is confirmed by the negative Seebeck coefficient of the CE-functionalized SWCNT films, the red shift of the G band in the Raman spectra, and the NH−π peak in X-ray photoelectron spectroscopy. The high dispersibility of CEs significantly improves the electrical and thermal transport of macroscale CNT assemblies. The sheet resistance of the CE-dispersed SWCNT thin films reaches 161 Ω sq–1 at 80.8% optical transmittance after functional modification by HNO3. Moreover, the CEs cross-link CNTs and epoxy molecules, forming a pathway for phonon transport in CNT/epoxy nanocomposites. The thermal conductivity of the CE–CNT–epoxy composite is enhanced by 1850% compared with the original epoxy, which is the highest enhancement reported to date for CNT/epoxy nanocomposites. The CE-based NH−π interaction provides a new paradigm for the effective and stable dispersion of SWCNTs in a facile and scalable process.