Nanoscale Anisotropy of SWCNTs Promotes Enhanced Diffusion in Heterogeneous Complex Fluids

Abstract Single-walled carbon nanotubes (SWCNTs) are anisotropic nanoparticles with unique mechanical, electrical, and optical properties. These properties have enabled applications in reinforcing nanocomposites, drug delivery, biosensing, and biomedical imaging, where their performance depends on transport through complex fluids. The mechanisms governing SWCNT transport in structured heterogeneous fluids, however, remain poorly understood because of their multiple characteristic length scales that can be smaller than or comparable to the structural length scales of the surrounding fluid. Here, we investigate the dynamics of SWCNTs in semidilute poly(ethylene oxide) solutions by systematically varying polymer concentration and molecular weight. We directly compare their transport with that of spherical nanoparticles (SNPs) with comparable characteristic dimensions to isolate the effect of particle anisotropy. SWCNTs exhibit substantially enhanced diffusivities up to 300× faster than Stokes−Einstein predictions. These deviations emerge at lower polymer molecular weights and are considerably larger than those observed for SNPs. SWCNT dynamics collapse onto a single curve when plotted as a function of the ratio of nanotube length to the polymer correlation length even well into the entangled regime, whereas SNPs exhibit a steeper power-law decrease that reflects coupling to entanglement dynamics. Moreover, SWCNTs exhibit pronounced non-Gaussian distributions of particle displacements, which confirm that SWCNTs experience different viscosities when transporting along or perpendicular to their length. Our results show that the nanoscale diameter of SWCNTs enables them to avoid constraints imposed by the polymer network and that their anisotropic geometry gives rise to distinct coupling to polymer microstructure and multiple diffusive modes. These findings reveal the mechanisms governing enhanced SWCNT transport and non-Gaussian statistics in structured complex media and provide a framework for predicting SWCNT dynamics in soft matter and biological environments.