C.M. Sims, J.P. Killgore, E. Mansfield, J.R. Downing, A.C.M. de Moraes, M.C. Hersam, J.A. Fagan
National Institute of Standards and Technology,
United States
Keywords: analytical ultracentrifugation, graphene, 2D materials, differential sedimentation, separation, metrology
Summary:
2D materials, such as graphene, MoS2, WS2, and MXenes, are expected to impact a wide variety of applications. These include thin film applications such as semiconductor electronics, separation membranes, and sensor devices, but also bulk material applications requiring incorporation into composite materials. While liquid-phase dispersion is commonly used to assemble or incorporate 2D materials into films or composites, the intrinsic material properties and transport phenomena depend on the size distribution of individual nanoplatelets and matrix-influenced liquid-phase interactions between nanoplatelets. Differential sedimentation (DS) is a popular, multi-stage processing method for liquid-phase dispersions of 2D materials, enabling production of subpopulations with narrowed lateral size and layer thickness distributions. However, characterization and optimization of this centrifugation cascade methodology has relied on surface analysis characterization techniques requiring deposition from solution and relatively slow measurements to sample enough particles for statistical comparisons. Here, we apply analytical ultracentrifugation (AUC) to rapidly and directly measure as-dispersed graphene nanoplatelet dispersions and subpopulations generated through DS. The liquid-phase characterization of AUC is shown to resolve both the broad sedimentation coefficient distributions of as-dispersed samples but also changes in subpopulation dispersions determined by a protocol of applied DS processing. With comparisons made to measurements on deposited samples by scanning electron microscopy and atomic force microscopy, the value of AUC to rapidly monitor changes in the sedimentation distribution of each particle population is demonstrated to allow tailoring of the DS protocol to produce significantly narrower population distributions. This rapid characterization is particularly important for technologies in which dispersed nanoparticles cannot be removed from a solvent solution for microscopy analysis.