No abstract

The production of graphene flakes at industrial scale required the development of new fabrication strategies beyond conventional mechanical exfoliation such as Liquid Phase Exfoliation. This successful endeavor should have been matched by a similar development in the statistical analysis of the newly mass-produced material. However, flake quantification protocols kept relying mostly on the analysis of a few flakes only, resulting in conflicting and misleading analyses. Here, we propose a new AFM-based semi-automated protocol for the simultaneous analysis and quantification of thousands of flakes. It yields statistically relevant values for flake size and thickness distributions. Moreover, we include an important mass content parameter which is essential to separate otherwise statistically identical graphene-rich from graphite-rich samples. This new methodology opens a new path in the characterization of large-scale produced flakes enabling direct and trustful comparison between different graphene, or any other 2D material, products.

The heterogeneous nature of mass-produced 2D material’s nanoflakes requires analysis of size and shape parameters: their distributions around the desired values are essential for production and characterization. In this work, we obtain analytical expressions and behaviors of statistical distributions of experimentally extracted size and shape parameters of nanoflakes obtained by liquid-phase exfoliation. The collected data are open and can be mathematically handled to be analyzed through different associations in different scales, such as the logarithm of the length/thickness (r) and length/width (r L) aspect ratios. We find that ln­(r), a shape parameter, follows nearly Gaussian distributions, being an efficient fingerprint to characterize the material type and processing. On the other hand, the logarithms of thickness and volume follow asymmetric distributions with specific asymptotic behaviors, called exponential-power-Gaussian functions, but centrifugation turns both nearly Gaussian-distributed. Finally, the logarithm of the length/width aspect ratio, ln­(r L), an in-plane shape parameter, was found to follow the single-parameter probability density distribution xe–λx 2 . The method detected that centrifugation enhances, by up to threefold, the percentage of flakes with large length/width ratios. This statistical methodology can be incorporated into the quality control of mass production of 2D nanoflakes, whose target applications can be found across the fast-growing nanomaterials’ industry.

A primitive cubic lattice composed of 1,000 atoms has 488 surface sites. By definition, every atom in a strictly two-dimensional single-layer lattice composes its surface. These surface atoms are the ones that undergo chemical interactions with the surrounding medium, thereby defining the functionalities of the nanostructure. As such, one of the most important morphological properties of nano-objects is the extremely large specific surface area that enhances their levels of reactivity. Here, we introduce an optical spectroscopy method to measure the surface area concentration, ρA, of mass-produced graphene nanoflakes in liquid dispersions. The information is accessed from the quenching of the fluorescence signal from the dye molecules dispersed in the medium. We found that the quantum efficiency of the fluorescence signal decays exponentially with the concentration of graphene’s surface area, the decay rate being independent of the degree of exfoliation. If the mass concentration ρ is known by other means, the specific surface area can be extracted from the ratio ρA/ρ. The measurements can be performed directly in liquid suspensions of nanoflakes, being highly applicable to the quality control of mass-produced two-dimensional nanomaterials, especially by means of mechanically assisted liquid-phase exfoliation.