Communication: Local energetic analysis of the interfacial and surface energies of graphene from the single layer to graphite

Substrate adhesion evolves non-monotonically with processing time in millimeter-scale aligned carbon nanotube arrays

The advantageous intrinsic and scale-dependent properties of aligned nanofibers (NFs) and their assembly into 3D architectures motivate their use as dry adhesives and shape-engineerable materials. While controlling NF-substrate adhesion is critical for scaled manufacturing and application-specific performance, current understanding of how this property evolves with processing conditions is limited. In this report, we introduce substrate adhesion predictive capabilities by using an exemplary array of NFs, aligned carbon nanotubes (CNTs), studied as a function of their processing. Substrate adhesion is found to scale non-monotonically with process time in a hydrocarbon environment and is investigated via the tensile pull-off of mm-scale CNT arrays from their growth substrate. CNT synthesis follows two regimes: Mode I ('Growth') and Mode II ('Post-Growth'), separated by growth termination. Within 10 minutes of post-growth, experiments and modeling indicate an order-of-magnitude increase in CNT array-substrate adhesion strength (∼40 to 285 kPa) and effective elastic array modulus (∼6 to 47 MPa), and a two-orders-of-magnitude increase in the single CNT-substrate adhesion force (∼0.190 to 12.3 nN) and work of adhesion (∼0.07 to 1.5 J m^-2), where the iron catalyst is found to remain on the substrate. Growth number decay in Mode I and carbon accumulation in Mode II contribute to the mechanical response, which may imply a change in the deformation mechanism. Predictive capabilities of the model are assessed for previously studied NF arrays, suggesting that the current framework can enable the future design and manufacture of high-value NF array applications.

Insight into the Electrical Double Layer of an Ionic Liquid on Graphene

Graphene is a promising next-generation conducting material with the potential to replace traditional electrode materials in supercapacitors. Since energy storage in supercapacitors relies on the electrolyte-electrode interface, here we elucidate the interfacial subnanometer structure of a single component liquid composed solely of cations and anions – an ionic liquid- on electrified graphene. We study the effect of applied potential on the interaction between graphene and a silicon tip in an ionic liquid and describe it within the framework of the Derjaguin-Landau-Verwey-Overbeck (DLVO) theory. The energy is stored in an electrical double layer composed of an extended Stern layer, which consists of multiple ion layers over ~2 nanometers, beyond which a diffuse layer forms to compensate the applied potential on graphene. The electrical double layer significantly responds to the applied potential, and it shows the transition from overscreening to crowding of counterions at the interface at the highest applied potentials. It is proposed that surface charging occurs through the adsorption of the imidazolium cation to unbiased graphene (likely due to π-π interactions) and that the surface potential is better compensated when counterion crowding happens. This study scrutinizes the electrified graphene-ionic liquid interface, with implications not only in the field of energy storage, but also in lubrication.