Abstract
Graphite's lubricating properties due to the "weak" interactions between individual layers have long been known. However, these interactions are not weak enough to allow graphite to readily exfoliate into graphene on a large scale. Separating graphite layers down to a single sheet is an intense area of research as scientists attempt to utilize graphene's superlative properties. The exfoliation and processing of layered materials is governed by the friction between layers. Friction on the macroscale can be intuitively understood, but there is little understanding of the mechanisms involved in nanolayered materials. Using molecular dynamics and a new forcefield, graphene's unusual behavior in a superlubric state is examined, and the energy dissipated between two such surfaces sliding past each other is shown. The dependence of friction on temperature and surface roughness is described, and agreement with experiment is reported. The accuracy of the simulated behavior enables the processes that drive exfoliation of graphite into individual graphene sheets to be described. Taking into account the friction between layers, a peeling mechanism of exfoliation is predicted to be of lower energy cost than shearing.
Highlights
The results of the adsorption energies of a graphite sheet using established forcefields (OPLS, AMBER, COMPASS and Driedling) along with comparisons to experiment and DFT simulations are shown in Figure S11–5
Values given in the main text for the distance travelled by a flake (e.g. Table I) are given as the arithmetic mean of the straight-line distance travelled
The total distance travelled gives a better indication of the friction between the substrate and projectile
Summary
To construct our new GraFF forcefield, we firstly identified the best existing forcefields for simulating the adsorption of graphene for simulating. The results of the adsorption energies of a graphite sheet using established forcefields (OPLS, AMBER, COMPASS and Driedling) along with comparisons to experiment and DFT simulations are shown in Figure S1 (and Table III in the main text)[1,2,3,4,5]. Both AMBER and Dreidling forcefields overestimate the adsorption energy and layer spacing (and are outside of the experimental region); these forcefields were discounted on this basis for the GraFF forcefield. Similar to many forcefields, GraFF cannot represent chemical reactions, but we expect it to be transferable to many situations were graphene and graphene oxide are involved
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