Despite the advanced stage of diamond thin-film technology, with applications ranging from superconductivity to biosensing, the realization of a stable and atomically thick two-dimensional diamond material, named here as diamondene, is still forthcoming. Adding to the outstanding properties of its bulk and thin-film counterparts, diamondene is predicted to be a ferromagnetic semiconductor with spin polarized bands. Here, we provide spectroscopic evidence for the formation of diamondene by performing Raman spectroscopy of double-layer graphene under high pressure. The results are explained in terms of a breakdown in the Kohn anomaly associated with the finite size of the remaining graphene sites surrounded by the diamondene matrix. Ab initio calculations and molecular dynamics simulations are employed to clarify the mechanism of diamondene formation, which requires two or more layers of graphene subjected to high pressures in the presence of specific chemical groups such as hydroxyl groups or hydrogens.
Abstract Molecular dynamics (MD) employing the Lennard-Jones (LJ) interaction potential was used to compute the heat capacities of argon at constant volume \CV\ and constant pressure \CP\ near the critical point very close to the asymptotic region. The accurate \MD\ calculation of critical divergences was shown to be related to a careful choice of the cutoff radius rc and the inclusion of long-range corrections in the \LJ\ potential. The computed \CP\ and \CV\ values have very good agreement as compared to available \NIST\ data. Furthermore, values of \CV\ in a range of temperatures for which \NIST\ data is not available could be computed. In the investigated range of temperatures, both \CP\ and \CV\ \MD\ results were fitted to a simple mathematical expression based on an empirical model that describes the critical effects when the asymptotic models are not appropriate. The present approach is of general applicability and robust to compute thermophysical properties of fluids in the near-critical region.
We report a first-principles study of edge-reconstructed, few-layered graphene nanoribbons. We find that the nanoribbon stability increases linearly with increasing width and decreases linearly with increasing number of layers (from three to six layers). Specifically, we find that a three-layer 1.3 nm wide ribbon is energetically more stable than the C60 fullerene, and that a 1.8 nm wide ribbon is more stable than a (10,0) carbon nanotube. The morphologies of the reconstructed edges are characterized by the presence of five-, six-, and sevenfold rings, with sp3 and sp2bonds at the reconstructed edges. The electronic structure of the few-layered nanoribbons with reconstructed edges can be metallic or semiconducting, with band gaps oscillating between 0 and 0.28 eV as a function of ribbon width.
Abstract Three basic diffusion properties of argon – shear viscosity, bulk viscosity and thermal conductivity – were studied in the neighborhood of the critical point using molecular dynamics (MD) and the Lennard-Jones potential energy function. \MD\ simulations were performed along the 1.0Pc and 1.2Pc isobars. Green-Kubo relations and a Lennard-Jones pair potential were used. Four different sets of Lennard-Jones parameters were used. A comparison of computed shear viscosity and thermal conductivity values with data available from the National Institute of Standards and Technology (NIST) displayed a good agreement. Results for bulk viscosity indicated that values of this property cannot be neglected in this thermodynamic region, a result that violates the traditional and much-assumed Stokes hypothesis in classical fluid mechanics. Furthermore, it was shown that in the neighborhood of the critical region the bulk viscosity can have larger values than the shear viscosity.
Abstract We propose an effective model for solute separation from fluids through reverse osmosis based on core-softened potentials. Such potentials have been used to investigate anomalous fluids in several situations under a great variety of approaches. Due to their simplicity, computational simulations become faster and mathematical treatments are possible. Our model aims to mimic water desalination through nano-membranes through reverse osmosis, for which we have found reasonable qualitative results when confronted against all-atoms simulations found in the literature. The purpose of this work is not to replace any fully atomistic simulation at this stage, but instead to pave the first steps towards coarse-grained models for water desalination processes. This may help to approach problems in larger scales, in size and time, and perhaps make analytical theories more viable.