We present molecular dynamics simulations of monolayer graphene under uniaxial tensile loading. The Morse, bending angle, torsion and Lennard-Jones potential functions are adopted within the mdFOAM library in the OpenFOAM software, to describe the molecular interactions in graphene. A well-validated graphene model using these set of potentials is not yet available. In this work, we investigate the accuracy of the mechanical properties of graphene when derived using these simpler potentials, compared to the more commonly used complex potentials such as the Tersoff-Brenner and AIREBO potentials. The computational speed up of our approach, which scales O(1.5N), where N is the number of carbon atoms, enabled us to vary a larger number of system parameters, including graphene sheet orientation, size, temperature and concentration of nanopores. The resultant effect on the elastic modulus, fracture stress and fracture strain is investigated. Our simulations show that graphene is anisotropic, and its mechanical properties are dependant on the sheet size. An increase in system temperature results in a significant reduction in the fracture stress and strain. Simulations of nanoporous graphene were created by distributing vacancy defects, both randomly and uniformly, across the lattice. We find that the fracture stress decreases substantially with increasing defect density. The elastic modulus was found to be constant up to around 5% vacancy defects, and decreases for higher defect densities. ARTICLE HISTORY

The successful integration of graphene in future technologies, such as filtration and nanoelectronics, depends on the ability to introduce controlled nanostructured defects in graphene. In this work, Raman spectroscopy is used to investigate the induction of disorder in graphene via gallium ion beam bombardment. Two configurations of CVD-grown graphene samples are used: (i) graphene supported on a Si/SiO2 substrate, and (ii) graphene suspended on porous TEM grids. It is observed that the supported graphene experiences more damage in response to lower beam doses than suspended graphene. This phenomenon is attributed to the behaviour of the energetic ions impinging the sample. In suspended graphene, the ions pass through the graphene membrane once and disperse to the atmosphere, while in supported graphene, the ions embed themselves in the substrate causing swelling and backscattering events, hence increasing the induced disorder. In supported graphene, the ratio between the Gaussian D and G peaks attributed to amorphous carbon, and the Lorentzian D and G peaks attributed to graphene, (IDG/IDL) and (IGG/IGL), are suggested to be used to quantify the degree of amorphization. The results are relevant to the development of nanostructured graphene-based filtration or desalination membranes, as well as for graphene-based nanoelectronics.

Photocatalytic coatings with self-cleaning properties are becoming increasingly more popular due to the increased awareness of the importance of cleaning and the associated high cost of cleaning supplies and services. This research investigated self-cleaning photocatalytic polydimethylsiloxane (PDMS)/titanium dioxide (TiO2) nanocomposite coatings and focused on selecting the optimal TiO2 phase and concentration. To date, the comparison of the different TiO2 phases as a nanocomposite coating has not been sufficiently considered. PDMS/TiO2 nanocomposite coatings with three nanomaterial (NM) samples (an anatase, rutile, and mixed phase) and three concentrations of TiO2 (0.6, 1 and 3 w/v%) were prepared, applied to glass slides by dip coating, and tested with respect to hydrophobicity, surface stability, antifogging, and photocatalytic properties. It was found that a stable hydrophobic coating with the optimal photocatalyitc performance was produced with 3 w/v% anatase TiO2.