The mechanical properties of irradiated single-layer graphene sheets are determined as a function of inserted vacancy concentration. We find that the vacancy-induced crystalline-to-amorphous transition is accompanied by a brittle-to-ductile transition in the failure response of irradiated graphene sheets for inserted vacancy concentrations of 8%–12%. While point defects and larger voids appreciably degrade the strength of pristine graphene, we find that even heavily damaged samples (∼20% vacancies) exhibit tensile strengths of ∼30 GPa, in significant excess of those typical of engineering materials. Our results suggest that defect engineering of graphene is feasible without incurring a complete loss of its desirable mechanical properties.

We study the elastic response of graphene nanomeshes based on molecular-statics and molecular-dynamics simulations of uniaxial tensile deformation tests. Elastic properties are determined as a function of the nanomesh architecture, namely, the lattice arrangement of the pores, pore morphology, material density (ρ), and pore edge passivation, and scaling laws for the density dependence of the elastic modulus M, M(ρ), are established. We find that, for circular unpassivated pores, M scales with the square of ρ. Deviations from quadratic scaling are most strongly influenced by pore morphology and, to a lesser extent, by pore edge passivation and temperature.

We report results of a systematic molecular-dynamics study on the vacancy-induced amorphization of single-layer graphene. An inserted vacancy concentration between 5% and 10% marks the onset of the amorphization transition. The computed amorphized configurations are in agreement with recent experimental observations. We find that the transition becomes less abrupt with vacancy concentration as the temperature increases and determine the surface roughness of the defective graphene as a function of vacancy concentration. We also find that the electronic density of states of vacancy-amorphized graphene is characterized by introduction of localized states near the Fermi level of perfect single-layer graphene.

An augmented Bayesian optimization approach is presented for materials discovery with noisy and unreliable measurements. A challenging non-Gaussian, non-sub-Gaussian noise process is used as a case study for the discovery...