Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to applications ranging from water filtration to electronics to investigations of radiation damage in graphite moderators. To assess the accuracy of DFT in such applications, we report diffusion quantum Monte Carlo (DMC) calculations of the formation energies of some common and important point defects in monolayer graphene: monovacancies, Stone-Wales defects, and silicon substitutions. We find that standard DFT methods underestimate monovacancy formation energies by around 1 eV. The disagreement between DFT and DMC is somewhat smaller for Stone-Wales defects and silicon substitutions. We examine vibrational contributions to the free energies of...
The allotropes of carbon make its solid phases amongst the most diverse of any element. It can occur...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
This thesis addresses several challenging problems in low-dimensional systems, which have rarely or ...
Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to...
Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to...
We report diffusion quantum Monte Carlo calculations of the interlayer binding energy of bilayer gra...
International audienceThe density functional tight binding approach (DFTB) is well adapted for the s...
The density functional tight binding approach (DFTB) is well adapted for the study of point and line...
We study low-dimensional materials and devices through use of the variational and diffusion quantum ...
Nearly quantitative agreement between density functional theory (DFT) and diffusion Monte Carlo (DMC...
Si dangling bonds at the interface of quasi-free-standing monolayer graphene (QFMLG) are known to ac...
By employing both molecular dynamics (MD) simulations and ab initio calculations based on the densit...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
Graphene is a one atom thick layer of carbon atoms arranged in hexagonal lattice in two-dimensions. ...
The allotropes of carbon make its solid phases amongst the most diverse of any element. It can occur...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
This thesis addresses several challenging problems in low-dimensional systems, which have rarely or ...
Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to...
Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to...
We report diffusion quantum Monte Carlo calculations of the interlayer binding energy of bilayer gra...
International audienceThe density functional tight binding approach (DFTB) is well adapted for the s...
The density functional tight binding approach (DFTB) is well adapted for the study of point and line...
We study low-dimensional materials and devices through use of the variational and diffusion quantum ...
Nearly quantitative agreement between density functional theory (DFT) and diffusion Monte Carlo (DMC...
Si dangling bonds at the interface of quasi-free-standing monolayer graphene (QFMLG) are known to ac...
By employing both molecular dynamics (MD) simulations and ab initio calculations based on the densit...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
Graphene is a one atom thick layer of carbon atoms arranged in hexagonal lattice in two-dimensions. ...
The allotropes of carbon make its solid phases amongst the most diverse of any element. It can occur...
Graphene, the thinnest material with a stable 2D structure, is a potential alternative for silicon-b...
This thesis addresses several challenging problems in low-dimensional systems, which have rarely or ...