Related papers: Computer Simulation of Carbonization and Graphitiz…
We introduce a machine learning approach to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). Our method is…
This paper presents a method to simulate the thermal behavior of 3D systems using a graph neural network. The method discussed achieves a significant speed-up with respect to a traditional finite-element simulation. The graph neural network…
Recent advances in scanning transmission electron microscopy (STEM) allow to observe solid-state transformations and reactions in materials induced by thermal stimulus or electron beam on the atomic level. However, despite the rate at which…
The collisions between high-energy ions and solids can result in significant physical and chemical changes to the material. These effects are potentially important for better understanding the chemistry of interstellar and planetary bodies,…
We probe the local inhomogeneities of the electronic properties of graphene at the nanoscale using scanning probe microscopy techniques. First, we focus on the study of the electronic inhomogeneities caused by the graphene-substrate…
Designing platforms to control phase-coherence and interference of electron waves is a cornerstone for future quantum electronics, computing or sensing. Nanoporous graphene (NPG) consisting of linked graphene nanoribbons has recently been…
Graphene oxide (GO) materials are widely studied, and yet their atomic-scale structures remain to be fully understood. Here we show that the chemical and configurational space of GO can be rapidly explored by advanced machine-learning…
The aim of the present work is to introduce a thermodynamic model to describe the growth of an oxide layer on a metallic substrate. More precisely, this paper offers a study of oxygen dissolution into a solid, and its consequences on the…
Formation of clusters of interstitial carbon atoms between the surface and second atomic layers of graphite is demonstrated by means of molecular dynamics simulations. It is shown that interstitial clusters result in the dome-like surface…
Graphene, the two-dimensional form of carbon presents outstanding electronic and transport properties. This gives hope for the development of applications in nanoelectronics. However, for industrial purpose, graphene has to be supported by…
Formation of clusters of interlayer interstitial carbon atoms in graphite is studied by means of molecular dynamics simulation. It is shown that the deformation potential is attractive for interstitials located in one interlayer region and…
Over many years, computational simulations based on Density Functional Theory (DFT) have been used extensively to study many different materials at the atomic scale. However, its application is restricted by system size, leaving a number of…
During the carbonization process of raw polymer precursors, graphitic structures can evolve. The presence of these graphitic structures affects mechanical properties of the carbonized carbon fibers. To gain a better understanding of the…
The physical processes occurring in the presence of disorder: point defects, grain boundaries, etc. may have detrimental effects on the electronic properties of graphene. Here we present an approach to reveal the grain structure of graphene…
Graphene is a truly two-dimensional material with exceptional electronic, mechanical, and optical properties. As such, it consists of surface only and can be probed by the well developed surface-science techniques as, e.g., scanning…
Energetic and geometric aspects of the permeation of low-Z atoms through graphene sheets are investigated. Energy barriers and deformations are calculated via density functional theory for the permeation of H, He, Li and Be atoms at several…
We present an ab initio study on the structural and electronic distortions of modified graphene by creation of vacancies, inclusion of boron atoms, and the coexistence of both, by means of thermodynamics and band structure calculations. In…
Polymer-derived ceramics combine the thermal stability of ceramics with the versatile properties of carbon domains, but modeling their atomic-scale evolution during processing remains elusive due to the limitations of traditional…
This study utilises linear-scaling density functional theory (DFT) and develops a new machine-learning potential for carbon and nitrogen (GAP-CN), based on the carbon potential (GAP20), to investigate the interaction between carbon…
Atomic vacancies have a strong impact in the mechanical, electronic and magnetic properties of graphene-like materials. By artificially generating isolated vacancies on a graphite surface and measuring their local density of states on the…