相关论文: Hybrid neural network potential for multilayer gra…
The application of the chiral decomposition procedure to hybrid graphene h-BN systems revealed rules for the partition of the system into effective subsystems being bilayers plus monolayer in case the number of layers is odd. Three types of…
We report results of a multiscale simulation study of multilayer structures consisting of graphene sheets with embedded Pt nanoparticles. Density functional theory is used to understand the energetics of Pt-graphene interfaces and provide…
The structural relaxation of multilayer graphene is essential in describing the interesting electronic properties induced by intentional misalignment of successive layers, including the recently reported superconductivity in twisted bilayer…
Graph neural networks (GNNs) provide powerful insights for brain neuroimaging technology from the view of graphical networks. However, most existing GNN-based models assume that the neuroimaging-produced brain connectome network is a…
Heterostructures prepared from graphene and fluorographene (FG) using the technology of 2D printing on solid and flexible substrates were fabricated and studied. Excellent stability of printed graphene layers and, to a lesser degree,…
The formation of image-potential states at the interface between a graphene layer and a metal surface is studied by means of model calculations. An analytical one-dimensional model-potential for the combined system is constructed and used…
The prediction of the atomistic structure and properties of crystals including defects based on ab-initio accurate simulations is essential for unraveling the nano-scale mechanisms that control the micromechanical and macroscopic behaviour…
Strain-engineered graphene has garnered much attention recently owing to the possibilities of creating substantial energy gaps enabled by pseudo-magnetic fields. While theoretical works proposed the possibility of creating large-area…
Graphene, a 2-dimensional monolayer form of sp2 hybridizated carbon atoms, is attracting increasing attention due to its unique and superior physicochemical properties. Covalently functionalized graphene layers, with their modifiable…
The interaction between graphene and hexagonal boron nitride (hBN) plays a pivotal role in determining the electronic and structural properties of graphene-based devices. In this work, we employ quantum Monte Carlo (QMC) to study the…
We introduce UEIPNet, an equivariant graph neural network designed to predict both interatomic potentials and tight-binding (TB) Hamiltonians for an atomic structure. The UEIPNet is trained using density functional theory calculations…
This review on graphene, a one atom thick, two-dimensional sheet of carbon atoms, starts with a general description of the graphene electronic structure as well as a basic experimental toolkit for identifying and handling this material.…
The unique optical and electronic properties of graphene allow one to realize active optical devices. While several types of graphene-based photonic modulators have already been demonstrated, the potential of combining the versatility of…
Infrared and visible image fusion has gradually proved to be a vital fork in the field of multi-modality imaging technologies. In recent developments, researchers not only focus on the quality of fused images but also evaluate their…
The possibility to control the commensurability and distance between graphene layers separated by a dielectric spacer is considered by the example of a heterostructure consisting of double-layer graphene separated by atomic layers of argon.…
The vertical integration of multiple two-dimensional (2D) materials in heterostructures, held together by van der Waals forces, has opened unprecedented possibilities for modifying the (opto-)electronic properties of nanodevices. Graphene,…
We report on the fabrication of hybrid molecular devices employing multilayer graphene (MLG) flakes which are patterned with a constriction using a helium ion microscope (HIM) or an oxygen plasma etch. The patterning step allows for the…
Electron's tunneling through potential barrier in monolayer and bilayer graphene lattices is investigated by using full tight-binding model. Emphasis is placed on the resonance tunneling feature and inter-valley scattering probability. It…
Recent intensive research on two-dimensional materials (2DMs) rekindle the interest in the intercalation of various atoms and molecules into layered compounds as a tool to manufacture 2DMs and tune their optoelectronic, magnetic and…
We introduce a multi-tasking graph convolutional neural network, HydraGNN, to simultaneously predict both global and atomic physical properties and demonstrate with ferromagnetic materials. We train HydraGNN on an open-source ab initio…