Related papers: Hybrid neural network potential for multilayer gra…
Graphene, the atomically-thin honeycomb carbon lattice, is a highly conducting 2D material whose exposed electronic structure offers an ideal platform for sensing. Its biocompatible, flexible, and chemically inert nature associated to the…
Hypergraphs are a powerful abstraction for representing higher-order interactions between entities of interest. To exploit these relationships in making downstream predictions, a variety of hypergraph neural network architectures have…
We outline a Kohn-Sham-Dirac density-functional-theory (DFT) scheme for graphene sheets that treats slowly-varying inhomogeneous external potentials and electron-electron interactions on an equal footing. The theory is able to account for…
Nanostructuring materials at small scales enables control over their physical properties, revealing behaviors not observed at larger dimensions. This strategy is particularly effective in two-dimensional (2D) materials, where surface…
The prediction of physicochemical properties from molecular structures is a crucial task for artificial intelligence aided molecular design. A growing number of Graph Neural Networks (GNNs) have been proposed to address this challenge.…
Recent progress in Graph Neural Networks (GNNs) for modeling atomic simulations has the potential to revolutionize catalyst discovery, which is a key step in making progress towards the energy breakthroughs needed to combat climate change.…
We evaluate the electronic transmission and conductance in bilayer graphene through a finite number of potential barriers. Further, we evaluate the dispersion relation in a bilayer graphene superlattice with a periodic potential applied to…
GeTe is a prototypical phase change material of high interest for applications in optical and electronic non-volatile memories. We present an interatomic potential for the bulk phases of GeTe, which is created using a neural network (NN)…
Graphene and boron nitride (GPBN) heterostructures provide a viable way to realize tunable bandgap, promising new opportunities in graphene-based nanoelectronic and optoelectronic devices. In the present study, we investigated the interplay…
Suspended membranes of monoatomic graphene exhibit great potential for applications in electronic and nanoelectromechanical devices. In this work, a "hot and dry" transfer process is demonstrated to address the fabrication and patterning…
Bernal stacked bilayer graphene subject to a superlattice potential can realize topological and stacked flat bands [1]. In the present work, we extend the study of a superlattice potential on graphene heterostructures to trilayer and…
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline…
Bandgap engineering by substituting C with B and N atoms in graphene has been shown to be a promising way to improve semiconducting properties of graphene. Such hybridized monolayers consisting of hexagonal BN phases in graphene (h-BNC)…
We employ dual-gated 30{\deg}-twisted bilayer graphene to demonstrate simultaneous ultra-high mobility and conductivity (up to 40 mS at room temperature), unattainable in a single-layer of graphene. We find quantitative agreement with a…
We use first-principle density functional theory (DFT) to study the transport properties of single and double barrier heterostructures realized by stacking multilayer h-BN or BC$_{2}$N, and graphene films between graphite leads. The…
We present an analytical model to study the electronic properties, including full band structure, low energy dispersions around the Dirac point and density of states of the ABC-stacking $N$-layer graphene (ABCNLG). An ABCNLG can be…
The performance limits of the multilayer graphene nanoribbon (GNR) field-effect transistor (FET) are assessed and compared to those of monolayer GNR FET and carbon nanotube (CNT) FET. The results show that with a thin high-k gate insulator…
Finite-temperature properties of graphene monolayers under tensile stress have been studied by path-integral molecular dynamics (PIMD) simulations. This method allows one to consider the quantization of vibrational modes in these…
MXene-based heterostructures have received considerable interest owing to their unique properties. Herein, we examine various heterostructures of a prototypical MXene and graphene using density functional theory. We find that the adhesion…
Defect engineering via parallel cracks has been proposed as a route to tailor the fracture response of graphene. However, atomistic fracture predictions can be strongly sensitive to the interatomic potential. Here, we quantify the effect of…