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The dispersive interaction between nanotubes is investigated through ab initio theory calculations and in an analytical approximation. A van der Waals density functional (vdW-DF) [Phys. Rev. Lett. 92, 246401 (2004)] is used to determine and…
We study the potential of mean force (PMF) between atomistic silica and gold nanoparticles in the vacuum by using molecular dynamics simulations. Such an investigation is devised in order to fully characterize the effective interactions…
We develop an empirical potential for silicon which represents a considerable improvement over existing models in describing local bonding for bulk defects and disordered phases. The model consists of two- and three-body interactions with…
Neural networks have been applied to tackle many-body electron correlations for small molecules and physical models in recent years. Here we propose a new architecture that extends molecular neural networks with the inclusion of periodic…
Phonon-based approaches and molecular dynamics are widely established methods for gaining access to a temperature-dependent description of material properties. However, when a compound's phase space is vast, density-functional-theory-backed…
We report a new Quantum Mechanical/Molecular Dynamics (QM/MD) simulation loop to model the coupling between the electron and atom dynamics in solid/liquid interfacial systems. The method can describe simultaneously both the quantum…
Quasi-continuous structural transformation from the crystalline to amorphous state takes place in graphite during ball-milling. The quantitative characteristics of a short- and a medium-range orders in carbon nanomaterials structure are…
Deep learning techniques have opened a new venue for electronic structure theory in recent years. In contrast to traditional methods, deep neural networks provide much more expressive and flexible wave function ansatz, resulting in better…
By merging bottom-up and top-down strategies we tailor graphene's electronic properties within nanometer accuracy, which opens up the possibility to design optical and plasmonic circuitries at will. In a first step, graphene electronic…
New ultra-hard rhombohedral B2N2 and BC2N - or hexagonal B6N6 and B3C6N3 - are derived from 3R graphite based on crystal chemistry rationale schematizing a mechanism for 2D => 3D transformation. Full unconstrained geometry optimizations…
A systematic review is made for the AA-, AB- and ABC-stacked graphites. The generalized tight-binding model, accompanied with the effective-mass approximation and the Kubo formula, is developed to investigate electronic and optical…
By combining classical molecular dynamics simulations and density functional theory total energy calculations, we study the possibility of doping graphene with B/N atoms using low-energy ion irradiation. Our simulations show that the…
Novel superhard materials, especially those with superior thermal and chemical stability, are needed to replace diamond. Carbon nitrides (C-N), which are likely to possess these charac- teristics and have even been expected to be harder…
Inexpensive machine learning potentials are increasingly being used to speed up structural optimization and molecular dynamics simulations of materials by iteratively predicting and applying interatomic forces. In these settings, it is…
Graph neural networks have recently become a standard method for analysing chemical compounds. In the field of molecular property prediction, the emphasis is now put on designing new model architectures, and the importance of atom…
The cointercalation of sodium with the solvent organic molecule into graphite can resolve difficulty of forming the stage-I Na-graphite intercalation compound, which is a predominant anode of Na-ion battery. To clarify the mechanism of such…
High-quality nitrogen-doped graphene on nickel is prepared by exploiting both the catalytic properties of nickel and the solubility of nitrogen atoms into its bulk. Following the standard chemical vapor deposition procedure, a previously…
Constructing an accurate atomistic model for the high-pressure phases of tin (Sn) is challenging because properties of Sn are sensitive to pressures. We develop machine-learning-based deep potentials for Sn with pressures ranging from 0 to…
Along with the inherent remarkable properties of graphene, adatom-intercalated graphene-related systems are expected to exhibit tunable electronic properties. The metal-based atoms could provide multi-orbital hybridizations with the…
In bilayer graphene the exact energy levels of quantum dots can be derived from the four-component continuum Hamiltonian. Here, we study the quantum dot energy levels with approximate equations and compare them with the exact levels. The…