相关论文: Machine Learning Potential for Hexagonal Boron Nit…
The allotropes of boron continue to challenge structural elucidation and solid-state theory. Here we use machine learning combined with random structure searching (RSS) algorithms to systematically construct an interatomic potential for…
When combined with graphene, hexagonal boron nitride (h-BN) is an ideal substrate and gate dielectric with which to build metalh-BN|graphene field-effect devices. We use first-principles density functional theory (DFT) calculations for…
The inherent crystal anisotropy of hexagonal boron nitride (hBN) sustains naturally hyperbolic phonon polaritons, i.e. polaritons that can propagate with very large wavevectors within the material volume, thereby enabling optical…
Artificial neural network potentials (NNPs) have emerged as effective tools for understanding atomic interactions at the atomic scale in various phenomena. Recently, we developed highly transferable NNPs for {\alpha}-iron and…
Lateral superlattices in 2D materials are emerging as a powerful platform for exploring novel quantum phenomena, which can be realized through the proximity coupling in forming moir\'e pattern with another layer. This approach, however, is…
Current interest in two-dimensional materials extends from graphene to others systems like single-layer hexagonal boron-nitride (h-BN), for the possibility of making heterogeneous structures to achieve exceptional properties that cannot be…
We present a transfer-free preparation method for graphene on hexagonal boron nitride (h-BN) crystals by chemical vapor deposition of graphene via a catalytic proximity effect, i.e. activated by a Cu catalyst close-by . We demonstrate the…
Encapsulating graphene in hexagonal Boron Nitride has several advantages: the highest mobilities reported to date are achieved in this way, and precise nanostructuring of graphene becomes feasible through the protective hBN layers.…
In this work, we present an empirical force field for hexagonal boron nitride (hBN) monolayers, derived via a bottom-up strategy from first principles calculations. We aim to deliver a simple analytical force field for boron nitride which…
Increased power density in modern microelectronics has led to thermal management challenges which can cause degradation in performance and reliability. In many high-power electronic devices, the power consumption and heat removal are…
Hexagonal boron nitride (hBN) is a wide bandgap van der Waals material that is emerging as a powerful platform for quantum optics and nanophotonics. In this work, we demonstrate whispering gallery mode silica microresonators hybridized with…
We introduce a machine learning prediction workflow to study the impact of defects on the Raman response of 2D materials. By combining the use of machine-learned interatomic potentials, the Raman-active $\Gamma$-weighted density of states…
Many positive electrode materials in lithium ion batteries include transition metals which are difficult to describe by electronic structure methods like density functional theory (DFT) due to the presence of multiple oxidation states. A…
Hexagonal boron nitride (hBN) is a promising material for next-generation semiconductor and optoelectronic devices due to its wide bandgap and remarkable optical properties. To apply this material in the semiconductor industry, it is…
Hexagonal boron nitride (hBN) is a wide band gap, van der Waals material that is highly promising for solid-state quantum technologies as a host of optically addressable, paramagnetic spin defects. Intrinsic and extrinsic point defects…
We investigate interlayer adhesion and relaxation at interfaces between graphene and hexagonal boron nitride (hBN) monolayers in van der Waals heterostructures. The adhesion potential between graphene and hBN is calculated as a function of…
We examine the effect of a hexagonal boron nitride (hBN) substrate on electron transport through graphene nanojunctions just before gap formation. Junctions in vacuum and on hBN are formed using classical molecular dynamics to create…
Hexagonal boron nitride (hBN) is a natural hyperbolic material which can also accommodate highly dispersive surface phonon-polariton modes. In this paper, we examine theoretically the mid-infrared optical properties of graphene-hBN…
Hexagonal boron nitride (BN), one of the very few layered insulators, plays a crucial role in 2D materials research. In particular, BN grown with a high pressure technique has proven to be an excellent substrate material for graphene and…
The thermoelectric properties of in plane heterostructures made of Graphene and hexagonal Boron Nitride (BN) have been investigated by means of atomistic simulation. The heterostructures consist in armchair graphene nanoribbons to the sides…