相关论文: Peripheral neuron survival and outgrowth on graphe…
Hydrogen is one of the prime candidates for clean energy source with high energy density. However, current industrial methods of hydrogen production are difficult to provide hydrogen with high purity, thus hard to meet the requirements in…
Porous graphene (PG) is a graphene derivative endowed of nanoporous architectures. This material possesses a particular structure with interconnected networks of high pore volume, producing membranes with a large surface area. Experiments…
Harnessing the wave-nature of charge carriers in solid state devices, electron optics investigates and exploits coherent phenomena, in analogy with optics and photonics. Typically, this requires complex electronic devices leveraging…
Brain connectomes offer detailed maps of neural connections within the brain. Recent studies have proposed novel connectome graph datasets and attempted to improve connectome classification by using graph deep learning. With recent advances…
We introduce a kinetic model for the growth of epitaxial graphene on 6H-SiC. The model applies to vicinal surfaces composed of half-unit-cell height steps where experiment shows that step flow sublimation of SiC promotes the formation and…
Axonal growth and the formation of synaptic connections are key steps in the development of the nervous system. Here we present experimental and theoretical results on axonal growth and interconnectivity in order to elucidate some of the…
Graphene-based membranes have been investigated as promising candidates for water filtration and gas separation applications. Experimental evidences have shown that graphene oxide can be impermeable to liquids, vapors and gases, while…
Using first-principles techniques, we calculate the renormalization of the electron Fermi velocity and the vibrational lifetimes arising from electron-phonon interactions in doped bilayer graphene and in graphite and compare the results…
Two experimental studies reported the spontaneous formation of amorphous and crystalline structures of C60 intercalated between graphene and a substrate. They observed interesting phenomena ranging from reaction between C60 molecules under…
On-surface synthesis enables the fabrication of graphene nanoribbons (GNRs) with atomic precision, allowing their electronic, optical, and magnetic properties to be tuned by engineering edge structure and width. Progress on the synthesis of…
The mechanical integrity of composite materials depends primarily on the interface strength and the defect density of the reinforcement which is the provider of enhanced strength and stiffness. In the case of graphene/ polymer…
Graphene, the first true two-dimensional material still reveals the most remarkable transport properties among the growing class of two-dimensional materials. Although many studies have investigated fundamental scattering processes, the…
Graph neural networks (GNNs) learn the representation of graph-structured data, and their expressiveness can be further enhanced by inferring node relations for propagation. Attention-based GNNs infer neighbor importance to manipulate the…
Graphene is one of the most researched two dimensional (2D) material due to its unique combination of mechanical, thermal and electrical properties. Special 2D structure of graphene enables it to exhibit a wide range of peculiar material…
In this paper, optical properties of Chiral Graphene Nanoribbons both in longitude and transverse polarization have been studied using density functional theory calculation. It has been shown that the selection rule which have been reported…
The optical properties of graphene (Gr)-covered CsPbBr$_3$ quantum dots (QDs) were investigated using micro-photoluminescence spectroscopy, revealing a remarkable three-orders-of-magnitude enhancement in photoluminescence (PL) intensity…
We report the results of our first-principles investigation on the interaction of the nucleobases adenine (A), cytosine (C), guanine (G), thymine (T), and uracil (U) with graphene, carried out within the density functional theory framework,…
We develop a polycrystal graph neural network (PGNN) model for predicting the effective properties of polycrystalline materials, using the Li7La3Zr2O12 ceramic as an example. A large-scale dataset with >5000 different three-dimensional…
Graph neural networks (GNNs) are the predominant approach for graph-based machine learning. While neural networks have shown great performance at learning useful representations, they are often criticized for their limited high-level…
Here, the possibility of the existence of nitro-graphene derivatives with undisturbed graphene backbone is considered. Based on the first-principles calculation, it is shown that while NO$_2$ is unable to form a covalent bond with bare…