Related papers: The next nearest neighbor effect on the 2D materia…
Using density functional based LDA+U method and linear-response theory, we study the magnetic exchange interactions of the superconductor Nd{1-x}Sr{x}NiO2. Our calculated nearest-neighbor exchange constant J1=82 meV is large, weakly…
In one dimension density-density interactions of particles reduce their mobility and hence the Drude weight, which controls the divergence of the optical conductivity at zero frequency, decreases. We study effects of pair hopping events on…
We theoretically propose possible magnetism-induced negative thermal expansion in honeycomb-lattice antiferromagnets with edge-sharing networks of $MX_6$ octahedra where $M$ and $X$ are transition-metal and ligand ions, respectively. In…
Two-dimensional (2D) materials exhibit a number of improved mechanical, optical, electronic properties compared to their bulk counterparts. The absence of dangling bonds in the cleaved surfaces of these materials allows combining different…
Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory…
The Hubbard and related models serve as a fundamental starting point in understanding the novel experimental phenomena in correlated electron materials, such as superconductivity, Mott insulator, magnetism and stripe phases. Recent…
We report magnetoresistance data in magnetic semiconductor multilayers, which exhibit a clear step-wise behavior as a function of external field. We attribute this highly non-trivial step-wise behavior to next-nearest-neighbor interlayer…
Advances in scaling down heterostructures and having an improved interface quality together with atomically-thin two-dimensional materials suggest a novel approach to systematically design materials. A given material can be transformed…
Two dimensional (2D) layered materials have recently gained renewed interest due to their exotic electronic properties along with high specific surface area. The prospects of exploiting these properties in sensing, catalysis, energy…
Fuzzy rough sets are well-suited for working with vague, imprecise or uncertain information and have been succesfully applied in real-world classification problems. One of the prominent representatives of this theory is fuzzy-rough nearest…
The particles in the honeycomb lattice with on-site $s$-wave pairing exhibit many interesting behaviors, which can be described in the framework of the Hubbard model. Among others, at the half-filling, some critical value $|U_c|$ of pairing…
Effects of electron many-body interactions amplify in an electronic system with a narrow bandwidth opening a way to exotic physics. A narrow band in a two-dimensional (2D) honeycomb lattice is particularly intriguing as combined with Dirac…
The thermodynamics of solid/liquid interfaces under nanoconfinement has tremendous implications for liquid transport properties. Here using molecular dynamics, we investigate graphite nanoslits and study how the water/graphite interfacial…
Two-dimensional (2D) materials provide a platform for developing novel spintronic devices and circuits for low-power electronics. In particular, inducing magnetism and injecting spins in graphene have promised the emerging field of graphene…
Using first-principles calculations, we predict a Chern insulating phase in thin films of the ferromagnetic semi-metal GdN. In contrast to previously proposed Chern insulator candidates, which mostly rely on honeycomb lattices, this system…
Recent experimental synthesis of two-dimensional (2D) heterostructures opens a door to new opportunities in tailoring the electronic properties for novel 2D devices. Here, we show that a wide range of lateral 2D heterostructures could have…
In a honeycomb lattice the symmetry has been broken by adding an ionic potential and a single-particle gap was generated in the spectrum. We have employed the iterative perturbation theory (IPT) in dynamical mean field approximation method…
DNNs have gained widespread adoption in feature interaction recommendation models. However, there has been a longstanding debate on their roles. On one hand, some works claim that DNNs possess the ability to implicitly capture high-order…
We show that as the result of the nesting property of the Fermi surface, the quarter-doped Hubbard model on honeycomb lattice is unstable with respect to the formation of a magnetic insulating state with nonzero spin chirality for…
Fermions hopping on a hexagonal lattice represent one of the most active research field in condensed matter since the discovery of graphene in 2004 and its numerous applications. Another exciting aspect of the interplay between geometry and…