Related papers: The structure of thin boron nanowires predicted us…
We predict the stabilities of \alpha-graphynes and their boron nitride analogues(\alpha-BNyne), which are considered as competitors of graphene and two-dimensional hexagonal BN. Based on first-principles plane wave method, we investigated…
Among exciting recent advances in the field of two-dimensional (2D) materials, the successful fabrications of the C60 fullerene networks has been a particularly inspiring accomplishment. Motivated by the recent achievements, herein we…
A derivative structure is a nonequivalent substitutional atomic configuration derived from a given primitive cell. The enumeration of derivative structures plays an essential role in searching for the ground states in multicomponent…
Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we…
One-dimensional NMR spectroscopy is one of the most widely used techniques for the characterization of organic compounds and natural products. For molecules with up to 36 non-hydrogen atoms, the number of possible structures has been…
We report a theoretical study of dielectric properties of models of amorphous Boron Nitride, using interatomic potentials generated by machine learning. We first perform first-principles simulations on small (about $100$ atoms in the…
Due to the vast chemical space, discovering materials with a specific function is challenging. Chemical formulas are obligated to conform to a set of exacting criteria such as charge neutrality, balanced electronegativity, synthesizability,…
Moir\'e patterns made of two-dimensional (2D) materials represent highly tunable electronic Hamiltonians, allowing a wide range of quantum phases to emerge in a single material. Current modeling techniques for moir\'e electrons requires…
The structural and electronic properties of hexagonal boron nitride (hBN) grown on stepped Ni surfaces are systematically investigated using a cylindrical Ni crystal as a tunable substrate. Our experiments reveal homogeneous hBN monolayer…
In this paper, three novel metallic sp2/sp3 -hybridized Boron Nitride (BN) polymorphs are proposed by first-principles calculations. One of them, named as tP-BN, is predicted based on the evolutionary particle swarm structural search. tP-BN…
In this work, we discovered a fundamental connection between selection for protein stability and emergence of preferred structures of proteins. Using standard exact 3-dimensional lattice model we evolve sequences starting from random ones…
Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage, through to water filtration. The structure-property relationships of these…
We present a novel statistical method for the study of stable atomic configurations in breaking nanowires based on the 2D cross-correlation analysis of conductance versus electrode separation traces. Applying this method, we can clearly…
The integration of density functional theory (DFT) with machine learning enables efficient \textit{ab initio} electronic structure calculations for ultra-large systems. In this work, we develop a transfer learning framework tailored for…
In the purpose of expanding the family of two-dimensional materials, we predict the existence of two-dimensional octa-structure of nitrogen group elements that are composed of squares and octagons in first-principle method based on density…
Group I/II materials exhibit unexpected structural phase transitions at high pressures, providing potential insight into the origins of elemental superconductivity. We present here a computational study of elemental barium and binary…
We introduce a global optimization approach for binary clusters that for a given cluster size is able to directly search for the structure and composition that has the greatest stability. We apply this approach to binary Lennard-Jones…
For face-centered cubic (fcc) and tetragonal (fct) iron a large number of magnetic configurations as a function of crystal structural parameters were studied by means of density functional theory. The stability of magnetic structures was…
Metastable materials are abundant in nature and technology, showcasing remarkable properties that inspire innovative materials design. However, traditional crystal structure prediction methods, which rely solely on energetic factors to…
Identifying the atomic structure of organic-inorganic interfaces is challenging with our current research tools. Interpreting the structure of complex molecular adsorbates from microscopy images can be difficult, and using atomistic…